WorldWideScience

Sample records for performance computing infrastructure

  1. Monitoring performance of a highly distributed and complex computing infrastructure in LHCb

    Science.gov (United States)

    Mathe, Z.; Haen, C.; Stagni, F.

    2017-10-01

    In order to ensure an optimal performance of the LHCb Distributed Computing, based on LHCbDIRAC, it is necessary to be able to inspect the behavior over time of many components: firstly the agents and services on which the infrastructure is built, but also all the computing tasks and data transfers that are managed by this infrastructure. This consists of recording and then analyzing time series of a large number of observables, for which the usage of SQL relational databases is far from optimal. Therefore within DIRAC we have been studying novel possibilities based on NoSQL databases (ElasticSearch, OpenTSDB and InfluxDB) as a result of this study we developed a new monitoring system based on ElasticSearch. It has been deployed on the LHCb Distributed Computing infrastructure for which it collects data from all the components (agents, services, jobs) and allows creating reports through Kibana and a web user interface, which is based on the DIRAC web framework. In this paper we describe this new implementation of the DIRAC monitoring system. We give details on the ElasticSearch implementation within the DIRAC general framework, as well as an overview of the advantages of the pipeline aggregation used for creating a dynamic bucketing of the time series. We present the advantages of using the ElasticSearch DSL high-level library for creating and running queries. Finally we shall present the performances of that system.

  2. Building a High Performance Computing Infrastructure for Novosibirsk Scientific Center

    International Nuclear Information System (INIS)

    Adakin, A; Chubarov, D; Nikultsev, V; Belov, S; Kaplin, V; Sukharev, A; Zaytsev, A; Kalyuzhny, V; Kuchin, N; Lomakin, S

    2011-01-01

    Novosibirsk Scientific Center (NSC), also known worldwide as Akademgorodok, is one of the largest Russian scientific centers hosting Novosibirsk State University (NSU) and more than 35 research organizations of the Siberian Branch of Russian Academy of Sciences including Budker Institute of Nuclear Physics (BINP), Institute of Computational Technologies (ICT), and Institute of Computational Mathematics and Mathematical Geophysics (ICM and MG). Since each institute has specific requirements on the architecture of the computing farms involved in its research field, currently we've got several computing facilities hosted by NSC institutes, each optimized for the particular set of tasks, of which the largest are the NSU Supercomputer Center, Siberian Supercomputer Center (ICM and MG), and a Grid Computing Facility of BINP. Recently a dedicated optical network with the initial bandwidth of 10 Gbps connecting these three facilities was built in order to make it possible to share the computing resources among the research communities of participating institutes, thus providing a common platform for building the computing infrastructure for various scientific projects. Unification of the computing infrastructure is achieved by extensive use of virtualization technologies based on XEN and KVM platforms. The solution implemented was tested thoroughly within the computing environment of KEDR detector experiment which is being carried out at BINP, and foreseen to be applied to the use cases of other HEP experiments in the upcoming future.

  3. High-Performance Compute Infrastructure in Astronomy: 2020 Is Only Months Away

    Science.gov (United States)

    Berriman, B.; Deelman, E.; Juve, G.; Rynge, M.; Vöckler, J. S.

    2012-09-01

    By 2020, astronomy will be awash with as much as 60 PB of public data. Full scientific exploitation of such massive volumes of data will require high-performance computing on server farms co-located with the data. Development of this computing model will be a community-wide enterprise that has profound cultural and technical implications. Astronomers must be prepared to develop environment-agnostic applications that support parallel processing. The community must investigate the applicability and cost-benefit of emerging technologies such as cloud computing to astronomy, and must engage the Computer Science community to develop science-driven cyberinfrastructure such as workflow schedulers and optimizers. We report here the results of collaborations between a science center, IPAC, and a Computer Science research institute, ISI. These collaborations may be considered pathfinders in developing a high-performance compute infrastructure in astronomy. These collaborations investigated two exemplar large-scale science-driver workflow applications: 1) Calculation of an infrared atlas of the Galactic Plane at 18 different wavelengths by placing data from multiple surveys on a common plate scale and co-registering all the pixels; 2) Calculation of an atlas of periodicities present in the public Kepler data sets, which currently contain 380,000 light curves. These products have been generated with two workflow applications, written in C for performance and designed to support parallel processing on multiple environments and platforms, but with different compute resource needs: the Montage image mosaic engine is I/O-bound, and the NASA Star and Exoplanet Database periodogram code is CPU-bound. Our presentation will report cost and performance metrics and lessons-learned for continuing development. Applicability of Cloud Computing: Commercial Cloud providers generally charge for all operations, including processing, transfer of input and output data, and for storage of data

  4. Computational Infrastructure for Nuclear Astrophysics

    International Nuclear Information System (INIS)

    Smith, Michael S.; Hix, W. Raphael; Bardayan, Daniel W.; Blackmon, Jeffery C.; Lingerfelt, Eric J.; Scott, Jason P.; Nesaraja, Caroline D.; Chae, Kyungyuk; Guidry, Michael W.; Koura, Hiroyuki; Meyer, Richard A.

    2006-01-01

    A Computational Infrastructure for Nuclear Astrophysics has been developed to streamline the inclusion of the latest nuclear physics data in astrophysics simulations. The infrastructure consists of a platform-independent suite of computer codes that is freely available online at nucastrodata.org. Features of, and future plans for, this software suite are given

  5. Perancangan dan Analisis Kinerja Private Cloud Computing dengan Layanan Infrastructure-As-A-Service (IAAS

    Directory of Open Access Journals (Sweden)

    Wikranta Arsa

    2014-07-01

    Abstract  Server machine is one of the main components in supporting and developing a web-based scientific work. The high price of the server to be the main obstacle in the student produced a scholarly work. Server configuration that can be done anywhere and anytime to be a fundamental desire, in addition to the booking engine is easy, fast, and flexible is also highly desirable. For that we need a system that can handle these problems. Cloud computing with Infrastructure-As-A-Serveice (IAAS can provide a reliable infrastructure. To determine the performance of the system, we required a performance analysis of cloud server between conventional servers. Results of performance analysis of private cloud computing with Infrastructure-As-A-Service (IAAS indicate that the cloud server performance comparison with conventional server is not too much different and the system resource usage level servers provide more leverage.   Keyword—Cloud Computing, Infrastructure As-A-Service (IAAS, Performance Analysis.

  6. A Distributed Computational Infrastructure for Science and Education

    Directory of Open Access Journals (Sweden)

    Rustam K. Bazarov

    2014-06-01

    Full Text Available Researchers have lately been paying increasingly more attention to parallel and distributed algorithms for solving high-dimensionality problems. In this regard, the issue of acquiring or renting computational resources becomes a topical one for employees of scientific and educational institutions. This article examines technology and methods for organizing a distributed computational infrastructure. The author addresses the experience of creating a high-performance system powered by existing clusterization and grid computing technology. The approach examined in the article helps minimize financial costs, aggregate territorially distributed computational resources and ensures a more rational use of available computer equipment, eliminating its downtimes.

  7. Activity-Driven Computing Infrastructure - Pervasive Computing in Healthcare

    DEFF Research Database (Denmark)

    Bardram, Jakob Eyvind; Christensen, Henrik Bærbak; Olesen, Anders Konring

    In many work settings, and especially in healthcare, work is distributed among many cooperating actors, who are constantly moving around and are frequently interrupted. In line with other researchers, we use the term pervasive computing to describe a computing infrastructure that supports work...

  8. Autonomic Management of Application Workflows on Hybrid Computing Infrastructure

    Directory of Open Access Journals (Sweden)

    Hyunjoo Kim

    2011-01-01

    Full Text Available In this paper, we present a programming and runtime framework that enables the autonomic management of complex application workflows on hybrid computing infrastructures. The framework is designed to address system and application heterogeneity and dynamics to ensure that application objectives and constraints are satisfied. The need for such autonomic system and application management is becoming critical as computing infrastructures become increasingly heterogeneous, integrating different classes of resources from high-end HPC systems to commodity clusters and clouds. For example, the framework presented in this paper can be used to provision the appropriate mix of resources based on application requirements and constraints. The framework also monitors the system/application state and adapts the application and/or resources to respond to changing requirements or environment. To demonstrate the operation of the framework and to evaluate its ability, we employ a workflow used to characterize an oil reservoir executing on a hybrid infrastructure composed of TeraGrid nodes and Amazon EC2 instances of various types. Specifically, we show how different applications objectives such as acceleration, conservation and resilience can be effectively achieved while satisfying deadline and budget constraints, using an appropriate mix of dynamically provisioned resources. Our evaluations also demonstrate that public clouds can be used to complement and reinforce the scheduling and usage of traditional high performance computing infrastructure.

  9. Grids in Europe - a computing infrastructure for science

    International Nuclear Information System (INIS)

    Kranzlmueller, D.

    2008-01-01

    Grids provide sheer unlimited computing power and access to a variety of resources to todays scientists. Moving from a research topic of computer science to a commodity tool for science and research in general, grid infrastructures are built all around the world. This talk provides an overview of the developments of grids in Europe, the status of the so-called national grid initiatives as well as the efforts towards an integrated European grid infrastructure. The latter, summarized under the title of the European Grid Initiative (EGI), promises a permanent and reliable grid infrastructure and its services in a way similar to research networks today. The talk describes the status of these efforts, the plans for the setup of this pan-European e-Infrastructure, and the benefits for the application communities. (author)

  10. A Heterogeneous High-Performance System for Computational and Computer Science

    Science.gov (United States)

    2016-11-15

    expand the research infrastructure at the institution but also to enhance the high -performance computing training provided to both undergraduate and... cloud computing, supercomputing, and the availability of cheap memory and storage led to enormous amounts of data to be sifted through in forensic... High -Performance Computing (HPC) tools that can be integrated with existing curricula and support our research to modernize and dramatically advance

  11. New Features in the Computational Infrastructure for Nuclear Astrophysics

    International Nuclear Information System (INIS)

    Smith, Michael Scott; Lingerfelt, Eric; Scott, J. P.; Nesaraja, Caroline D; Chae, Kyung YuK.; Koura, Hiroyuki; Roberts, Luke F.; Hix, William Raphael; Bardayan, Daniel W.; Blackmon, Jeff C.

    2006-01-01

    A Computational Infrastructure for Nuclear Astrophysics has been developed to streamline the inclusion of the latest nuclear physics data in astrophysics simulations. The infrastructure consists of a platform-independent suite of computer codes that are freely available online at http://nucastrodata.org. The newest features of, and future plans for, this software suite are given

  12. A Cross-Platform Infrastructure for Scalable Runtime Application Performance Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Jack Dongarra; Shirley Moore; Bart Miller, Jeffrey Hollingsworth; Tracy Rafferty

    2005-03-15

    The purpose of this project was to build an extensible cross-platform infrastructure to facilitate the development of accurate and portable performance analysis tools for current and future high performance computing (HPC) architectures. Major accomplishments include tools and techniques for multidimensional performance analysis, as well as improved support for dynamic performance monitoring of multithreaded and multiprocess applications. Previous performance tool development has been limited by the burden of having to re-write a platform-dependent low-level substrate for each architecture/operating system pair in order to obtain the necessary performance data from the system. Manual interpretation of performance data is not scalable for large-scale long-running applications. The infrastructure developed by this project provides a foundation for building portable and scalable performance analysis tools, with the end goal being to provide application developers with the information they need to analyze, understand, and tune the performance of terascale applications on HPC architectures. The backend portion of the infrastructure provides runtime instrumentation capability and access to hardware performance counters, with thread-safety for shared memory environments and a communication substrate to support instrumentation of multiprocess and distributed programs. Front end interfaces provides tool developers with a well-defined, platform-independent set of calls for requesting performance data. End-user tools have been developed that demonstrate runtime data collection, on-line and off-line analysis of performance data, and multidimensional performance analysis. The infrastructure is based on two underlying performance instrumentation technologies. These technologies are the PAPI cross-platform library interface to hardware performance counters and the cross-platform Dyninst library interface for runtime modification of executable images. The Paradyn and KOJAK

  13. Design and study of parallel computing environment of Monte Carlo simulation for particle therapy planning using a public cloud-computing infrastructure

    International Nuclear Information System (INIS)

    Yokohama, Noriya

    2013-01-01

    This report was aimed at structuring the design of architectures and studying performance measurement of a parallel computing environment using a Monte Carlo simulation for particle therapy using a high performance computing (HPC) instance within a public cloud-computing infrastructure. Performance measurements showed an approximately 28 times faster speed than seen with single-thread architecture, combined with improved stability. A study of methods of optimizing the system operations also indicated lower cost. (author)

  14. Integrating multiple scientific computing needs via a Private Cloud infrastructure

    International Nuclear Information System (INIS)

    Bagnasco, S; Berzano, D; Brunetti, R; Lusso, S; Vallero, S

    2014-01-01

    In a typical scientific computing centre, diverse applications coexist and share a single physical infrastructure. An underlying Private Cloud facility eases the management and maintenance of heterogeneous use cases such as multipurpose or application-specific batch farms, Grid sites catering to different communities, parallel interactive data analysis facilities and others. It allows to dynamically and efficiently allocate resources to any application and to tailor the virtual machines according to the applications' requirements. Furthermore, the maintenance of large deployments of complex and rapidly evolving middleware and application software is eased by the use of virtual images and contextualization techniques; for example, rolling updates can be performed easily and minimizing the downtime. In this contribution we describe the Private Cloud infrastructure at the INFN-Torino Computer Centre, that hosts a full-fledged WLCG Tier-2 site and a dynamically expandable PROOF-based Interactive Analysis Facility for the ALICE experiment at the CERN LHC and several smaller scientific computing applications. The Private Cloud building blocks include the OpenNebula software stack, the GlusterFS filesystem (used in two different configurations for worker- and service-class hypervisors) and the OpenWRT Linux distribution (used for network virtualization). A future integration into a federated higher-level infrastructure is made possible by exposing commonly used APIs like EC2 and by using mainstream contextualization tools like CloudInit.

  15. Computational Infrastructure for Geodynamics (CIG)

    Science.gov (United States)

    Gurnis, M.; Kellogg, L. H.; Bloxham, J.; Hager, B. H.; Spiegelman, M.; Willett, S.; Wysession, M. E.; Aivazis, M.

    2004-12-01

    Solid earth geophysicists have a long tradition of writing scientific software to address a wide range of problems. In particular, computer simulations came into wide use in geophysics during the decade after the plate tectonic revolution. Solution schemes and numerical algorithms that developed in other areas of science, most notably engineering, fluid mechanics, and physics, were adapted with considerable success to geophysics. This software has largely been the product of individual efforts and although this approach has proven successful, its strength for solving problems of interest is now starting to show its limitations as we try to share codes and algorithms or when we want to recombine codes in novel ways to produce new science. With funding from the NSF, the US community has embarked on a Computational Infrastructure for Geodynamics (CIG) that will develop, support, and disseminate community-accessible software for the greater geodynamics community from model developers to end-users. The software is being developed for problems involving mantle and core dynamics, crustal and earthquake dynamics, magma migration, seismology, and other related topics. With a high level of community participation, CIG is leveraging state-of-the-art scientific computing into a suite of open-source tools and codes. The infrastructure that we are now starting to develop will consist of: (a) a coordinated effort to develop reusable, well-documented and open-source geodynamics software; (b) the basic building blocks - an infrastructure layer - of software by which state-of-the-art modeling codes can be quickly assembled; (c) extension of existing software frameworks to interlink multiple codes and data through a superstructure layer; (d) strategic partnerships with the larger world of computational science and geoinformatics; and (e) specialized training and workshops for both the geodynamics and broader Earth science communities. The CIG initiative has already started to

  16. Using Infrastructure Awareness to Support the Recruitment of Volunteer Computing Participants

    DEFF Research Database (Denmark)

    Ramos, Juan David Hincapie

    , the properties of computational infrastructures provided in the periphery of the user’s attention, and supporting gradual disclosure of detailed information on user’s request. Working with users of the Mini-Grid, this thesis shows the design process of two infrastructure awareness systems aimed at supporting...... the recruitment of participants, the implementation of one possible technical strategy, and an in-the-wild evaluation. The thesis finalizes with a discussion of the results and implications of infrastructure awareness for participative and other computational infrastructures....

  17. Eucalyptus: an open-source cloud computing infrastructure

    International Nuclear Information System (INIS)

    Nurmi, Daniel; Wolski, Rich; Grzegorczyk, Chris; Obertelli, Graziano; Soman, Sunil; Youseff, Lamia; Zagorodnov, Dmitrii

    2009-01-01

    Utility computing, elastic computing, and cloud computing are all terms that refer to the concept of dynamically provisioning processing time and storage space from a ubiquitous 'cloud' of computational resources. Such systems allow users to acquire and release the resources on demand and provide ready access to data from processing elements, while relegating the physical location and exact parameters of the resources. Over the past few years, such systems have become increasingly popular, but nearly all current cloud computing offerings are either proprietary or depend upon software infrastructure that is invisible to the research community. In this work, we present Eucalyptus, an open-source software implementation of cloud computing that utilizes compute resources that are typically available to researchers, such as clusters and workstation farms. In order to foster community research exploration of cloud computing systems, the design of Eucalyptus emphasizes modularity, allowing researchers to experiment with their own security, scalability, scheduling, and interface implementations. In this paper, we outline the design of Eucalyptus, describe our own implementations of the modular system components, and provide results from experiments that measure performance and scalability of a Eucalyptus installation currently deployed for public use. The main contribution of our work is the presentation of the first research-oriented open-source cloud computing system focused on enabling methodical investigations into the programming, administration, and deployment of systems exploring this novel distributed computing model.

  18. VMEbus based computer and real-time UNIX as infrastructure of DAQ

    International Nuclear Information System (INIS)

    Yasu, Y.; Fujii, H.; Nomachi, M.; Kodama, H.; Inoue, E.; Tajima, Y.; Takeuchi, Y.; Shimizu, Y.

    1994-01-01

    This paper describes what the authors have constructed as the infrastructure of data acquisition system (DAQ). The paper reports recent developments concerned with HP VME board computer with LynxOS (HP742rt/HP-RT) and Alpha/OSF1 with VMEbus adapter. The paper also reports current status of developing a Benchmark Suite for Data Acquisition (DAQBENCH) for measuring not only the performance of VME/CAMAC access but also that of the context switching, the inter-process communications and so on, for various computers including Workstation-based systems and VME board computers

  19. Analysis of CERN computing infrastructure and monitoring data

    Science.gov (United States)

    Nieke, C.; Lassnig, M.; Menichetti, L.; Motesnitsalis, E.; Duellmann, D.

    2015-12-01

    Optimizing a computing infrastructure on the scale of LHC requires a quantitative understanding of a complex network of many different resources and services. For this purpose the CERN IT department and the LHC experiments are collecting a large multitude of logs and performance probes, which are already successfully used for short-term analysis (e.g. operational dashboards) within each group. The IT analytics working group has been created with the goal to bring data sources from different services and on different abstraction levels together and to implement a suitable infrastructure for mid- to long-term statistical analysis. It further provides a forum for joint optimization across single service boundaries and the exchange of analysis methods and tools. To simplify access to the collected data, we implemented an automated repository for cleaned and aggregated data sources based on the Hadoop ecosystem. This contribution describes some of the challenges encountered, such as dealing with heterogeneous data formats, selecting an efficient storage format for map reduce and external access, and will describe the repository user interface. Using this infrastructure we were able to quantitatively analyze the relationship between CPU/wall fraction, latency/throughput constraints of network and disk and the effective job throughput. In this contribution we will first describe the design of the shared analysis infrastructure and then present a summary of first analysis results from the combined data sources.

  20. First results from a combined analysis of CERN computing infrastructure metrics

    Science.gov (United States)

    Duellmann, Dirk; Nieke, Christian

    2017-10-01

    The IT Analysis Working Group (AWG) has been formed at CERN across individual computing units and the experiments to attempt a cross cutting analysis of computing infrastructure and application metrics. In this presentation we will describe the first results obtained using medium/long term data (1 months — 1 year) correlating box level metrics, job level metrics from LSF and HTCondor, IO metrics from the physics analysis disk pools (EOS) and networking and application level metrics from the experiment dashboards. We will cover in particular the measurement of hardware performance and prediction of job duration, the latency sensitivity of different job types and a search for bottlenecks with the production job mix in the current infrastructure. The presentation will conclude with the proposal of a small set of metrics to simplify drawing conclusions also in the more constrained environment of public cloud deployments.

  1. The IceCube Computing Infrastructure Model

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    Besides the big LHC experiments a number of mid-size experiments is coming online which need to define new computing models to meet the demands on processing and storage requirements of those experiments. We present the hybrid computing model of IceCube which leverages GRID models with a more flexible direct user model as an example of a possible solution. In IceCube a central datacenter at UW-Madison servers as Tier-0 with a single Tier-1 datacenter at DESY Zeuthen. We describe the setup of the IceCube computing infrastructure and report on our experience in successfully provisioning the IceCube computing needs.

  2. A Cloud Computing-Enabled Spatio-Temporal Cyber-Physical Information Infrastructure for Efficient Soil Moisture Monitoring

    Directory of Open Access Journals (Sweden)

    Lianjie Zhou

    2016-06-01

    Full Text Available Comprehensive surface soil moisture (SM monitoring is a vital task in precision agriculture applications. SM monitoring includes remote sensing imagery monitoring and in situ sensor-based observational monitoring. Cloud computing can increase computational efficiency enormously. A geographical web service was developed to assist in agronomic decision making, and this tool can be scaled to any location and crop. By integrating cloud computing and the web service-enabled information infrastructure, this study uses the cloud computing-enabled spatio-temporal cyber-physical infrastructure (CESCI to provide an efficient solution for soil moisture monitoring in precision agriculture. On the server side of CESCI, diverse Open Geospatial Consortium web services work closely with each other. Hubei Province, located on the Jianghan Plain in central China, is selected as the remote sensing study area in the experiment. The Baoxie scientific experimental field in Wuhan City is selected as the in situ sensor study area. The results show that the proposed method enhances the efficiency of remote sensing imagery mapping and in situ soil moisture interpolation. In addition, the proposed method is compared to other existing precision agriculture infrastructures. In this comparison, the proposed infrastructure performs soil moisture mapping in Hubei Province in 1.4 min and near real-time in situ soil moisture interpolation in an efficient manner. Moreover, an enhanced performance monitoring method can help to reduce costs in precision agriculture monitoring, as well as increasing agricultural productivity and farmers’ net-income.

  3. A virtual computing infrastructure for TS-CV SCADA systems

    CERN Document Server

    Poulsen, S

    2008-01-01

    In modern data centres, it is an emerging trend to operate and manage computers as software components or logical resources and not as physical machines. This technique is known as â€ワvirtualisation” and the new computers are referred to as â€ワvirtual machines” (VMs). Multiple VMs can be consolidated on a single hardware platform and managed in ways that are not possible with physical machines. However, this is not yet widely practiced for control system deployment. In TS-CV, a collection of VMs or a â€ワvirtual infrastructure” is installed since 2005 for SCADA systems, PLC program development, and alarm transmission. This makes it possible to consolidate distributed, heterogeneous operating systems and applications on a limited number of standardised high-performance servers in the Central Control Room (CCR). More generally, virtualisation assists in offering continuous computing services for controls and maintaining performance and assuring quality. Implementing our systems in a vi...

  4. Network and computing infrastructure for scientific applications in Georgia

    Science.gov (United States)

    Kvatadze, R.; Modebadze, Z.

    2016-09-01

    Status of network and computing infrastructure and available services for research and education community of Georgia are presented. Research and Educational Networking Association - GRENA provides the following network services: Internet connectivity, network services, cyber security, technical support, etc. Computing resources used by the research teams are located at GRENA and at major state universities. GE-01-GRENA site is included in European Grid infrastructure. Paper also contains information about programs of Learning Center and research and development projects in which GRENA is participating.

  5. Eucalyptus: an open-source cloud computing infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Nurmi, Daniel; Wolski, Rich; Grzegorczyk, Chris; Obertelli, Graziano; Soman, Sunil; Youseff, Lamia; Zagorodnov, Dmitrii, E-mail: rich@cs.ucsb.ed [Computer Science Department, University of California, Santa Barbara, CA 93106 (United States) and Eucalyptus Systems Inc., 130 Castilian Dr., Goleta, CA 93117 (United States)

    2009-07-01

    Utility computing, elastic computing, and cloud computing are all terms that refer to the concept of dynamically provisioning processing time and storage space from a ubiquitous 'cloud' of computational resources. Such systems allow users to acquire and release the resources on demand and provide ready access to data from processing elements, while relegating the physical location and exact parameters of the resources. Over the past few years, such systems have become increasingly popular, but nearly all current cloud computing offerings are either proprietary or depend upon software infrastructure that is invisible to the research community. In this work, we present Eucalyptus, an open-source software implementation of cloud computing that utilizes compute resources that are typically available to researchers, such as clusters and workstation farms. In order to foster community research exploration of cloud computing systems, the design of Eucalyptus emphasizes modularity, allowing researchers to experiment with their own security, scalability, scheduling, and interface implementations. In this paper, we outline the design of Eucalyptus, describe our own implementations of the modular system components, and provide results from experiments that measure performance and scalability of a Eucalyptus installation currently deployed for public use. The main contribution of our work is the presentation of the first research-oriented open-source cloud computing system focused on enabling methodical investigations into the programming, administration, and deployment of systems exploring this novel distributed computing model.

  6. Strategic Plan for a Scientific Cloud Computing infrastructure for Europe

    CERN Document Server

    Lengert, Maryline

    2011-01-01

    Here we present the vision, concept and direction for forming a European Industrial Strategy for a Scientific Cloud Computing Infrastructure to be implemented by 2020. This will be the framework for decisions and for securing support and approval in establishing, initially, an R&D European Cloud Computing Infrastructure that serves the need of European Research Area (ERA ) and Space Agencies. This Cloud Infrastructure will have the potential beyond this initial user base to evolve to provide similar services to a broad range of customers including government and SMEs. We explain how this plan aims to support the broader strategic goals of our organisations and identify the benefits to be realised by adopting an industrial Cloud Computing model. We also outline the prerequisites and commitment needed to achieve these objectives.

  7. Cloud computing can simplify HIT infrastructure management.

    Science.gov (United States)

    Glaser, John

    2011-08-01

    Software as a Service (SaaS), built on cloud computing technology, is emerging as the forerunner in IT infrastructure because it helps healthcare providers reduce capital investments. Cloud computing leads to predictable, monthly, fixed operating expenses for hospital IT staff. Outsourced cloud computing facilities are state-of-the-art data centers boasting some of the most sophisticated networking equipment on the market. The SaaS model helps hospitals safeguard against technology obsolescence, minimizes maintenance requirements, and simplifies management.

  8. ORGANIZATION OF CLOUD COMPUTING INFRASTRUCTURE BASED ON SDN NETWORK

    Directory of Open Access Journals (Sweden)

    Alexey A. Efimenko

    2013-01-01

    Full Text Available The article presents the main approaches to cloud computing infrastructure based on the SDN network in present data processing centers (DPC. The main indexes of management effectiveness of network infrastructure of DPC are determined. The examples of solutions for the creation of virtual network devices are provided.

  9. Managing a tier-2 computer centre with a private cloud infrastructure

    International Nuclear Information System (INIS)

    Bagnasco, Stefano; Berzano, Dario; Brunetti, Riccardo; Lusso, Stefano; Vallero, Sara

    2014-01-01

    In a typical scientific computing centre, several applications coexist and share a single physical infrastructure. An underlying Private Cloud infrastructure eases the management and maintenance of such heterogeneous applications (such as multipurpose or application-specific batch farms, Grid sites, interactive data analysis facilities and others), allowing dynamic allocation resources to any application. Furthermore, the maintenance of large deployments of complex and rapidly evolving middleware and application software is eased by the use of virtual images and contextualization techniques. Such infrastructures are being deployed in some large centres (see e.g. the CERN Agile Infrastructure project), but with several open-source tools reaching maturity this is becoming viable also for smaller sites. In this contribution we describe the Private Cloud infrastructure at the INFN-Torino Computer Centre, that hosts a full-fledged WLCG Tier-2 centre, an Interactive Analysis Facility for the ALICE experiment at the CERN LHC and several smaller scientific computing applications. The private cloud building blocks include the OpenNebula software stack, the GlusterFS filesystem and the OpenWRT Linux distribution (used for network virtualization); a future integration into a federated higher-level infrastructure is made possible by exposing commonly used APIs like EC2 and OCCI

  10. NCI's High Performance Computing (HPC) and High Performance Data (HPD) Computing Platform for Environmental and Earth System Data Science

    Science.gov (United States)

    Evans, Ben; Allen, Chris; Antony, Joseph; Bastrakova, Irina; Gohar, Kashif; Porter, David; Pugh, Tim; Santana, Fabiana; Smillie, Jon; Trenham, Claire; Wang, Jingbo; Wyborn, Lesley

    2015-04-01

    The National Computational Infrastructure (NCI) has established a powerful and flexible in-situ petascale computational environment to enable both high performance computing and Data-intensive Science across a wide spectrum of national environmental and earth science data collections - in particular climate, observational data and geoscientific assets. This paper examines 1) the computational environments that supports the modelling and data processing pipelines, 2) the analysis environments and methods to support data analysis, and 3) the progress so far to harmonise the underlying data collections for future interdisciplinary research across these large volume data collections. NCI has established 10+ PBytes of major national and international data collections from both the government and research sectors based on six themes: 1) weather, climate, and earth system science model simulations, 2) marine and earth observations, 3) geosciences, 4) terrestrial ecosystems, 5) water and hydrology, and 6) astronomy, social and biosciences. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. The data is largely sourced from NCI's partners (which include the custodians of many of the major Australian national-scale scientific collections), leading research communities, and collaborating overseas organisations. New infrastructures created at NCI mean the data collections are now accessible within an integrated High Performance Computing and Data (HPC-HPD) environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large-scale high-bandwidth Lustre filesystems. The hardware was designed at inception to ensure that it would allow the layered software environment to flexibly accommodate the advancement of future data science. New approaches to software technology and data models have also had to be developed to enable access to these large and exponentially

  11. A Decision Matrix and Monitoring based Framework for Infrastructure Performance Enhancement in A Cloud based Environment

    OpenAIRE

    Alam, Mansaf; Shakil, Kashish Ara

    2014-01-01

    Cloud environment is very different from traditional computing environment and therefore tracking the performance of cloud leverages additional requirements. The movement of data in cloud is very fast. Hence, it requires that resources and infrastructure available at disposal must be equally competent. Infrastructure level performance in cloud involves the performance of servers, network and storage which act as the heart and soul for driving the entire cloud business. Thus a constant improve...

  12. Measuring and improving infrastructure performance

    National Research Council Canada - National Science Library

    Committee on Measuring and Improving Infrastructure Performance, National Research Council

    .... Developing a framework for guiding attempts at measuring the performance of infrastructure systems and grappling with the concept of defining good performance are the major themes of this book...

  13. School infrastructure performance indicator system (SIPIS)

    CSIR Research Space (South Africa)

    Gibberd, Jeremy T

    2007-05-01

    Full Text Available This paper describes the School Infrastructure Performance Indicator System (SIPIS) project which explores how an indicator system could be developed for school infrastructure in South Africa. It outlines the key challenges faced by the system...

  14. Cloud Computing for Complex Performance Codes.

    Energy Technology Data Exchange (ETDEWEB)

    Appel, Gordon John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hadgu, Teklu [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Klein, Brandon Thorin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Miner, John Gifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-02-01

    This report describes the use of cloud computing services for running complex public domain performance assessment problems. The work consisted of two phases: Phase 1 was to demonstrate complex codes, on several differently configured servers, could run and compute trivial small scale problems in a commercial cloud infrastructure. Phase 2 focused on proving non-trivial large scale problems could be computed in the commercial cloud environment. The cloud computing effort was successfully applied using codes of interest to the geohydrology and nuclear waste disposal modeling community.

  15. Copyright and personal use of CERN’s computing infrastructure

    CERN Multimedia

    IT Department

    2009-01-01

    (La version française sera en ligne prochainement)The rules covering the personal use of CERN’s computing infrastructure are defined in Operational Circular No. 5 and its Subsidiary Rules (see http://cern.ch/ComputingRules). All users of CERN’s computing infrastructure must comply with these rules, whether they access CERN’s computing facilities from within the Organization’s site or at another location. In particular, OC5 clause 17 requires that proprietary rights (the rights in software, music, video, etc.) must be respected. The user is liable for damages resulting from non-compliance. Recently, there have been several violations of OC5, where copyright material was discovered on public world-readable disk space. Please ensure that all material under your responsibility (in particular in files owned by your account) respects proprietary rights, including with respect to the restriction of access by third parties. CERN Security Team

  16. High-Performance Computing Paradigm and Infrastructure

    CERN Document Server

    Yang, Laurence T

    2006-01-01

    With hyperthreading in Intel processors, hypertransport links in next generation AMD processors, multi-core silicon in today's high-end microprocessors from IBM and emerging grid computing, parallel and distributed computers have moved into the mainstream

  17. National Computational Infrastructure for Lattice Gauge Theory

    Energy Technology Data Exchange (ETDEWEB)

    Brower, Richard C.

    2014-04-15

    SciDAC-2 Project The Secret Life of Quarks: National Computational Infrastructure for Lattice Gauge Theory, from March 15, 2011 through March 14, 2012. The objective of this project is to construct the software needed to study quantum chromodynamics (QCD), the theory of the strong interactions of sub-atomic physics, and other strongly coupled gauge field theories anticipated to be of importance in the energy regime made accessible by the Large Hadron Collider (LHC). It builds upon the successful efforts of the SciDAC-1 project National Computational Infrastructure for Lattice Gauge Theory, in which a QCD Applications Programming Interface (QCD API) was developed that enables lattice gauge theorists to make effective use of a wide variety of massively parallel computers. This project serves the entire USQCD Collaboration, which consists of nearly all the high energy and nuclear physicists in the United States engaged in the numerical study of QCD and related strongly interacting quantum field theories. All software developed in it is publicly available, and can be downloaded from a link on the USQCD Collaboration web site, or directly from the github repositories with entrance linke http://usqcd-software.github.io

  18. Review of CERN Computer Centre Infrastructure

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    The CERN Computer Centre is reviewing strategies for optimizing the use of the existing infrastructure in the future, and in the likely scenario that any extension will be remote from CERN, and in the light of the way other large facilities are today being operated. Over the past six months, CERN has been investigating modern and widely-used tools and procedures used for virtualisation, clouds and fabric management in order to reduce operational effort, increase agility and support unattended remote computer centres. This presentation will give the details on the project’s motivations, current status and areas for future investigation.

  19. WRF4G project: Adaptation of WRF Model to Distributed Computing Infrastructures

    Science.gov (United States)

    Cofino, Antonio S.; Fernández Quiruelas, Valvanuz; García Díez, Markel; Blanco Real, Jose C.; Fernández, Jesús

    2013-04-01

    demonstrate the ability of Grid infrastructures in solving a scientific problem with interest and relevance on the meteorology area (implying a high computational cost) we will perform a high resolution hindcast on Southwestern Europe with ERA-Interim re-analysis as boundary and initial conditions. The production of an atmospheric hindcast at high resolution, will provide an appropriate assessment of the possibilities and uncertainties of the WRF model for the evaluation and forecasting of weather, energy and natural hazards. [1] http://www.meteo.unican.es/software/wrf4g

  20. National Computational Infrastructure for Lattice Gauge Theory: Final Report

    International Nuclear Information System (INIS)

    Richard Brower; Norman Christ; Michael Creutz; Paul Mackenzie; John Negele; Claudio Rebbi; David Richards; Stephen Sharpe; Robert Sugar

    2006-01-01

    This is the final report of Department of Energy SciDAC Grant ''National Computational Infrastructure for Lattice Gauge Theory''. It describes the software developed under this grant, which enables the effective use of a wide variety of supercomputers for the study of lattice quantum chromodynamics (lattice QCD). It also describes the research on and development of commodity clusters optimized for the study of QCD. Finally, it provides some high lights of research enabled by the infrastructure created under this grant, as well as a full list of the papers resulting from research that made use of this infrastructure

  1. Enabling High-Performance Computing as a Service

    KAUST Repository

    AbdelBaky, Moustafa; Parashar, Manish; Kim, Hyunjoo; Jordan, Kirk E.; Sachdeva, Vipin; Sexton, James; Jamjoom, Hani; Shae, Zon-Yin; Pencheva, Gergina; Tavakoli, Reza; Wheeler, Mary F.

    2012-01-01

    With the right software infrastructure, clouds can provide scientists with as a service access to high-performance computing resources. An award-winning prototype framework transforms the Blue Gene/P system into an elastic cloud to run a

  2. Reliability issues related to the usage of Cloud Computing in Critical Infrastructures

    OpenAIRE

    Diez Gonzalez, Oscar Manuel; Silva Vazquez, Andrés

    2011-01-01

    The use of cloud computing is extending to all kind of systems, including the ones that are part of Critical Infrastructures, and measuring the reliability is becoming more difficult. Computing is becoming the 5th utility, in part thanks to the use of cloud services. Cloud computing is used now by all types of systems and organizations, including critical infrastructure, creating hidden inter-dependencies on both public and private cloud models. This paper investigates the use of cloud co...

  3. Inclusive vision for high performance computing at the CSIR

    CSIR Research Space (South Africa)

    Gazendam, A

    2006-02-01

    Full Text Available and computationally intensive applications. A number of different technologies and standards were identified as core to the open and distributed high-performance infrastructure envisaged...

  4. Enabling High-Performance Computing as a Service

    KAUST Repository

    AbdelBaky, Moustafa

    2012-10-01

    With the right software infrastructure, clouds can provide scientists with as a service access to high-performance computing resources. An award-winning prototype framework transforms the Blue Gene/P system into an elastic cloud to run a representative HPC application. © 2012 IEEE.

  5. RAPPORT: running scientific high-performance computing applications on the cloud.

    Science.gov (United States)

    Cohen, Jeremy; Filippis, Ioannis; Woodbridge, Mark; Bauer, Daniela; Hong, Neil Chue; Jackson, Mike; Butcher, Sarah; Colling, David; Darlington, John; Fuchs, Brian; Harvey, Matt

    2013-01-28

    Cloud computing infrastructure is now widely used in many domains, but one area where there has been more limited adoption is research computing, in particular for running scientific high-performance computing (HPC) software. The Robust Application Porting for HPC in the Cloud (RAPPORT) project took advantage of existing links between computing researchers and application scientists in the fields of bioinformatics, high-energy physics (HEP) and digital humanities, to investigate running a set of scientific HPC applications from these domains on cloud infrastructure. In this paper, we focus on the bioinformatics and HEP domains, describing the applications and target cloud platforms. We conclude that, while there are many factors that need consideration, there is no fundamental impediment to the use of cloud infrastructure for running many types of HPC applications and, in some cases, there is potential for researchers to benefit significantly from the flexibility offered by cloud platforms.

  6. Infrastructure for Multiphysics Software Integration in High Performance Computing-Aided Science and Engineering

    Energy Technology Data Exchange (ETDEWEB)

    Campbell, Michael T. [Illinois Rocstar LLC, Champaign, IL (United States); Safdari, Masoud [Illinois Rocstar LLC, Champaign, IL (United States); Kress, Jessica E. [Illinois Rocstar LLC, Champaign, IL (United States); Anderson, Michael J. [Illinois Rocstar LLC, Champaign, IL (United States); Horvath, Samantha [Illinois Rocstar LLC, Champaign, IL (United States); Brandyberry, Mark D. [Illinois Rocstar LLC, Champaign, IL (United States); Kim, Woohyun [Illinois Rocstar LLC, Champaign, IL (United States); Sarwal, Neil [Illinois Rocstar LLC, Champaign, IL (United States); Weisberg, Brian [Illinois Rocstar LLC, Champaign, IL (United States)

    2016-10-15

    The project described in this report constructed and exercised an innovative multiphysics coupling toolkit called the Illinois Rocstar MultiPhysics Application Coupling Toolkit (IMPACT). IMPACT is an open source, flexible, natively parallel infrastructure for coupling multiple uniphysics simulation codes into multiphysics computational systems. IMPACT works with codes written in several high-performance-computing (HPC) programming languages, and is designed from the beginning for HPC multiphysics code development. It is designed to be minimally invasive to the individual physics codes being integrated, and has few requirements on those physics codes for integration. The goal of IMPACT is to provide the support needed to enable coupling existing tools together in unique and innovative ways to produce powerful new multiphysics technologies without extensive modification and rewrite of the physics packages being integrated. There are three major outcomes from this project: 1) construction, testing, application, and open-source release of the IMPACT infrastructure, 2) production of example open-source multiphysics tools using IMPACT, and 3) identification and engagement of interested organizations in the tools and applications resulting from the project. This last outcome represents the incipient development of a user community and application echosystem being built using IMPACT. Multiphysics coupling standardization can only come from organizations working together to define needs and processes that span the space of necessary multiphysics outcomes, which Illinois Rocstar plans to continue driving toward. The IMPACT system, including source code, documentation, and test problems are all now available through the public gitHUB.org system to anyone interested in multiphysics code coupling. Many of the basic documents explaining use and architecture of IMPACT are also attached as appendices to this document. Online HTML documentation is available through the gitHUB site

  7. US QCD computational performance studies with PERI

    International Nuclear Information System (INIS)

    Zhang, Y; Fowler, R; Huck, K; Malony, A; Porterfield, A; Reed, D; Shende, S; Taylor, V; Wu, X

    2007-01-01

    We report on some of the interactions between two SciDAC projects: The National Computational Infrastructure for Lattice Gauge Theory (USQCD), and the Performance Engineering Research Institute (PERI). Many modern scientific programs consistently report the need for faster computational resources to maintain global competitiveness. However, as the size and complexity of emerging high end computing (HEC) systems continue to rise, achieving good performance on such systems is becoming ever more challenging. In order to take full advantage of the resources, it is crucial to understand the characteristics of relevant scientific applications and the systems these applications are running on. Using tools developed under PERI and by other performance measurement researchers, we studied the performance of two applications, MILC and Chroma, on several high performance computing systems at DOE laboratories. In the case of Chroma, we discuss how the use of C++ and modern software engineering and programming methods are driving the evolution of performance tools

  8. Evolution of Cloud Storage as Cloud Computing Infrastructure Service

    OpenAIRE

    Rajan, Arokia Paul; Shanmugapriyaa

    2013-01-01

    Enterprises are driving towards less cost, more availability, agility, managed risk - all of which is accelerated towards Cloud Computing. Cloud is not a particular product, but a way of delivering IT services that are consumable on demand, elastic to scale up and down as needed, and follow a pay-for-usage model. Out of the three common types of cloud computing service models, Infrastructure as a Service (IaaS) is a service model that provides servers, computing power, network bandwidth and S...

  9. High-performance computing in seismology

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-09-01

    The scientific, technical, and economic importance of the issues discussed here presents a clear agenda for future research in computational seismology. In this way these problems will drive advances in high-performance computing in the field of seismology. There is a broad community that will benefit from this work, including the petroleum industry, research geophysicists, engineers concerned with seismic hazard mitigation, and governments charged with enforcing a comprehensive test ban treaty. These advances may also lead to new applications for seismological research. The recent application of high-resolution seismic imaging of the shallow subsurface for the environmental remediation industry is an example of this activity. This report makes the following recommendations: (1) focused efforts to develop validated documented software for seismological computations should be supported, with special emphasis on scalable algorithms for parallel processors; (2) the education of seismologists in high-performance computing technologies and methodologies should be improved; (3) collaborations between seismologists and computational scientists and engineers should be increased; (4) the infrastructure for archiving, disseminating, and processing large volumes of seismological data should be improved.

  10. High-performance computing for structural mechanics and earthquake/tsunami engineering

    CERN Document Server

    Hori, Muneo; Ohsaki, Makoto

    2016-01-01

    Huge earthquakes and tsunamis have caused serious damage to important structures such as civil infrastructure elements, buildings and power plants around the globe.  To quantitatively evaluate such damage processes and to design effective prevention and mitigation measures, the latest high-performance computational mechanics technologies, which include telascale to petascale computers, can offer powerful tools. The phenomena covered in this book include seismic wave propagation in the crust and soil, seismic response of infrastructure elements such as tunnels considering soil-structure interactions, seismic response of high-rise buildings, seismic response of nuclear power plants, tsunami run-up over coastal towns and tsunami inundation considering fluid-structure interactions. The book provides all necessary information for addressing these phenomena, ranging from the fundamentals of high-performance computing for finite element methods, key algorithms of accurate dynamic structural analysis, fluid flows ...

  11. High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis.

    Science.gov (United States)

    Simonyan, Vahan; Chumakov, Konstantin; Dingerdissen, Hayley; Faison, William; Goldweber, Scott; Golikov, Anton; Gulzar, Naila; Karagiannis, Konstantinos; Vinh Nguyen Lam, Phuc; Maudru, Thomas; Muravitskaja, Olesja; Osipova, Ekaterina; Pan, Yang; Pschenichnov, Alexey; Rostovtsev, Alexandre; Santana-Quintero, Luis; Smith, Krista; Thompson, Elaine E; Tkachenko, Valery; Torcivia-Rodriguez, John; Voskanian, Alin; Wan, Quan; Wang, Jing; Wu, Tsung-Jung; Wilson, Carolyn; Mazumder, Raja

    2016-01-01

    The High-performance Integrated Virtual Environment (HIVE) is a distributed storage and compute environment designed primarily to handle next-generation sequencing (NGS) data. This multicomponent cloud infrastructure provides secure web access for authorized users to deposit, retrieve, annotate and compute on NGS data, and to analyse the outcomes using web interface visual environments appropriately built in collaboration with research and regulatory scientists and other end users. Unlike many massively parallel computing environments, HIVE uses a cloud control server which virtualizes services, not processes. It is both very robust and flexible due to the abstraction layer introduced between computational requests and operating system processes. The novel paradigm of moving computations to the data, instead of moving data to computational nodes, has proven to be significantly less taxing for both hardware and network infrastructure.The honeycomb data model developed for HIVE integrates metadata into an object-oriented model. Its distinction from other object-oriented databases is in the additional implementation of a unified application program interface to search, view and manipulate data of all types. This model simplifies the introduction of new data types, thereby minimizing the need for database restructuring and streamlining the development of new integrated information systems. The honeycomb model employs a highly secure hierarchical access control and permission system, allowing determination of data access privileges in a finely granular manner without flooding the security subsystem with a multiplicity of rules. HIVE infrastructure will allow engineers and scientists to perform NGS analysis in a manner that is both efficient and secure. HIVE is actively supported in public and private domains, and project collaborations are welcomed. Database URL: https://hive.biochemistry.gwu.edu. © The Author(s) 2016. Published by Oxford University Press.

  12. Grid Computing Making the Global Infrastructure a Reality

    CERN Document Server

    Fox, Geoffrey C; Hey, Anthony J G

    2003-01-01

    Grid computing is applying the resources of many computers in a network to a single problem at the same time Grid computing appears to be a promising trend for three reasons: (1) Its ability to make more cost-effective use of a given amount of computer resources, (2) As a way to solve problems that can't be approached without an enormous amount of computing power (3) Because it suggests that the resources of many computers can be cooperatively and perhaps synergistically harnessed and managed as a collaboration toward a common objective. A number of corporations, professional groups, university consortiums, and other groups have developed or are developing frameworks and software for managing grid computing projects. The European Community (EU) is sponsoring a project for a grid for high-energy physics, earth observation, and biology applications. In the United States, the National Technology Grid is prototyping a computational grid for infrastructure and an access grid for people. Sun Microsystems offers Gri...

  13. Quantum Accelerators for High-performance Computing Systems

    Energy Technology Data Exchange (ETDEWEB)

    Humble, Travis S. [ORNL; Britt, Keith A. [ORNL; Mohiyaddin, Fahd A. [ORNL

    2017-11-01

    We define some of the programming and system-level challenges facing the application of quantum processing to high-performance computing. Alongside barriers to physical integration, prominent differences in the execution of quantum and conventional programs challenges the intersection of these computational models. Following a brief overview of the state of the art, we discuss recent advances in programming and execution models for hybrid quantum-classical computing. We discuss a novel quantum-accelerator framework that uses specialized kernels to offload select workloads while integrating with existing computing infrastructure. We elaborate on the role of the host operating system to manage these unique accelerator resources, the prospects for deploying quantum modules, and the requirements placed on the language hierarchy connecting these different system components. We draw on recent advances in the modeling and simulation of quantum computing systems with the development of architectures for hybrid high-performance computing systems and the realization of software stacks for controlling quantum devices. Finally, we present simulation results that describe the expected system-level behavior of high-performance computing systems composed from compute nodes with quantum processing units. We describe performance for these hybrid systems in terms of time-to-solution, accuracy, and energy consumption, and we use simple application examples to estimate the performance advantage of quantum acceleration.

  14. CernVM Co-Pilot: an Extensible Framework for Building Scalable Computing Infrastructures on the Cloud

    Science.gov (United States)

    Harutyunyan, A.; Blomer, J.; Buncic, P.; Charalampidis, I.; Grey, F.; Karneyeu, A.; Larsen, D.; Lombraña González, D.; Lisec, J.; Segal, B.; Skands, P.

    2012-12-01

    CernVM Co-Pilot is a framework for instantiating an ad-hoc computing infrastructure on top of managed or unmanaged computing resources. Co-Pilot can either be used to create a stand-alone computing infrastructure, or to integrate new computing resources into existing infrastructures (such as Grid or batch). Unlike traditional middleware systems, Co-Pilot components communicate using the Extensible Messaging and Presence protocol (XMPP). This allows the system to be easily scaled in case of a high load, and it also simplifies the development of new components. In this contribution we present the latest developments and the current status of the framework, discuss how it can be extended to suit the needs of a particular community, as well as describe the operational experience of using the framework in the LHC@home 2.0 volunteer computing project.

  15. CernVM Co-Pilot: an Extensible Framework for Building Scalable Computing Infrastructures on the Cloud

    International Nuclear Information System (INIS)

    Harutyunyan, A; Blomer, J; Buncic, P; Charalampidis, I; Grey, F; Karneyeu, A; Larsen, D; Lombraña González, D; Lisec, J; Segal, B; Skands, P

    2012-01-01

    CernVM Co-Pilot is a framework for instantiating an ad-hoc computing infrastructure on top of managed or unmanaged computing resources. Co-Pilot can either be used to create a stand-alone computing infrastructure, or to integrate new computing resources into existing infrastructures (such as Grid or batch). Unlike traditional middleware systems, Co-Pilot components communicate using the Extensible Messaging and Presence protocol (XMPP). This allows the system to be easily scaled in case of a high load, and it also simplifies the development of new components. In this contribution we present the latest developments and the current status of the framework, discuss how it can be extended to suit the needs of a particular community, as well as describe the operational experience of using the framework in the LHC at home 2.0 volunteer computing project.

  16. High performance computing in science and engineering '09: transactions of the High Performance Computing Center, Stuttgart (HLRS) 2009

    National Research Council Canada - National Science Library

    Nagel, Wolfgang E; Kröner, Dietmar; Resch, Michael

    2010-01-01

    ...), NIC/JSC (J¨ u lich), and LRZ (Munich). As part of that strategic initiative, in May 2009 already NIC/JSC has installed the first phase of the GCS HPC Tier-0 resources, an IBM Blue Gene/P with roughly 300.000 Cores, this time in J¨ u lich, With that, the GCS provides the most powerful high-performance computing infrastructure in Europe alread...

  17. Infrastructure Support for Collaborative Pervasive Computing Systems

    DEFF Research Database (Denmark)

    Vestergaard Mogensen, Martin

    Collaborative Pervasive Computing Systems (CPCS) are currently being deployed to support areas such as clinical work, emergency situations, education, ad-hoc meetings, and other areas involving information sharing and collaboration.These systems allow the users to work together synchronously......, but from different places, by sharing information and coordinating activities. Several researchers have shown the value of such distributed collaborative systems. However, building these systems is by no means a trivial task and introduces a lot of yet unanswered questions. The aforementioned areas......, are all characterized by unstable, volatile environments, either due to the underlying components changing or the nomadic work habits of users. A major challenge, for the creators of collaborative pervasive computing systems, is the construction of infrastructures supporting the system. The complexity...

  18. CernVM Co-Pilot: an Extensible Framework for Building Scalable Cloud Computing Infrastructures

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    CernVM Co-Pilot is a framework for instantiating an ad-hoc computing infrastructure on top of distributed computing resources. Such resources include commercial computing clouds (e.g. Amazon EC2), scientific computing clouds (e.g. CERN lxcloud), as well as the machines of users participating in volunteer computing projects (e.g. BOINC). The framework consists of components that communicate using the Extensible Messaging and Presence protocol (XMPP), allowing for new components to be developed in virtually any programming language and interfaced to existing Grid and batch computing infrastructures exploited by the High Energy Physics community. Co-Pilot has been used to execute jobs for both the ALICE and ATLAS experiments at CERN. CernVM Co-Pilot is also one of the enabling technologies behind the LHC@home 2.0 volunteer computing project, which is the first such project that exploits virtual machine technology. The use of virtual machines eliminates the necessity of modifying existing applications and adapt...

  19. Towards Portable Large-Scale Image Processing with High-Performance Computing.

    Science.gov (United States)

    Huo, Yuankai; Blaber, Justin; Damon, Stephen M; Boyd, Brian D; Bao, Shunxing; Parvathaneni, Prasanna; Noguera, Camilo Bermudez; Chaganti, Shikha; Nath, Vishwesh; Greer, Jasmine M; Lyu, Ilwoo; French, William R; Newton, Allen T; Rogers, Baxter P; Landman, Bennett A

    2018-05-03

    High-throughput, large-scale medical image computing demands tight integration of high-performance computing (HPC) infrastructure for data storage, job distribution, and image processing. The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has constructed a large-scale image storage and processing infrastructure that is composed of (1) a large-scale image database using the eXtensible Neuroimaging Archive Toolkit (XNAT), (2) a content-aware job scheduling platform using the Distributed Automation for XNAT pipeline automation tool (DAX), and (3) a wide variety of encapsulated image processing pipelines called "spiders." The VUIIS CCI medical image data storage and processing infrastructure have housed and processed nearly half-million medical image volumes with Vanderbilt Advanced Computing Center for Research and Education (ACCRE), which is the HPC facility at the Vanderbilt University. The initial deployment was natively deployed (i.e., direct installations on a bare-metal server) within the ACCRE hardware and software environments, which lead to issues of portability and sustainability. First, it could be laborious to deploy the entire VUIIS CCI medical image data storage and processing infrastructure to another HPC center with varying hardware infrastructure, library availability, and software permission policies. Second, the spiders were not developed in an isolated manner, which has led to software dependency issues during system upgrades or remote software installation. To address such issues, herein, we describe recent innovations using containerization techniques with XNAT/DAX which are used to isolate the VUIIS CCI medical image data storage and processing infrastructure from the underlying hardware and software environments. The newly presented XNAT/DAX solution has the following new features: (1) multi-level portability from system level to the application level, (2) flexible and dynamic software

  20. Problem-Oriented Simulation Packages and Computational Infrastructure for Numerical Studies of Powerful Gyrotrons

    International Nuclear Information System (INIS)

    Damyanova, M; Sabchevski, S; Vasileva, E; Balabanova, E; Zhelyazkov, I; Dankov, P; Malinov, P

    2016-01-01

    Powerful gyrotrons are necessary as sources of strong microwaves for electron cyclotron resonance heating (ECRH) and electron cyclotron current drive (ECCD) of magnetically confined plasmas in various reactors (most notably ITER) for controlled thermonuclear fusion. Adequate physical models and efficient problem-oriented software packages are essential tools for numerical studies, analysis, optimization and computer-aided design (CAD) of such high-performance gyrotrons operating in a CW mode and delivering output power of the order of 1-2 MW. In this report we present the current status of our simulation tools (physical models, numerical codes, pre- and post-processing programs, etc.) as well as the computational infrastructure on which they are being developed, maintained and executed. (paper)

  1. German contributions to the CMS computing infrastructure

    International Nuclear Information System (INIS)

    Scheurer, A

    2010-01-01

    The CMS computing model anticipates various hierarchically linked tier centres to counter the challenges provided by the enormous amounts of data which will be collected by the CMS detector at the Large Hadron Collider, LHC, at CERN. During the past years, various computing exercises were performed to test the readiness of the computing infrastructure, the Grid middleware and the experiment's software for the startup of the LHC which took place in September 2008. In Germany, several tier sites are set up to allow for an efficient and reliable way to simulate possible physics processes as well as to reprocess, analyse and interpret the numerous stored collision events of the experiment. It will be shown that the German computing sites played an important role during the experiment's preparation phase and during data-taking of CMS and, therefore, scientific groups in Germany will be ready to compete for discoveries in this new era of particle physics. This presentation focuses on the German Tier-1 centre GridKa, located at Forschungszentrum Karlsruhe, the German CMS Tier-2 federation DESY/RWTH with installations at the University of Aachen and the research centre DESY. In addition, various local computing resources in Aachen, Hamburg and Karlsruhe are briefly introduced as well. It will be shown that an excellent cooperation between the different German institutions and physicists led to well established computing sites which cover all parts of the CMS computing model. Therefore, the following topics are discussed and the achieved goals and the gained knowledge are depicted: data management and distribution among the different tier sites, Grid-based Monte Carlo production at the Tier-2 as well as Grid-based and locally submitted inhomogeneous user analyses at the Tier-3s. Another important task is to ensure a proper and reliable operation 24 hours a day, especially during the time of data-taking. For this purpose, the meta-monitoring tool 'HappyFace', which was

  2. National Computational Infrastructure for Lattice Gauge Theory: Final report

    International Nuclear Information System (INIS)

    Reed, Daniel A.

    2008-01-01

    In this document we describe work done under the SciDAC-1 Project National Computerational Infrastructure for Lattice Gauge Theory. The objective of this project was to construct the computational infrastructure needed to study quantum chromodynamics (QCD). Nearly all high energy and nuclear physicists in the United States working on the numerical study of QCD are involved in the project, as are Brookhaven National Laboratory (BNL), Fermi National Accelerator Laboratory (FNAL), and Thomas Jefferson National Accelerator Facility (JLab). A list of the senior participants is given in Appendix A.2. The project includes the development of community software for the effective use of the terascale computers, and the research and development of commodity clusters optimized for the study of QCD. The software developed as part of this effort is publicly available, and is being widely used by physicists in the United States and abroad. The prototype clusters built with SciDAC-1 fund have been used to test the software, and are available to lattice gauge theorists in the United States on a peer reviewed basis

  3. Defense strategies for cloud computing multi-site server infrastructures

    Energy Technology Data Exchange (ETDEWEB)

    Rao, Nageswara S. [ORNL; Ma, Chris Y. T. [Hang Seng Management College, Hon Kong; He, Fei [Texas A& M University, Kingsville, TX, USA

    2018-01-01

    We consider cloud computing server infrastructures for big data applications, which consist of multiple server sites connected over a wide-area network. The sites house a number of servers, network elements and local-area connections, and the wide-area network plays a critical, asymmetric role of providing vital connectivity between them. We model this infrastructure as a system of systems, wherein the sites and wide-area network are represented by their cyber and physical components. These components can be disabled by cyber and physical attacks, and also can be protected against them using component reinforcements. The effects of attacks propagate within the systems, and also beyond them via the wide-area network.We characterize these effects using correlations at two levels using: (a) aggregate failure correlation function that specifies the infrastructure failure probability given the failure of an individual site or network, and (b) first-order differential conditions on system survival probabilities that characterize the component-level correlations within individual systems. We formulate a game between an attacker and a provider using utility functions composed of survival probability and cost terms. At Nash Equilibrium, we derive expressions for the expected capacity of the infrastructure given by the number of operational servers connected to the network for sum-form, product-form and composite utility functions.

  4. DEISA2: supporting and developing a European high-performance computing ecosystem

    International Nuclear Information System (INIS)

    Lederer, H

    2008-01-01

    The DEISA Consortium has deployed and operated the Distributed European Infrastructure for Supercomputing Applications. Through the EU FP7 DEISA2 project (funded for three years as of May 2008), the consortium is continuing to support and enhance the distributed high-performance computing infrastructure and its activities and services relevant for applications enabling, operation, and technologies, as these are indispensable for the effective support of computational sciences for high-performance computing (HPC). The service-provisioning model will be extended from one that supports single projects to one supporting virtual European communities. Collaborative activities will also be carried out with new European and other international initiatives. Of strategic importance is cooperation with the PRACE project, which is preparing for the installation of a limited number of leadership-class Tier-0 supercomputers in Europe. The key role and aim of DEISA will be to deliver a turnkey operational solution for a persistent European HPC ecosystem that will integrate national Tier-1 centers and the new Tier-0 centers

  5. WISDOM-II: Screening against multiple targets implicated in malaria using computational grid infrastructures

    Directory of Open Access Journals (Sweden)

    Kenyon Colin

    2009-05-01

    Full Text Available Abstract Background Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the Plasmodium parasite, some are promising targets to carry out rational drug discovery. Motivation Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR, and on a new promising one, glutathione-S-transferase. Methods In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate in silico docking and in information technology to design and operate large scale grid infrastructures. Results On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, In vitro results are underway for all the targets against which screening is performed. Conclusion The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software

  6. Climate change and infrastructure performance: should we worry about?

    NARCIS (Netherlands)

    Oslakovic, I.; Maat, ter H.W.; Hartmann, A.; Dewulf, G.

    2012-01-01

    Although it has been known for a while that climate-related factors account for the performance development of infrastructure, it remains difficult for infrastructure manager to estimate the effect of the anticipated climate change. The impact of climate factors differs very much between

  7. Deploy Nalu/Kokkos algorithmic infrastructure with performance benchmarking.

    Energy Technology Data Exchange (ETDEWEB)

    Domino, Stefan P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ananthan, Shreyas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Knaus, Robert C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Williams, Alan B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-09-29

    assembly timings faster than that observed on Haswell architecture. The computational workload of higher-order meshes, therefore, seems ideally suited for the many-core architecture and justi es further exploration of higher-order on NGP platforms. A Trilinos/Tpetra-based multi-threaded GMRES preconditioned by symmetric Gauss Seidel (SGS) represents the core solver infrastructure for the low-Mach advection/diffusion implicit solves. The threaded solver stack has been tested on small problems on NREL's Peregrine system using the newly developed and deployed Kokkos-view/SIMD kernels. fforts are underway to deploy the Tpetra-based solver stack on NERSC Cori system to benchmark its performance at scale on KNL machines.

  8. Computational infrastructure for law enforcement. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Lades, M.; Kunz, C.; Strikos, I.

    1997-02-01

    This project planned to demonstrate the leverage of enhanced computational infrastructure for law enforcement by demonstrating the face recognition capability at LLNL. The project implemented a face finder module extending the segmentation capabilities of the current face recognition so it was capable of processing different image formats and sizes and create the pilot of a network-accessible image database for the demonstration of face recognition capabilities. The project was funded at $40k (2 man-months) for a feasibility study. It investigated several essential components of a networked face recognition system which could help identify, apprehend, and convict criminals.

  9. Network computing infrastructure to share tools and data in global nuclear energy partnership

    International Nuclear Information System (INIS)

    Kim, Guehee; Suzuki, Yoshio; Teshima, Naoya

    2010-01-01

    CCSE/JAEA (Center for Computational Science and e-Systems/Japan Atomic Energy Agency) integrated a prototype system of a network computing infrastructure for sharing tools and data to support the U.S. and Japan collaboration in GNEP (Global Nuclear Energy Partnership). We focused on three technical issues to apply our information process infrastructure, which are accessibility, security, and usability. In designing the prototype system, we integrated and improved both network and Web technologies. For the accessibility issue, we adopted SSL-VPN (Security Socket Layer - Virtual Private Network) technology for the access beyond firewalls. For the security issue, we developed an authentication gateway based on the PKI (Public Key Infrastructure) authentication mechanism to strengthen the security. Also, we set fine access control policy to shared tools and data and used shared key based encryption method to protect tools and data against leakage to third parties. For the usability issue, we chose Web browsers as user interface and developed Web application to provide functions to support sharing tools and data. By using WebDAV (Web-based Distributed Authoring and Versioning) function, users can manipulate shared tools and data through the Windows-like folder environment. We implemented the prototype system in Grid infrastructure for atomic energy research: AEGIS (Atomic Energy Grid Infrastructure) developed by CCSE/JAEA. The prototype system was applied for the trial use in the first period of GNEP. (author)

  10. X-ray-induced acoustic computed tomography of concrete infrastructure

    Science.gov (United States)

    Tang, Shanshan; Ramseyer, Chris; Samant, Pratik; Xiang, Liangzhong

    2018-02-01

    X-ray-induced Acoustic Computed Tomography (XACT) takes advantage of both X-ray absorption contrast and high ultrasonic resolution in a single imaging modality by making use of the thermoacoustic effect. In XACT, X-ray absorption by defects and other structures in concrete create thermally induced pressure jumps that launch ultrasonic waves, which are then received by acoustic detectors to form images. In this research, XACT imaging was used to non-destructively test and identify defects in concrete. For concrete structures, we conclude that XACT imaging allows multiscale imaging at depths ranging from centimeters to meters, with spatial resolutions from sub-millimeter to centimeters. XACT imaging also holds promise for single-side testing of concrete infrastructure and provides an optimal solution for nondestructive inspection of existing bridges, pavement, nuclear power plants, and other concrete infrastructure.

  11. Distributed Monitoring Infrastructure for Worldwide LHC Computing Grid

    CERN Document Server

    Andrade, Pedro; Bhatt, Kislay; Chand, Phool; Collados, David; Duggal, Vibhuti; Fuente, Paloma; Hayashi, Soichi; Imamagic, Emir; Joshi, Pradyumna; Kalmady, Rajesh; Karnani, Urvashi; Kumar, Vaibhav; Lapka, Wojciech; Quick, Robert; Tarragon, Jacobo; Teige, Scott; Triantafyllidis, Christos

    2012-01-01

    The journey of a monitoring probe from its development phase to the moment its execution result is presented in an availability report is a complex process. It goes through multiple phases such as development, testing, integration, release, deployment, execution, data aggregation, computation, and reporting. Further, it involves people with different roles (developers, site managers, VO managers, service managers, management), from different middleware providers (ARC, dCache, gLite, UNICORE and VDT), consortiums (WLCG, EMI, EGI, OSG), and operational teams (GOC, OMB, OTAG, CSIRT). The seamless harmonization of these distributed actors is in daily use for monitoring of the WLCG infrastructure. In this paper we describe the monitoring of the WLCG infrastructure from the operational perspective. We explain the complexity of the journey of a monitoring probe from its execution on a grid node to the visualization on the MyWLCG portal where it is exposed to other clients. This monitoring workflow profits from the i...

  12. FY 1995 Blue Book: High Performance Computing and Communications: Technology for the National Information Infrastructure

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — The Federal High Performance Computing and Communications HPCC Program was created to accelerate the development of future generations of high performance computers...

  13. Comprehensive Simulation Lifecycle Management for High Performance Computing Modeling and Simulation, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — There are significant logistical barriers to entry-level high performance computing (HPC) modeling and simulation (M IllinoisRocstar) sets up the infrastructure for...

  14. Software Infrastructure for Computer-aided Drug Discovery and Development, a Practical Example with Guidelines.

    Science.gov (United States)

    Moretti, Loris; Sartori, Luca

    2016-09-01

    In the field of Computer-Aided Drug Discovery and Development (CADDD) the proper software infrastructure is essential for everyday investigations. The creation of such an environment should be carefully planned and implemented with certain features in order to be productive and efficient. Here we describe a solution to integrate standard computational services into a functional unit that empowers modelling applications for drug discovery. This system allows users with various level of expertise to run in silico experiments automatically and without the burden of file formatting for different software, managing the actual computation, keeping track of the activities and graphical rendering of the structural outcomes. To showcase the potential of this approach, performances of five different docking programs on an Hiv-1 protease test set are presented. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Benchmarking infrastructure for mutation text mining.

    Science.gov (United States)

    Klein, Artjom; Riazanov, Alexandre; Hindle, Matthew M; Baker, Christopher Jo

    2014-02-25

    Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system. While large benchmark corpora for biological entity and relation extraction are focused mostly on genes, proteins, diseases, and species, our benchmarking infrastructure fills the gap for mutation information. The core infrastructure comprises (1) an ontology for modelling annotations, (2) SPARQL queries for computing performance metrics, and (3) a sizeable collection of manually curated documents, that can support mutation grounding and mutation impact extraction experiments. We have developed the principal infrastructure for the benchmarking of mutation text mining tasks. The use of RDF and OWL as the representation for corpora ensures extensibility. The infrastructure is suitable for out-of-the-box use in several important scenarios and is ready, in its current state, for initial community adoption.

  16. Benchmarking infrastructure for mutation text mining

    Science.gov (United States)

    2014-01-01

    Background Experimental research on the automatic extraction of information about mutations from texts is greatly hindered by the lack of consensus evaluation infrastructure for the testing and benchmarking of mutation text mining systems. Results We propose a community-oriented annotation and benchmarking infrastructure to support development, testing, benchmarking, and comparison of mutation text mining systems. The design is based on semantic standards, where RDF is used to represent annotations, an OWL ontology provides an extensible schema for the data and SPARQL is used to compute various performance metrics, so that in many cases no programming is needed to analyze results from a text mining system. While large benchmark corpora for biological entity and relation extraction are focused mostly on genes, proteins, diseases, and species, our benchmarking infrastructure fills the gap for mutation information. The core infrastructure comprises (1) an ontology for modelling annotations, (2) SPARQL queries for computing performance metrics, and (3) a sizeable collection of manually curated documents, that can support mutation grounding and mutation impact extraction experiments. Conclusion We have developed the principal infrastructure for the benchmarking of mutation text mining tasks. The use of RDF and OWL as the representation for corpora ensures extensibility. The infrastructure is suitable for out-of-the-box use in several important scenarios and is ready, in its current state, for initial community adoption. PMID:24568600

  17. The performance of low-cost commercial cloud computing as an alternative in computational chemistry.

    Science.gov (United States)

    Thackston, Russell; Fortenberry, Ryan C

    2015-05-05

    The growth of commercial cloud computing (CCC) as a viable means of computational infrastructure is largely unexplored for the purposes of quantum chemistry. In this work, the PSI4 suite of computational chemistry programs is installed on five different types of Amazon World Services CCC platforms. The performance for a set of electronically excited state single-point energies is compared between these CCC platforms and typical, "in-house" physical machines. Further considerations are made for the number of cores or virtual CPUs (vCPUs, for the CCC platforms), but no considerations are made for full parallelization of the program (even though parallelization of the BLAS library is implemented), complete high-performance computing cluster utilization, or steal time. Even with this most pessimistic view of the computations, CCC resources are shown to be more cost effective for significant numbers of typical quantum chemistry computations. Large numbers of large computations are still best utilized by more traditional means, but smaller-scale research may be more effectively undertaken through CCC services. © 2015 Wiley Periodicals, Inc.

  18. Design and implementation of a reliable and cost-effective cloud computing infrastructure: the INFN Napoli experience

    International Nuclear Information System (INIS)

    Capone, V; Esposito, R; Pardi, S; Taurino, F; Tortone, G

    2012-01-01

    Over the last few years we have seen an increasing number of services and applications needed to manage and maintain cloud computing facilities. This is particularly true for computing in high energy physics, which often requires complex configurations and distributed infrastructures. In this scenario a cost effective rationalization and consolidation strategy is the key to success in terms of scalability and reliability. In this work we describe an IaaS (Infrastructure as a Service) cloud computing system, with high availability and redundancy features, which is currently in production at INFN-Naples and ATLAS Tier-2 data centre. The main goal we intended to achieve was a simplified method to manage our computing resources and deliver reliable user services, reusing existing hardware without incurring heavy costs. A combined usage of virtualization and clustering technologies allowed us to consolidate our services on a small number of physical machines, reducing electric power costs. As a result of our efforts we developed a complete solution for data and computing centres that can be easily replicated using commodity hardware. Our architecture consists of 2 main subsystems: a clustered storage solution, built on top of disk servers running GlusterFS file system, and a virtual machines execution environment. GlusterFS is a network file system able to perform parallel writes on multiple disk servers, providing this way live replication of data. High availability is also achieved via a network configuration using redundant switches and multiple paths between hypervisor hosts and disk servers. We also developed a set of management scripts to easily perform basic system administration tasks such as automatic deployment of new virtual machines, adaptive scheduling of virtual machines on hypervisor hosts, live migration and automated restart in case of hypervisor failures.

  19. Design and implementation of a reliable and cost-effective cloud computing infrastructure: the INFN Napoli experience

    Science.gov (United States)

    Capone, V.; Esposito, R.; Pardi, S.; Taurino, F.; Tortone, G.

    2012-12-01

    Over the last few years we have seen an increasing number of services and applications needed to manage and maintain cloud computing facilities. This is particularly true for computing in high energy physics, which often requires complex configurations and distributed infrastructures. In this scenario a cost effective rationalization and consolidation strategy is the key to success in terms of scalability and reliability. In this work we describe an IaaS (Infrastructure as a Service) cloud computing system, with high availability and redundancy features, which is currently in production at INFN-Naples and ATLAS Tier-2 data centre. The main goal we intended to achieve was a simplified method to manage our computing resources and deliver reliable user services, reusing existing hardware without incurring heavy costs. A combined usage of virtualization and clustering technologies allowed us to consolidate our services on a small number of physical machines, reducing electric power costs. As a result of our efforts we developed a complete solution for data and computing centres that can be easily replicated using commodity hardware. Our architecture consists of 2 main subsystems: a clustered storage solution, built on top of disk servers running GlusterFS file system, and a virtual machines execution environment. GlusterFS is a network file system able to perform parallel writes on multiple disk servers, providing this way live replication of data. High availability is also achieved via a network configuration using redundant switches and multiple paths between hypervisor hosts and disk servers. We also developed a set of management scripts to easily perform basic system administration tasks such as automatic deployment of new virtual machines, adaptive scheduling of virtual machines on hypervisor hosts, live migration and automated restart in case of hypervisor failures.

  20. Enhanced computational infrastructure for data analysis at the DIII-D National Fusion Facility

    International Nuclear Information System (INIS)

    Schissel, D.P.; Peng, Q.; Schachter, J.; Terpstra, T.B.; Casper, T.A.; Freeman, J.; Jong, R.; Keith, K.M.; McHarg, B.B.; Meyer, W.H.; Parker, C.T.

    2000-01-01

    Recently a number of enhancements to the computer hardware infrastructure have been implemented at the DIII-D National Fusion Facility. Utilizing these improvements to the hardware infrastructure, software enhancements are focusing on streamlined analysis, automation, and graphical user interface (GUI) systems to enlarge the user base. The adoption of the load balancing software package LSF Suite by Platform Computing has dramatically increased the availability of CPU cycles and the efficiency of their use. Streamlined analysis has been aided by the adoption of the MDSplus system to provide a unified interface to analyzed DIII-D data. The majority of MDSplus data is made available in between pulses giving the researcher critical information before setting up the next pulse. Work on data viewing and analysis tools focuses on efficient GUI design with object-oriented programming (OOP) for maximum code flexibility. Work to enhance the computational infrastructure at DIII-D has included a significant effort to aid the remote collaborator since the DIII-D National Team consists of scientists from nine national laboratories, 19 foreign laboratories, 16 universities, and five industrial partnerships. As a result of this work, DIII-D data is available on a 24x7 basis from a set of viewing and analysis tools that can be run on either the collaborators' or DIII-D's computer systems. Additionally, a web based data and code documentation system has been created to aid the novice and expert user alike

  1. Enhanced Computational Infrastructure for Data Analysis at the DIII-D National Fusion Facility

    International Nuclear Information System (INIS)

    Schissel, D.P.; Peng, Q.; Schachter, J.; Terpstra, T.B.; Casper, T.A.; Freeman, J.; Jong, R.; Keith, K.M.; Meyer, W.H.; Parker, C.T.; McCharg, B.B.

    1999-01-01

    Recently a number of enhancements to the computer hardware infrastructure have been implemented at the DIII-D National Fusion Facility. Utilizing these improvements to the hardware infrastructure, software enhancements are focusing on streamlined analysis, automation, and graphical user interface (GUI) systems to enlarge the user base. The adoption of the load balancing software package LSF Suite by Platform Computing has dramatically increased the availability of CPU cycles and the efficiency of their use. Streamlined analysis has been aided by the adoption of the MDSplus system to provide a unified interface to analyzed DIII-D data. The majority of MDSplus data is made available in between pulses giving the researcher critical information before setting up the next pulse. Work on data viewing and analysis tools focuses on efficient GUI design with object-oriented programming (OOP) for maximum code flexibility. Work to enhance the computational infrastructure at DIII-D has included a significant effort to aid the remote collaborator since the DIII-D National Team consists of scientists from 9 national laboratories, 19 foreign laboratories, 16 universities, and 5 industrial partnerships. As a result of this work, DIII-D data is available on a 24 x 7 basis from a set of viewing and analysis tools that can be run either on the collaborators' or DIII-Ds computer systems. Additionally, a Web based data and code documentation system has been created to aid the novice and expert user alike

  2. @neurIST: infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services.

    Science.gov (United States)

    Benkner, Siegfried; Arbona, Antonio; Berti, Guntram; Chiarini, Alessandro; Dunlop, Robert; Engelbrecht, Gerhard; Frangi, Alejandro F; Friedrich, Christoph M; Hanser, Susanne; Hasselmeyer, Peer; Hose, Rod D; Iavindrasana, Jimison; Köhler, Martin; Iacono, Luigi Lo; Lonsdale, Guy; Meyer, Rodolphe; Moore, Bob; Rajasekaran, Hariharan; Summers, Paul E; Wöhrer, Alexander; Wood, Steven

    2010-11-01

    The increasing volume of data describing human disease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the @neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system's architecture is generic enough that it could be adapted to the treatment of other diseases. Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers clinicians the tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medical researchers gain access to a critical mass of aneurysm related data due to the system's ability to federate distributed information sources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access and work on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand for performing computationally intensive simulations for treatment planning and research.

  3. Procurement of complex performance in public infrastructure: a process perspective

    OpenAIRE

    Hartmann, Andreas; Roehrich, Jens; Davies, Andrew; Frederiksen, Lars; Davies, J.; Harrington, T.; Kirkwood, D.; Holweg, M.

    2011-01-01

    The paper analyzes the process of transitioning from procuring single products and services to procuring complex performance in public infrastructure. The aim is to examine the change in the interactions between buyer and supplier, the emergence of value co-creation and the capability development during the transition process. Based on a multiple, longitudinal case study the paper proposes three generic transition stages towards increased performance and infrastructural complexity. These stag...

  4. Cloud Computing and Virtual Desktop Infrastructures in Afloat Environments

    OpenAIRE

    Gillette, Stefan E.

    2012-01-01

    The phenomenon of “cloud computing” has become ubiquitous among users of the Internet and many commercial applications. Yet, the U.S. Navy has conducted limited research in this nascent technology. This thesis explores the application and integration of cloud computing both at the shipboard level and in a multi-ship environment. A virtual desktop infrastructure, mirroring a shipboard environment, was built and analyzed in the Cloud Lab at the Naval Postgraduate School, which offers a potentia...

  5. Performance analysis of cloud computing services for many-tasks scientific computing

    NARCIS (Netherlands)

    Iosup, A.; Ostermann, S.; Yigitbasi, M.N.; Prodan, R.; Fahringer, T.; Epema, D.H.J.

    2011-01-01

    Cloud computing is an emerging commercial infrastructure paradigm that promises to eliminate the need for maintaining expensive computing facilities by companies and institutes alike. Through the use of virtualization and resource time sharing, clouds serve with a single set of physical resources a

  6. High-Performance Java Codes for Computational Fluid Dynamics

    Science.gov (United States)

    Riley, Christopher; Chatterjee, Siddhartha; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

    2001-01-01

    The computational science community is reluctant to write large-scale computationally -intensive applications in Java due to concerns over Java's poor performance, despite the claimed software engineering advantages of its object-oriented features. Naive Java implementations of numerical algorithms can perform poorly compared to corresponding Fortran or C implementations. To achieve high performance, Java applications must be designed with good performance as a primary goal. This paper presents the object-oriented design and implementation of two real-world applications from the field of Computational Fluid Dynamics (CFD): a finite-volume fluid flow solver (LAURA, from NASA Langley Research Center), and an unstructured mesh adaptation algorithm (2D_TAG, from NASA Ames Research Center). This work builds on our previous experience with the design of high-performance numerical libraries in Java. We examine the performance of the applications using the currently available Java infrastructure and show that the Java version of the flow solver LAURA performs almost within a factor of 2 of the original procedural version. Our Java version of the mesh adaptation algorithm 2D_TAG performs within a factor of 1.5 of its original procedural version on certain platforms. Our results demonstrate that object-oriented software design principles are not necessarily inimical to high performance.

  7. Large-Scale Data Collection Metadata Management at the National Computation Infrastructure

    Science.gov (United States)

    Wang, J.; Evans, B. J. K.; Bastrakova, I.; Ryder, G.; Martin, J.; Duursma, D.; Gohar, K.; Mackey, T.; Paget, M.; Siddeswara, G.

    2014-12-01

    Data Collection management has become an essential activity at the National Computation Infrastructure (NCI) in Australia. NCI's partners (CSIRO, Bureau of Meteorology, Australian National University, and Geoscience Australia), supported by the Australian Government and Research Data Storage Infrastructure (RDSI), have established a national data resource that is co-located with high-performance computing. This paper addresses the metadata management of these data assets over their lifetime. NCI manages 36 data collections (10+ PB) categorised as earth system sciences, climate and weather model data assets and products, earth and marine observations and products, geosciences, terrestrial ecosystem, water management and hydrology, astronomy, social science and biosciences. The data is largely sourced from NCI partners, the custodians of many of the national scientific records, and major research community organisations. The data is made available in a HPC and data-intensive environment - a ~56000 core supercomputer, virtual labs on a 3000 core cloud system, and data services. By assembling these large national assets, new opportunities have arisen to harmonise the data collections, making a powerful cross-disciplinary resource.To support the overall management, a Data Management Plan (DMP) has been developed to record the workflows, procedures, the key contacts and responsibilities. The DMP has fields that can be exported to the ISO19115 schema and to the collection level catalogue of GeoNetwork. The subset or file level metadata catalogues are linked with the collection level through parent-child relationship definition using UUID. A number of tools have been developed that support interactive metadata management, bulk loading of data, and support for computational workflows or data pipelines. NCI creates persistent identifiers for each of the assets. The data collection is tracked over its lifetime, and the recognition of the data providers, data owners, data

  8. Sampling Approaches for Multi-Domain Internet Performance Measurement Infrastructures

    Energy Technology Data Exchange (ETDEWEB)

    Calyam, Prasad

    2014-09-15

    The next-generation of high-performance networks being developed in DOE communities are critical for supporting current and emerging data-intensive science applications. The goal of this project is to investigate multi-domain network status sampling techniques and tools to measure/analyze performance, and thereby provide “network awareness” to end-users and network operators in DOE communities. We leverage the infrastructure and datasets available through perfSONAR, which is a multi-domain measurement framework that has been widely deployed in high-performance computing and networking communities; the DOE community is a core developer and the largest adopter of perfSONAR. Our investigations include development of semantic scheduling algorithms, measurement federation policies, and tools to sample multi-domain and multi-layer network status within perfSONAR deployments. We validate our algorithms and policies with end-to-end measurement analysis tools for various monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. In addition, we develop a multi-domain architecture for an enterprise-specific perfSONAR deployment that can implement monitoring-objective based sampling and that adheres to any domain-specific measurement policies.

  9. A Survey of Software Infrastructures and Frameworks for Ubiquitous Computing

    Directory of Open Access Journals (Sweden)

    Christoph Endres

    2005-01-01

    Full Text Available In this survey, we discuss 29 software infrastructures and frameworks which support the construction of distributed interactive systems. They range from small projects with one implemented prototype to large scale research efforts, and they come from the fields of Augmented Reality (AR, Intelligent Environments, and Distributed Mobile Systems. In their own way, they can all be used to implement various aspects of the ubiquitous computing vision as described by Mark Weiser [60]. This survey is meant as a starting point for new projects, in order to choose an existing infrastructure for reuse, or to get an overview before designing a new one. It tries to provide a systematic, relatively broad (and necessarily not very deep overview, while pointing to relevant literature for in-depth study of the systems discussed.

  10. Complete distributed computing environment for a HEP experiment: experience with ARC-connected infrastructure for ATLAS

    International Nuclear Information System (INIS)

    Read, A; Taga, A; O-Saada, F; Pajchel, K; Samset, B H; Cameron, D

    2008-01-01

    Computing and storage resources connected by the Nordugrid ARC middleware in the Nordic countries, Switzerland and Slovenia are a part of the ATLAS computing Grid. This infrastructure is being commissioned with the ongoing ATLAS Monte Carlo simulation production in preparation for the commencement of data taking in 2008. The unique non-intrusive architecture of ARC, its straightforward interplay with the ATLAS Production System via the Dulcinea executor, and its performance during the commissioning exercise is described. ARC support for flexible and powerful end-user analysis within the GANGA distributed analysis framework is also shown. Whereas the storage solution for this Grid was earlier based on a large, distributed collection of GridFTP-servers, the ATLAS computing design includes a structured SRM-based system with a limited number of storage endpoints. The characteristics, integration and performance of the old and new storage solutions are presented. Although the hardware resources in this Grid are quite modest, it has provided more than double the agreed contribution to the ATLAS production with an efficiency above 95% during long periods of stable operation

  11. Complete distributed computing environment for a HEP experiment: experience with ARC-connected infrastructure for ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Read, A; Taga, A; O-Saada, F; Pajchel, K; Samset, B H; Cameron, D [Department of Physics, University of Oslo, P.b. 1048 Blindern, N-0316 Oslo (Norway)], E-mail: a.l.read@fys.uio.no

    2008-07-15

    Computing and storage resources connected by the Nordugrid ARC middleware in the Nordic countries, Switzerland and Slovenia are a part of the ATLAS computing Grid. This infrastructure is being commissioned with the ongoing ATLAS Monte Carlo simulation production in preparation for the commencement of data taking in 2008. The unique non-intrusive architecture of ARC, its straightforward interplay with the ATLAS Production System via the Dulcinea executor, and its performance during the commissioning exercise is described. ARC support for flexible and powerful end-user analysis within the GANGA distributed analysis framework is also shown. Whereas the storage solution for this Grid was earlier based on a large, distributed collection of GridFTP-servers, the ATLAS computing design includes a structured SRM-based system with a limited number of storage endpoints. The characteristics, integration and performance of the old and new storage solutions are presented. Although the hardware resources in this Grid are quite modest, it has provided more than double the agreed contribution to the ATLAS production with an efficiency above 95% during long periods of stable operation.

  12. Building Resilient Cloud Over Unreliable Commodity Infrastructure

    OpenAIRE

    Kedia, Piyus; Bansal, Sorav; Deshpande, Deepak; Iyer, Sreekanth

    2012-01-01

    Cloud Computing has emerged as a successful computing paradigm for efficiently utilizing managed compute infrastructure such as high speed rack-mounted servers, connected with high speed networking, and reliable storage. Usually such infrastructure is dedicated, physically secured and has reliable power and networking infrastructure. However, much of our idle compute capacity is present in unmanaged infrastructure like idle desktops, lab machines, physically distant server machines, and lapto...

  13. The Impacts of Port Infrastructure and Logistics Performance on Economic Growth

    DEFF Research Database (Denmark)

    Munim, Ziaul Haque; Schramm, Hans-Joachim

    2018-01-01

    Considering 91 countries with seaports, this study conducted an empirical inquiry into the broader economic contribution of seaborne trade, from a port infrastructure quality and logistics performance perspective. Investment in quality improvement of port infrastructure and its contribution to ec...

  14. High Performance Computing in Science and Engineering '08 : Transactions of the High Performance Computing Center

    CERN Document Server

    Kröner, Dietmar; Resch, Michael

    2009-01-01

    The discussions and plans on all scienti?c, advisory, and political levels to realize an even larger “European Supercomputer” in Germany, where the hardware costs alone will be hundreds of millions Euro – much more than in the past – are getting closer to realization. As part of the strategy, the three national supercomputing centres HLRS (Stuttgart), NIC/JSC (Julic ¨ h) and LRZ (Munich) have formed the Gauss Centre for Supercomputing (GCS) as a new virtual organization enabled by an agreement between the Federal Ministry of Education and Research (BMBF) and the state ministries for research of Baden-Wurttem ¨ berg, Bayern, and Nordrhein-Westfalen. Already today, the GCS provides the most powerful high-performance computing - frastructure in Europe. Through GCS, HLRS participates in the European project PRACE (Partnership for Advances Computing in Europe) and - tends its reach to all European member countries. These activities aligns well with the activities of HLRS in the European HPC infrastructur...

  15. a Holistic Approach for Inspection of Civil Infrastructures Based on Computer Vision Techniques

    Science.gov (United States)

    Stentoumis, C.; Protopapadakis, E.; Doulamis, A.; Doulamis, N.

    2016-06-01

    In this work, it is examined the 2D recognition and 3D modelling of concrete tunnel cracks, through visual cues. At the time being, the structural integrity inspection of large-scale infrastructures is mainly performed through visual observations by human inspectors, who identify structural defects, rate them and, then, categorize their severity. The described approach targets at minimum human intervention, for autonomous inspection of civil infrastructures. The shortfalls of existing approaches in crack assessment are being addressed by proposing a novel detection scheme. Although efforts have been made in the field, synergies among proposed techniques are still missing. The holistic approach of this paper exploits the state of the art techniques of pattern recognition and stereo-matching, in order to build accurate 3D crack models. The innovation lies in the hybrid approach for the CNN detector initialization, and the use of the modified census transformation for stereo matching along with a binary fusion of two state-of-the-art optimization schemes. The described approach manages to deal with images of harsh radiometry, along with severe radiometric differences in the stereo pair. The effectiveness of this workflow is evaluated on a real dataset gathered in highway and railway tunnels. What is promising is that the computer vision workflow described in this work can be transferred, with adaptations of course, to other infrastructure such as pipelines, bridges and large industrial facilities that are in the need of continuous state assessment during their operational life cycle.

  16. Signal and image processing algorithm performance in a virtual and elastic computing environment

    Science.gov (United States)

    Bennett, Kelly W.; Robertson, James

    2013-05-01

    The U.S. Army Research Laboratory (ARL) supports the development of classification, detection, tracking, and localization algorithms using multiple sensing modalities including acoustic, seismic, E-field, magnetic field, PIR, and visual and IR imaging. Multimodal sensors collect large amounts of data in support of algorithm development. The resulting large amount of data, and their associated high-performance computing needs, increases and challenges existing computing infrastructures. Purchasing computer power as a commodity using a Cloud service offers low-cost, pay-as-you-go pricing models, scalability, and elasticity that may provide solutions to develop and optimize algorithms without having to procure additional hardware and resources. This paper provides a detailed look at using a commercial cloud service provider, such as Amazon Web Services (AWS), to develop and deploy simple signal and image processing algorithms in a cloud and run the algorithms on a large set of data archived in the ARL Multimodal Signatures Database (MMSDB). Analytical results will provide performance comparisons with existing infrastructure. A discussion on using cloud computing with government data will discuss best security practices that exist within cloud services, such as AWS.

  17. A General Purpose High Performance Linux Installation Infrastructure

    International Nuclear Information System (INIS)

    Wachsmann, Alf

    2002-01-01

    With more and more and larger and larger Linux clusters, the question arises how to install them. This paper addresses this question by proposing a solution using only standard software components. This installation infrastructure scales well for a large number of nodes. It is also usable for installing desktop machines or diskless Linux clients, thus, is not designed for cluster installations in particular but is, nevertheless, highly performant. The infrastructure proposed uses PXE as the network boot component on the nodes. It uses DHCP and TFTP servers to get IP addresses and a bootloader to all nodes. It then uses kickstart to install Red Hat Linux over NFS. We have implemented this installation infrastructure at SLAC with our given server hardware and installed a 256 node cluster in 30 minutes. This paper presents the measurements from this installation and discusses the bottlenecks in our installation

  18. A Framework for Debugging Geoscience Projects in a High Performance Computing Environment

    Science.gov (United States)

    Baxter, C.; Matott, L.

    2012-12-01

    High performance computing (HPC) infrastructure has become ubiquitous in today's world with the emergence of commercial cloud computing and academic supercomputing centers. Teams of geoscientists, hydrologists and engineers can take advantage of this infrastructure to undertake large research projects - for example, linking one or more site-specific environmental models with soft computing algorithms, such as heuristic global search procedures, to perform parameter estimation and predictive uncertainty analysis, and/or design least-cost remediation systems. However, the size, complexity and distributed nature of these projects can make identifying failures in the associated numerical experiments using conventional ad-hoc approaches both time- consuming and ineffective. To address these problems a multi-tiered debugging framework has been developed. The framework allows for quickly isolating and remedying a number of potential experimental failures, including: failures in the HPC scheduler; bugs in the soft computing code; bugs in the modeling code; and permissions and access control errors. The utility of the framework is demonstrated via application to a series of over 200,000 numerical experiments involving a suite of 5 heuristic global search algorithms and 15 mathematical test functions serving as cheap analogues for the simulation-based optimization of pump-and-treat subsurface remediation systems.

  19. Data Intensive Scientific Computing on Petabyte Scalable Infrastructure, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The infrastructure and programming paradigm for petabyte-level data processing performed at companies like Google and Yahoo shed some promising lights on the...

  20. A cyber infrastructure for the SKA Telescope Manager

    Science.gov (United States)

    Barbosa, Domingos; Barraca, João. P.; Carvalho, Bruno; Maia, Dalmiro; Gupta, Yashwant; Natarajan, Swaminathan; Le Roux, Gerhard; Swart, Paul

    2016-07-01

    The Square Kilometre Array Telescope Manager (SKA TM) will be responsible for assisting the SKA Operations and Observation Management, carrying out System diagnosis and collecting Monitoring and Control data from the SKA subsystems and components. To provide adequate compute resources, scalability, operation continuity and high availability, as well as strict Quality of Service, the TM cyber-infrastructure (embodied in the Local Infrastructure - LINFRA) consists of COTS hardware and infrastructural software (for example: server monitoring software, host operating system, virtualization software, device firmware), providing a specially tailored Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) solution. The TM infrastructure provides services in the form of computational power, software defined networking, power, storage abstractions, and high level, state of the art IaaS and PaaS management interfaces. This cyber platform will be tailored to each of the two SKA Phase 1 telescopes (SKA_MID in South Africa and SKA_LOW in Australia) instances, each presenting different computational and storage infrastructures and conditioned by location. This cyber platform will provide a compute model enabling TM to manage the deployment and execution of its multiple components (observation scheduler, proposal submission tools, MandC components, Forensic tools and several Databases, etc). In this sense, the TM LINFRA is primarily focused towards the provision of isolated instances, mostly resorting to virtualization technologies, while defaulting to bare hardware if specifically required due to performance, security, availability, or other requirement.

  1. The Impact of Airport Performance towards Construction and Infrastructure Expansion in Indonesia

    Science.gov (United States)

    Laksono, T. D.; Kurniasih, N.; Hasyim, C.; Setiawan, M. I.; Ahmar, A. S.

    2018-01-01

    Development that is generated from airport areas includes construction and infrastructure development. This research reviews about how the implementation of material management in certain construction project and the relationship between development especially construction and infrastructure development with Airport Performance. The method that is used in this research is mixed method. The population in this research is 297 airports that are existed in Indonesia. From those 297 airports then it is chosen airports that have the most completed data about construction project and it is obtained 148 airports. Based on the coefficient correlation (R) test it is known that construction and infrastructure development has relatively strong relation with airport performance variable, but there are still other factors that influence construction and infrastructure development become bigger effect.

  2. A performance analysis of EC2 cloud computing services for scientific computing

    NARCIS (Netherlands)

    Ostermann, S.; Iosup, A.; Yigitbasi, M.N.; Prodan, R.; Fahringer, T.; Epema, D.H.J.; Avresky, D.; Diaz, M.; Bode, A.; Bruno, C.; Dekel, E.

    2010-01-01

    Cloud Computing is emerging today as a commercial infrastructure that eliminates the need for maintaining expensive computing hardware. Through the use of virtualization, clouds promise to address with the same shared set of physical resources a large user base with different needs. Thus, clouds

  3. Cloud Computing in Support of Applied Learning: A Baseline Study of Infrastructure Design at Southern Polytechnic State University

    Science.gov (United States)

    Conn, Samuel S.; Reichgelt, Han

    2013-01-01

    Cloud computing represents an architecture and paradigm of computing designed to deliver infrastructure, platforms, and software as constructible computing resources on demand to networked users. As campuses are challenged to better accommodate academic needs for applications and computing environments, cloud computing can provide an accommodating…

  4. Business Models of High Performance Computing Centres in Higher Education in Europe

    Science.gov (United States)

    Eurich, Markus; Calleja, Paul; Boutellier, Roman

    2013-01-01

    High performance computing (HPC) service centres are a vital part of the academic infrastructure of higher education organisations. However, despite their importance for research and the necessary high capital expenditures, business research on HPC service centres is mostly missing. From a business perspective, it is important to find an answer to…

  5. A Grid-Based Cyber Infrastructure for High Performance Chemical Dynamics Simulations

    Directory of Open Access Journals (Sweden)

    Khadka Prashant

    2008-10-01

    Full Text Available Chemical dynamics simulation is an effective means to study atomic level motions of molecules, collections of molecules, liquids, surfaces, interfaces of materials, and chemical reactions. To make chemical dynamics simulations globally accessible to a broad range of users, recently a cyber infrastructure was developed that provides an online portal to VENUS, a popular chemical dynamics simulation program package, to allow people to submit simulation jobs that will be executed on the web server machine. In this paper, we report new developments of the cyber infrastructure for the improvement of its quality of service by dispatching the submitted simulations jobs from the web server machine onto a cluster of workstations for execution, and by adding an animation tool, which is optimized for animating the simulation results. The separation of the server machine from the simulation-running machine improves the service quality by increasing the capacity to serve more requests simultaneously with even reduced web response time, and allows the execution of large scale, time-consuming simulation jobs on the powerful workstation cluster. With the addition of an animation tool, the cyber infrastructure automatically converts, upon the selection of the user, some simulation results into an animation file that can be viewed on usual web browsers without requiring installation of any special software on the user computer. Since animation is essential for understanding the results of chemical dynamics simulations, this animation capacity provides a better way for understanding simulation details of the chemical dynamics. By combining computing resources at locations under different administrative controls, this cyber infrastructure constitutes a grid environment providing physically and administratively distributed functionalities through a single easy-to-use online portal

  6. Dynamic Collaboration Infrastructure for Hydrologic Science

    Science.gov (United States)

    Tarboton, D. G.; Idaszak, R.; Castillo, C.; Yi, H.; Jiang, F.; Jones, N.; Goodall, J. L.

    2016-12-01

    Data and modeling infrastructure is becoming increasingly accessible to water scientists. HydroShare is a collaborative environment that currently offers water scientists the ability to access modeling and data infrastructure in support of data intensive modeling and analysis. It supports the sharing of and collaboration around "resources" which are social objects defined to include both data and models in a structured standardized format. Users collaborate around these objects via comments, ratings, and groups. HydroShare also supports web services and cloud based computation for the execution of hydrologic models and analysis and visualization of hydrologic data. However, the quantity and variety of data and modeling infrastructure available that can be accessed from environments like HydroShare is increasing. Storage infrastructure can range from one's local PC to campus or organizational storage to storage in the cloud. Modeling or computing infrastructure can range from one's desktop to departmental clusters to national HPC resources to grid and cloud computing resources. How does one orchestrate this vast number of data and computing infrastructure without needing to correspondingly learn each new system? A common limitation across these systems is the lack of efficient integration between data transport mechanisms and the corresponding high-level services to support large distributed data and compute operations. A scientist running a hydrology model from their desktop may require processing a large collection of files across the aforementioned storage and compute resources and various national databases. To address these community challenges a proof-of-concept prototype was created integrating HydroShare with RADII (Resource Aware Data-centric collaboration Infrastructure) to provide software infrastructure to enable the comprehensive and rapid dynamic deployment of what we refer to as "collaborative infrastructure." In this presentation we discuss the

  7. A simple grid implementation with Berkeley Open Infrastructure for Network Computing using BLAST as a model

    Directory of Open Access Journals (Sweden)

    Watthanai Pinthong

    2016-07-01

    Full Text Available Development of high-throughput technologies, such as Next-generation sequencing, allows thousands of experiments to be performed simultaneously while reducing resource requirement. Consequently, a massive amount of experiment data is now rapidly generated. Nevertheless, the data are not readily usable or meaningful until they are further analysed and interpreted. Due to the size of the data, a high performance computer (HPC is required for the analysis and interpretation. However, the HPC is expensive and difficult to access. Other means were developed to allow researchers to acquire the power of HPC without a need to purchase and maintain one such as cloud computing services and grid computing system. In this study, we implemented grid computing in a computer training center environment using Berkeley Open Infrastructure for Network Computing (BOINC as a job distributor and data manager combining all desktop computers to virtualize the HPC. Fifty desktop computers were used for setting up a grid system during the off-hours. In order to test the performance of the grid system, we adapted the Basic Local Alignment Search Tools (BLAST to the BOINC system. Sequencing results from Illumina platform were aligned to the human genome database by BLAST on the grid system. The result and processing time were compared to those from a single desktop computer and HPC. The estimated durations of BLAST analysis for 4 million sequence reads on a desktop PC, HPC and the grid system were 568, 24 and 5 days, respectively. Thus, the grid implementation of BLAST by BOINC is an efficient alternative to the HPC for sequence alignment. The grid implementation by BOINC also helped tap unused computing resources during the off-hours and could be easily modified for other available bioinformatics software.

  8. A HOLISTIC APPROACH FOR INSPECTION OF CIVIL INFRASTRUCTURES BASED ON COMPUTER VISION TECHNIQUES

    Directory of Open Access Journals (Sweden)

    C. Stentoumis

    2016-06-01

    Full Text Available In this work, it is examined the 2D recognition and 3D modelling of concrete tunnel cracks, through visual cues. At the time being, the structural integrity inspection of large-scale infrastructures is mainly performed through visual observations by human inspectors, who identify structural defects, rate them and, then, categorize their severity. The described approach targets at minimum human intervention, for autonomous inspection of civil infrastructures. The shortfalls of existing approaches in crack assessment are being addressed by proposing a novel detection scheme. Although efforts have been made in the field, synergies among proposed techniques are still missing. The holistic approach of this paper exploits the state of the art techniques of pattern recognition and stereo-matching, in order to build accurate 3D crack models. The innovation lies in the hybrid approach for the CNN detector initialization, and the use of the modified census transformation for stereo matching along with a binary fusion of two state-of-the-art optimization schemes. The described approach manages to deal with images of harsh radiometry, along with severe radiometric differences in the stereo pair. The effectiveness of this workflow is evaluated on a real dataset gathered in highway and railway tunnels. What is promising is that the computer vision workflow described in this work can be transferred, with adaptations of course, to other infrastructure such as pipelines, bridges and large industrial facilities that are in the need of continuous state assessment during their operational life cycle.

  9. Access control infrastructure for on-demand provisioned virtualised infrastructure services

    NARCIS (Netherlands)

    Demchenko, Y.; Ngo, C.; de Laat, C.; Smari, W.W.; Fox, G.C.

    2011-01-01

    Cloud technologies are emerging as a new way of provisioning virtualised computing and infrastructure services on-demand for collaborative projects and groups. Security in provisioning virtual infrastructure services should address two general aspects: supporting secure operation of the provisioning

  10. BONFIRE: benchmarking computers and computer networks

    OpenAIRE

    Bouckaert, Stefan; Vanhie-Van Gerwen, Jono; Moerman, Ingrid; Phillips, Stephen; Wilander, Jerker

    2011-01-01

    The benchmarking concept is not new in the field of computing or computer networking. With “benchmarking tools”, one usually refers to a program or set of programs, used to evaluate the performance of a solution under certain reference conditions, relative to the performance of another solution. Since the 1970s, benchmarking techniques have been used to measure the performance of computers and computer networks. Benchmarking of applications and virtual machines in an Infrastructure-as-a-Servi...

  11. 8th International Workshop on Parallel Tools for High Performance Computing

    CERN Document Server

    Gracia, José; Knüpfer, Andreas; Resch, Michael; Nagel, Wolfgang

    2015-01-01

    Numerical simulation and modelling using High Performance Computing has evolved into an established technique in academic and industrial research. At the same time, the High Performance Computing infrastructure is becoming ever more complex. For instance, most of the current top systems around the world use thousands of nodes in which classical CPUs are combined with accelerator cards in order to enhance their compute power and energy efficiency. This complexity can only be mastered with adequate development and optimization tools. Key topics addressed by these tools include parallelization on heterogeneous systems, performance optimization for CPUs and accelerators, debugging of increasingly complex scientific applications, and optimization of energy usage in the spirit of green IT. This book represents the proceedings of the 8th International Parallel Tools Workshop, held October 1-2, 2014 in Stuttgart, Germany – which is a forum to discuss the latest advancements in the parallel tools.

  12. Towards sustainability: An interoperability outline for a Regional ARC based infrastructure in the WLCG and EGEE infrastructures

    International Nuclear Information System (INIS)

    Field, L; Gronager, M; Johansson, D; Kleist, J

    2010-01-01

    Interoperability of grid infrastructures is becoming increasingly important in the emergence of large scale grid infrastructures based on national and regional initiatives. To achieve interoperability of grid infrastructures adaptions and bridging of many different systems and services needs to be tackled. A grid infrastructure offers services for authentication, authorization, accounting, monitoring, operation besides from the services for handling and data and computations. This paper presents an outline of the work done to integrate the Nordic Tier-1 and 2s, which for the compute part is based on the ARC middleware, into the WLCG grid infrastructure co-operated by the EGEE project. Especially, a throughout description of integration of the compute services is presented.

  13. The Multi-modal Australian ScienceS Imaging and Visualisation Environment (MASSIVE high performance computing infrastructure: applications in neuroscience and neuroinformatics research

    Directory of Open Access Journals (Sweden)

    Wojtek James eGoscinski

    2014-03-01

    Full Text Available The Multi-modal Australian ScienceS Imaging and Visualisation Environment (MASSIVE is a national imaging and visualisation facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organisation (CSIRO, and the Victorian Partnership for Advanced Computing (VPAC, with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI, x-ray computer tomography (CT, electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i integrated multiple different neuroimaging analysis software components, (ii enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research.

  14. Building a Community Infrastructure for Scalable On-Line Performance Analysis Tools around Open|SpeedShop

    Energy Technology Data Exchange (ETDEWEB)

    Galarowicz, James E. [Krell Institute, Ames, IA (United States); Miller, Barton P. [Univ. of Wisconsin, Madison, WI (United States). Computer Sciences Dept.; Hollingsworth, Jeffrey K. [Univ. of Maryland, College Park, MD (United States). Computer Sciences Dept.; Roth, Philip [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Future Technologies Group, Computer Science and Math Division; Schulz, Martin [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Applied Scientific Computing (CASC)

    2013-12-19

    In this project we created a community tool infrastructure for program development tools targeting Petascale class machines and beyond. This includes tools for performance analysis, debugging, and correctness tools, as well as tuning and optimization frameworks. The developed infrastructure provides a comprehensive and extensible set of individual tool building components. We started with the basic elements necessary across all tools in such an infrastructure followed by a set of generic core modules that allow a comprehensive performance analysis at scale. Further, we developed a methodology and workflow that allows others to add or replace modules, to integrate parts into their own tools, or to customize existing solutions. In order to form the core modules, we built on the existing Open|SpeedShop infrastructure and decomposed it into individual modules that match the necessary tool components. At the same time, we addressed the challenges found in performance tools for petascale systems in each module. When assembled, this instantiation of community tool infrastructure provides an enhanced version of Open|SpeedShop, which, while completely different in its architecture, provides scalable performance analysis for petascale applications through a familiar interface. This project also built upon and enhances capabilities and reusability of project partner components as specified in the original project proposal. The overall project team’s work over the project funding cycle was focused on several areas of research, which are described in the following sections. The reminder of this report also highlights related work as well as preliminary work that supported the project. In addition to the project partners funded by the Office of Science under this grant, the project team included several collaborators who contribute to the overall design of the envisioned tool infrastructure. In particular, the project team worked closely with the other two DOE NNSA

  15. Resilient and Robust High Performance Computing Platforms for Scientific Computing Integrity

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Yier [Univ. of Central Florida, Orlando, FL (United States)

    2017-07-14

    As technology advances, computer systems are subject to increasingly sophisticated cyber-attacks that compromise both their security and integrity. High performance computing platforms used in commercial and scientific applications involving sensitive, or even classified data, are frequently targeted by powerful adversaries. This situation is made worse by a lack of fundamental security solutions that both perform efficiently and are effective at preventing threats. Current security solutions fail to address the threat landscape and ensure the integrity of sensitive data. As challenges rise, both private and public sectors will require robust technologies to protect its computing infrastructure. The research outcomes from this project try to address all these challenges. For example, we present LAZARUS, a novel technique to harden kernel Address Space Layout Randomization (KASLR) against paging-based side-channel attacks. In particular, our scheme allows for fine-grained protection of the virtual memory mappings that implement the randomization. We demonstrate the effectiveness of our approach by hardening a recent Linux kernel with LAZARUS, mitigating all of the previously presented side-channel attacks on KASLR. Our extensive evaluation shows that LAZARUS incurs only 0.943% overhead for standard benchmarks, and is therefore highly practical. We also introduced HA2lloc, a hardware-assisted allocator that is capable of leveraging an extended memory management unit to detect memory errors in the heap. We also perform testing using HA2lloc in a simulation environment and find that the approach is capable of preventing common memory vulnerabilities.

  16. Performance Measurements in a High Throughput Computing Environment

    CERN Document Server

    AUTHOR|(CDS)2145966; Gribaudo, Marco

    The IT infrastructures of companies and research centres are implementing new technologies to satisfy the increasing need of computing resources for big data analysis. In this context, resource profiling plays a crucial role in identifying areas where the improvement of the utilisation efficiency is needed. In order to deal with the profiling and optimisation of computing resources, two complementary approaches can be adopted: the measurement-based approach and the model-based approach. The measurement-based approach gathers and analyses performance metrics executing benchmark applications on computing resources. Instead, the model-based approach implies the design and implementation of a model as an abstraction of the real system, selecting only those aspects relevant to the study. This Thesis originates from a project carried out by the author within the CERN IT department. CERN is an international scientific laboratory that conducts fundamental researches in the domain of elementary particle physics. The p...

  17. Performance Risks Allocation in Bot Infrastructure in Nigeria: A Case Study of Lagos Infrastructure Project

    Directory of Open Access Journals (Sweden)

    Sanni Gabriel A.

    2017-08-01

    Full Text Available The study assessed allocation, criteria and allotment effectiveness of performance risks in Build- Operate-Transfer (BOT transportation infrastructure in Nigeria using Lagos Infrastructure Project (LIP as a case study. LIP is the only BOT-procured tolled road that has attained ‘operate’ stage of BOT cycle in Nigeria. It revealed that more operating risks were actually allocated to the concessionaire than the grantor and most of the risks were preferred retained by the allottee. Significant fraction of the risks was effectively allocated between the concessionaire and grantor except those that involve close interface between participants. While grantor rated nine risks high and seven risks very high; the concessionaire assessed nine risks to be high and five risks to be very high; the grantor rated the effectiveness level to be seventy three per cent and the concessionaire assessed it to be sixty four per cent. The study recommended that the evolving knowledge from Lagos Infrastructure Project (LIP should be documented to guide future BOT transactions in Nigeria.

  18. Defense of Cyber Infrastructures Against Cyber-Physical Attacks Using Game-Theoretic Models.

    Science.gov (United States)

    Rao, Nageswara S V; Poole, Stephen W; Ma, Chris Y T; He, Fei; Zhuang, Jun; Yau, David K Y

    2016-04-01

    The operation of cyber infrastructures relies on both cyber and physical components, which are subject to incidental and intentional degradations of different kinds. Within the context of network and computing infrastructures, we study the strategic interactions between an attacker and a defender using game-theoretic models that take into account both cyber and physical components. The attacker and defender optimize their individual utilities, expressed as sums of cost and system terms. First, we consider a Boolean attack-defense model, wherein the cyber and physical subinfrastructures may be attacked and reinforced as individual units. Second, we consider a component attack-defense model wherein their components may be attacked and defended, and the infrastructure requires minimum numbers of both to function. We show that the Nash equilibrium under uniform costs in both cases is computable in polynomial time, and it provides high-level deterministic conditions for the infrastructure survival. When probabilities of successful attack and defense, and of incidental failures, are incorporated into the models, the results favor the attacker but otherwise remain qualitatively similar. This approach has been motivated and validated by our experiences with UltraScience Net infrastructure, which was built to support high-performance network experiments. The analytical results, however, are more general, and we apply them to simplified models of cloud and high-performance computing infrastructures. © 2015 Society for Risk Analysis.

  19. Probability Distributome: A Web Computational Infrastructure for Exploring the Properties, Interrelations, and Applications of Probability Distributions.

    Science.gov (United States)

    Dinov, Ivo D; Siegrist, Kyle; Pearl, Dennis K; Kalinin, Alexandr; Christou, Nicolas

    2016-06-01

    Probability distributions are useful for modeling, simulation, analysis, and inference on varieties of natural processes and physical phenomena. There are uncountably many probability distributions. However, a few dozen families of distributions are commonly defined and are frequently used in practice for problem solving, experimental applications, and theoretical studies. In this paper, we present a new computational and graphical infrastructure, the Distributome , which facilitates the discovery, exploration and application of diverse spectra of probability distributions. The extensible Distributome infrastructure provides interfaces for (human and machine) traversal, search, and navigation of all common probability distributions. It also enables distribution modeling, applications, investigation of inter-distribution relations, as well as their analytical representations and computational utilization. The entire Distributome framework is designed and implemented as an open-source, community-built, and Internet-accessible infrastructure. It is portable, extensible and compatible with HTML5 and Web2.0 standards (http://Distributome.org). We demonstrate two types of applications of the probability Distributome resources: computational research and science education. The Distributome tools may be employed to address five complementary computational modeling applications (simulation, data-analysis and inference, model-fitting, examination of the analytical, mathematical and computational properties of specific probability distributions, and exploration of the inter-distributional relations). Many high school and college science, technology, engineering and mathematics (STEM) courses may be enriched by the use of modern pedagogical approaches and technology-enhanced methods. The Distributome resources provide enhancements for blended STEM education by improving student motivation, augmenting the classical curriculum with interactive webapps, and overhauling the

  20. Telecommunications, power supply, computer systems: the infrastructures of the soccer world cup; Telecommunications, electricite, informatique: les infrastructures de la Coupe du Monde

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    1998-06-01

    The 1998 edition of the soccer world cup took place in ten different stadiums in France and several related sites. This short paper gives a general overview of the infrastructures developed for this occasion in the domains of telecommunications, power supply (substations, protection systems, computerized control systems..), and computer systems. (J.S.)

  1. Procuring complex performance:case: public infrastructure projects

    OpenAIRE

    Leppänen, T. (Tero)

    2015-01-01

    Abstract This research studies procuring complex performance (PCP) in the case of public infrastructure projects. Focus of the research is on the interface between public clients and private sector contractors. Purpose of this research is to find out what are the main challenges of different project delivery methods according to literature (RQ1) and what are the practical challenges of public procurement (RQ2). As an end re...

  2. The impact of Knowledge Management Infrastructure on Performance Effectiveness in Jordanian Organizations

    Directory of Open Access Journals (Sweden)

    Nasser Mohammad Soud Jaradat, Dr.

    2014-06-01

    Full Text Available This study aims to determine the impact of knowledge management infrastructure on the performance effectiveness of the Jordanian organizations that need knowledge to perform their work and tasks. The study sample includes some public and private organizations working in Jordan and dealing with the knowledge subjects. The findings indicated that there was a strong effect for knowledge management infrastructure on the performance effectiveness. Organizations should establish knowledge directorates to discover and transmit knowledge to workers with a view to improve the creativeness and distinctiveness of organizations.

  3. Post Construction Green Infrastructure Performance Monitoring Parameters and Their Functional Components

    Directory of Open Access Journals (Sweden)

    Thewodros K. Geberemariam

    2016-12-01

    Full Text Available Drainage system infrastructures in most urbanized cities have reached or exceeded their design life cycle and are characterized by running with inadequate capacity. These highly degraded infrastructures are already overwhelmed and continued to impose a significant challenge to the quality of water and ecological systems. With predicted urban growth and climate change the situation is only going to get worse. As a result, municipalities are increasingly considering the concept of retrofitting existing stormwater drainage systems with green infrastructure practices as the first and an important step to reduce stormwater runoff volume and pollutant load inputs into combined sewer systems (CSO and wastewater facilities. Green infrastructure practices include an open green space that can absorb stormwater runoff, ranging from small-scale naturally existing pocket of lands, right-of-way bioswales, and trees planted along the sidewalk as well as large-scale public parks. Despite the growing municipalities’ interest to retrofit existing stormwater drainage systems with green infrastructure, few studies and relevant information are available on their performance and cost-effectiveness. Therefore, this paper aims to help professionals learn about and become familiar with green infrastructure, decrease implementation barriers, and provide guidance for monitoring green infrastructure using the combination of survey questionnaires, meta-narrative and systematic literature review techniques.

  4. The ATLAS Simulation Infrastructure

    CERN Document Server

    Aad, G.; Abdallah, J.; Abdelalim, A.A.; Abdesselam, A.; Abdinov, O.; Abi, B.; Abolins, M.; Abramowicz, H.; Abreu, H.; Acharya, B.S.; Adams, D.L.; Addy, T.N.; Adelman, J.; Adorisio, C.; Adragna, P.; Adye, T.; Aefsky, S.; Aguilar-Saavedra, J.A.; Aharrouche, M.; Ahlen, S.P.; Ahles, F.; Ahmad, A.; Ahmed, H.; Ahsan, M.; Aielli, G.; Akdogan, T.; Akesson, T.P.A.; Akimoto, G.; Akimov, A.V.; Aktas, A.; Alam, M.S.; Alam, M.A.; Albrand, S.; Aleksa, M.; Aleksandrov, I.N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Aliyev, M.; Allport, P.P.; Allwood-Spiers, S.E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alviggi, M.G.; Amako, K.; Amelung, C.; Amorim, A.; Amoros, G.; Amram, N.; Anastopoulos, C.; Andeen, T.; Anders, C.F.; Anderson, K.J.; Andreazza, A.; Andrei, V.; Anduaga, X.S.; Angerami, A.; Anghinolfi, F.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonelli, S.; Antos, J.; Antunovic, B.; Anulli, F.; Aoun, S.; Arabidze, G.; Aracena, I.; Arai, Y.; Arce, A.T.H.; Archambault, J.P.; Arfaoui, S.; Arguin, J-F.; Argyropoulos, T.; Arik, M.; Armbruster, A.J.; Arnaez, O.; Arnault, C.; Artamonov, A.; Arutinov, D.; Asai, M.; Asai, S.; Asfandiyarov, R.; Ask, S.; Asman, B.; Asner, D.; Asquith, L.; Assamagan, K.; Astbury, A.; Astvatsatourov, A.; Atoian, G.; Auerbach, B.; Augsten, K.; Aurousseau, M.; Austin, N.; Avolio, G.; Avramidou, R.; Axen, D.; Ay, C.; Azuelos, G.; Azuma, Y.; Baak, M.A.; Bach, A.M.; Bachacou, H.; Bachas, K.; Backes, M.; Badescu, E.; Bagnaia, P.; Bai, Y.; Bain, T.; Baines, J.T.; Baker, O.K.; Baker, M.D.; Baker, S; Baltasar Dos Santos Pedrosa, F.; Banas, E.; Banerjee, P.; Banerjee, S.; Banfi, D.; Bangert, A.; Bansal, V.; Baranov, S.P.; Baranov, S.; Barashkou, A.; Barber, T.; Barberio, E.L.; Barberis, D.; Barbero, M.; Bardin, D.Y.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B.M.; Barnett, R.M.; Baroncelli, A.; Barr, A.J.; Barreiro, F.; Barreiro Guimaraes da Costa, J.; Barrillon, P.; Bartoldus, R.; Bartsch, D.; Bates, R.L.; Batkova, L.; Batley, J.R.; Battaglia, A.; Battistin, M.; Bauer, F.; Bawa, H.S.; Bazalova, M.; Beare, B.; Beau, T.; Beauchemin, P.H.; Beccherle, R.; Becerici, N.; Bechtle, P.; Beck, G.A.; Beck, H.P.; Beckingham, M.; Becks, K.H.; Beddall, A.J.; Beddall, A.; Bednyakov, V.A.; Bee, C.; Begel, M.; Behar Harpaz, S.; Behera, P.K.; Beimforde, M.; Belanger-Champagne, C.; Bell, P.J.; Bell, W.H.; Bella, G.; Bellagamba, L.; Bellina, F.; Bellomo, M.; Belloni, A.; Belotskiy, K.; Beltramello, O.; Ben Ami, S.; Benary, O.; Benchekroun, D.; Bendel, M.; Benedict, B.H.; Benekos, N.; Benhammou, Y.; Benincasa, G.P.; Benjamin, D.P.; Benoit, M.; Bensinger, J.R.; Benslama, K.; Bentvelsen, S.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernat, P.; Bernhard, R.; Bernius, C.; Berry, T.; Bertin, A.; Besana, M.I.; Besson, N.; Bethke, S.; Bianchi, R.M.; Bianco, M.; Biebel, O.; Biesiada, J.; Biglietti, M.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biscarat, C.; Bitenc, U.; Black, K.M.; Blair, R.E.; Blanchard, J-B; Blanchot, G.; Blocker, C.; Blondel, A.; Blum, W.; Blumenschein, U.; Bobbink, G.J.; Bocci, A.; Boehler, M.; Boek, J.; Boelaert, N.; Boser, S.; Bogaerts, J.A.; Bogouch, A.; Bohm, C.; Bohm, J.; Boisvert, V.; Bold, T.; Boldea, V.; Bondarenko, V.G.; Bondioli, M.; Boonekamp, M.; Bordoni, S.; Borer, C.; Borisov, A.; Borissov, G.; Borjanovic, I.; Borroni, S.; Bos, K.; Boscherini, D.; Bosman, M.; Boterenbrood, H.; Bouchami, J.; Boudreau, J.; Bouhova-Thacker, E.V.; Boulahouache, C.; Bourdarios, C.; Boveia, A.; Boyd, J.; Boyko, I.R.; Bozovic-Jelisavcic, I.; Bracinik, J.; Braem, A.; Branchini, P.; Brandenburg, G.W.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J.E.; Braun, H.M.; Brelier, B.; Bremer, J.; Brenner, R.; Bressler, S.; Britton, D.; Brochu, F.M.; Brock, I.; Brock, R.; Brodet, E.; Bromberg, C.; Brooijmans, G.; Brooks, W.K.; Brown, G.; Bruckman de Renstrom, P.A.; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Bucci, F.; Buchanan, J.; Buchholz, P.; Buckley, A.G.; Budagov, I.A.; Budick, B.; Buscher, V.; Bugge, L.; Bulekov, O.; Bunse, M.; Buran, T.; Burckhart, H.; Burdin, S.; Burgess, T.; Burke, S.; Busato, E.; Bussey, P.; Buszello, C.P.; Butin, F.; Butler, B.; Butler, J.M.; Buttar, C.M.; Butterworth, J.M.; Byatt, T.; Caballero, J.; Cabrera Urban, S.; Caforio, D.; Cakir, O.; Calafiura, P.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L.P.; Calvet, D.; Camarri, P.; Cameron, D.; Campana, S.; Campanelli, M.; Canale, V.; Canelli, F.; Canepa, A.; Cantero, J.; Capasso, L.; Capeans Garrido, M.D.M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Caramarcu, C.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, B.; Caron, S.; Carrillo Montoya, G.D.; Carron Montero, S.; Carter, A.A.; Carter, J.R.; Carvalho, J.; Casadei, D.; Casado, M.P.; Cascella, M.; Castaneda Hernandez, A.M.; Castaneda-Miranda, E.; Castillo Gimenez, V.; Castro, N.F.; Cataldi, G.; Catinaccio, A.; Catmore, J.R.; Cattai, A.; Cattani, G.; Caughron, S.; Cauz, D.; Cavalleri, P.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerqueira, A.S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cetin, S.A.; Chafaq, A.; Chakraborty, D.; Chan, K.; Chapman, J.D.; Chapman, J.W.; Chareyre, E.; Charlton, D.G.; Chavda, V.; Cheatham, S.; Chekanov, S.; Chekulaev, S.V.; Chelkov, G.A.; Chen, H.; Chen, S.; Chen, X.; Cheplakov, A.; Chepurnov, V.F.; Cherkaoui El Moursli, R.; Tcherniatine, V.; Chesneanu, D.; Cheu, E.; Cheung, S.L.; Chevalier, L.; Chevallier, F.; Chiarella, V.; Chiefari, G.; Chikovani, L.; Childers, J.T.; Chilingarov, A.; Chiodini, G.; Chizhov, V.; Choudalakis, G.; Chouridou, S.; Christidi, I.A.; Christov, A.; Chromek-Burckhart, D.; Chu, M.L.; Chudoba, J.; Ciapetti, G.; Ciftci, A.K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciobotaru, M.D.; Ciocca, C.; Ciocio, A.; Cirilli, M.; Citterio, M.; Clark, A.; Clark, P.J.; Cleland, W.; Clemens, J.C.; Clement, B.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coggeshall, J.; Cogneras, E.; Colijn, A.P.; Collard, C.; Collins, N.J.; Collins-Tooth, C.; Collot, J.; Colon, G.; Conde Muino, P.; Coniavitis, E.; Consonni, M.; Constantinescu, S.; Conta, C.; Conventi, F.; Cooke, M.; Cooper, B.D.; Cooper-Sarkar, A.M.; Cooper-Smith, N.J.; Copic, K.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M.J.; Costanzo, D.; Costin, T.; Cote, D.; Coura Torres, R.; Courneyea, L.; Cowan, G.; Cowden, C.; Cox, B.E.; Cranmer, K.; Cranshaw, J.; Cristinziani, M.; Crosetti, G.; Crupi, R.; Crepe-Renaudin, S.; Cuenca Almenar, C.; Cuhadar Donszelmann, T.; Curatolo, M.; Curtis, C.J.; Cwetanski, P.; Czyczula, Z.; D'Auria, S.; D'Onofrio, M.; D'Orazio, A.; Da Via, C; Dabrowski, W.; Dai, T.; Dallapiccola, C.; Dallison, S.J.; Daly, C.H.; Dam, M.; Danielsson, H.O.; Dannheim, D.; Dao, V.; Darbo, G.; Darlea, G.L.; Davey, W.; Davidek, T.; Davidson, N.; Davidson, R.; Davies, M.; Davison, A.R.; Dawson, I.; Daya, R.K.; De, K.; de Asmundis, R.; De Castro, S.; De Castro Faria Salgado, P.E.; De Cecco, S.; de Graat, J.; De Groot, N.; de Jong, P.; De Mora, L.; De Oliveira Branco, M.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J.B.; De Zorzi, G.; Dean, S.; Dedovich, D.V.; Degenhardt, J.; Dehchar, M.; Del Papa, C.; Del Peso, J.; Del Prete, T.; Dell'Acqua, A.; Dell'Asta, L.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delsart, P.A.; Deluca, C.; Demers, S.; Demichev, M.; Demirkoz, B.; Deng, J.; Deng, W.; Denisov, S.P.; Derkaoui, J.E.; Derue, F.; Dervan, P.; Desch, K.; Deviveiros, P.O.; Dewhurst, A.; DeWilde, B.; Dhaliwal, S.; Dhullipudi, R.; Di Ciaccio, A.; Di Ciaccio, L.; Di Domenico, A.; Di Girolamo, A.; Di Girolamo, B.; Di Luise, S.; Di Mattia, A.; Di Nardo, R.; Di Simone, A.; Di Sipio, R.; Diaz, M.A.; Diblen, F.; Diehl, E.B.; Dietrich, J.; Dietzsch, T.A.; Diglio, S.; Dindar Yagci, K.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djilkibaev, R.; Djobava, T.; do Vale, M.A.B.; Do Valle Wemans, A.; Doan, T.K.O.; Dobos, D.; Dobson, E.; Dobson, M.; Doglioni, C.; Doherty, T.; Dolejsi, J.; Dolenc, I.; Dolezal, Z.; Dolgoshein, B.A.; Dohmae, T.; Donega, M.; Donini, J.; Dopke, J.; Doria, A.; Dos Anjos, A.; Dotti, A.; Dova, M.T.; Doxiadis, A.; Doyle, A.T.; Drasal, Z.; Dris, M.; Dubbert, J.; Duchovni, E.; Duckeck, G.; Dudarev, A.; Dudziak, F.; Duhrssen, M.; Duflot, L.; Dufour, M-A.; Dunford, M.; Duran Yildiz, H.; Dushkin, A.; Duxfield, R.; Dwuznik, M.; Duren, M.; Ebenstein, W.L.; Ebke, J.; Eckweiler, S.; Edmonds, K.; Edwards, C.A.; Egorov, K.; Ehrenfeld, W.; Ehrich, T.; Eifert, T.; Eigen, G.; Einsweiler, K.; Eisenhandler, E.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, K.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Engelmann, R.; Engl, A.; Epp, B.; Eppig, A.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ermoline, I.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Escobar, C.; Espinal Curull, X.; Esposito, B.; Etienvre, A.I.; Etzion, E.; Evans, H.; Fabbri, L.; Fabre, C.; Facius, K.; Fakhrutdinov, R.M.; Falciano, S.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farley, J.; Farooque, T.; Farrington, S.M.; Farthouat, P.; Fassnacht, P.; Fassouliotis, D.; Fatholahzadeh, B.; Fayard, L.; Fayette, F.; Febbraro, R.; Federic, P.; Fedin, O.L.; Fedorko, W.; Feligioni, L.; Felzmann, C.U.; Feng, C.; Feng, E.J.; Fenyuk, A.B.; Ferencei, J.; Ferland, J.; Fernandes, B.; Fernando, W.; Ferrag, S.; Ferrando, J.; Ferrara, V.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferrer, A.; Ferrer, M.L.; Ferrere, D.; Ferretti, C.; Fiascaris, M.; Fiedler, F.; Filipcic, A.; Filippas, A.; Filthaut, F.; Fincke-Keeler, M.; Fiolhais, M.C.N.; Fiorini, L.; Firan, A.; Fischer, G.; Fisher, M.J.; Flechl, M.; Fleck, I.; Fleckner, J.; Fleischmann, P.; Fleischmann, S.; Flick, T.; Flores Castillo, L.R.; Flowerdew, M.J.; Fonseca Martin, T.; Formica, A.; Forti, A.; Fortin, D.; Fournier, D.; Fowler, A.J.; Fowler, K.; Fox, H.; Francavilla, P.; Franchino, S.; Francis, D.; Franklin, M.; Franz, S.; Fraternali, M.; Fratina, S.; Freestone, J.; French, S.T.; Froeschl, R.; Froidevaux, D.; Frost, J.A.; Fukunaga, C.; Fullana Torregrosa, E.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gadfort, T.; Gadomski, S.; Gagliardi, G.; Gagnon, P.; Galea, C.; Gallas, E.J.; Gallo, V.; Gallop, B.J.; Gallus, P.; Galyaev, E.; Gan, K.K.; Gao, Y.S.; Gaponenko, A.; Garcia-Sciveres, M.; Garcia, C.; Garcia Navarro, J.E.; Gardner, R.W.; Garelli, N.; Garitaonandia, H.; Garonne, V.; Gatti, C.; Gaudio, G.; Gautard, V.; Gauzzi, P.; Gavrilenko, I.L.; Gay, C.; Gaycken, G.; Gazis, E.N.; Ge, P.; Gee, C.N.P.; Geich-Gimbel, Ch.; Gellerstedt, K.; Gemme, C.; Genest, M.H.; Gentile, S.; Georgatos, F.; George, S.; Gershon, A.; Ghazlane, H.; Ghodbane, N.; Giacobbe, B.; Giagu, S.; Giakoumopoulou, V.; Giangiobbe, V.; Gianotti, F.; Gibbard, B.; Gibson, A.; Gibson, S.M.; Gilbert, L.M.; Gilchriese, M.; Gilewsky, V.; Gingrich, D.M.; Ginzburg, J.; Giokaris, N.; Giordani, M.P.; Giordano, R.; Giorgi, F.M.; Giovannini, P.; Giraud, P.F.; Girtler, P.; Giugni, D.; Giusti, P.; Gjelsten, B.K.; Gladilin, L.K.; Glasman, C.; Glazov, A.; Glitza, K.W.; Glonti, G.L.; Godfrey, J.; Godlewski, J.; Goebel, M.; Gopfert, T.; Goeringer, C.; Gossling, C.; Gottfert, T.; Goggi, V.; Goldfarb, S.; Goldin, D.; Golling, T.; Gomes, A.; Gomez Fajardo, L.S.; Goncalo, R.; Gonella, L.; Gong, C.; Gonzalez de la Hoz, S.; Gonzalez Silva, M.L.; Gonzalez-Sevilla, S.; Goodson, J.J.; Goossens, L.; Gordon, H.A.; Gorelov, I.; Gorfine, G.; Gorini, B.; Gorini, E.; Gorisek, A.; Gornicki, E.; Gosdzik, B.; Gosselink, M.; Gostkin, M.I.; Gough Eschrich, I.; Gouighri, M.; Goujdami, D.; Goulette, M.P.; Goussiou, A.G.; Goy, C.; Grabowska-Bold, I.; Grafstrom, P.; Grahn, K-J.; Grancagnolo, S.; Grassi, V.; Gratchev, V.; Grau, N.; Gray, H.M.; Gray, J.A.; Graziani, E.; Green, B.; Greenshaw, T.; Greenwood, Z.D.; Gregor, I.M.; Grenier, P.; Griesmayer, E.; Griffiths, J.; Grigalashvili, N.; Grillo, A.A.; Grimm, K.; Grinstein, S.; Grishkevich, Y.V.; Groh, M.; Groll, M.; Gross, E.; Grosse-Knetter, J.; Groth-Jensen, J.; Grybel, K.; Guicheney, C.; Guida, A.; Guillemin, T.; Guler, H.; Gunther, J.; Guo, B.; Gupta, A.; Gusakov, Y.; Gutierrez, A.; Gutierrez, P.; Guttman, N.; Gutzwiller, O.; Guyot, C.; Gwenlan, C.; Gwilliam, C.B.; Haas, A.; Haas, S.; Haber, C.; Hadavand, H.K.; Hadley, D.R.; Haefner, P.; Hartel, R.; Hajduk, Z.; Hakobyan, H.; Haller, J.; Hamacher, K.; Hamilton, A.; Hamilton, S.; Han, L.; Hanagaki, K.; Hance, M.; Handel, C.; Hanke, P.; Hansen, J.R.; Hansen, J.B.; Hansen, J.D.; Hansen, P.H.; Hansl-Kozanecka, T.; Hansson, P.; Hara, K.; Hare, G.A.; Harenberg, T.; Harrington, R.D.; Harris, O.M.; Harrison, K; Hartert, J.; Hartjes, F.; Harvey, A.; Hasegawa, S.; Hasegawa, Y.; Hashemi, K.; Hassani, S.; Haug, S.; Hauschild, M.; Hauser, R.; Havranek, M.; Hawkes, C.M.; Hawkings, R.J.; Hayakawa, T.; Hayward, H.S.; Haywood, S.J.; Head, S.J.; Hedberg, V.; Heelan, L.; Heim, S.; Heinemann, B.; Heisterkamp, S.; Helary, L.; Heller, M.; Hellman, S.; Helsens, C.; Hemperek, T.; Henderson, R.C.W.; Henke, M.; Henrichs, A.; Henriques Correia, A.M.; Henrot-Versille, S.; Hensel, C.; Henss, T.; Hernandez Jimenez, Y.; Hershenhorn, A.D.; Herten, G.; Hertenberger, R.; Hervas, L.; Hessey, N.P.; Higon-Rodriguez, E.; Hill, J.C.; Hiller, K.H.; Hillert, S.; Hillier, S.J.; Hinchliffe, I.; Hines, E.; Hirose, M.; Hirsch, F.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M.C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M.R.; Hoffman, J.; Hoffmann, D.; Hohlfeld, M.; Holy, T.; Holzbauer, J.L.; Homma, Y.; Horazdovsky, T.; Hori, T.; Horn, C.; Horner, S.; Horvat, S.; Hostachy, J-Y.; Hou, S.; Hoummada, A.; Howe, T.; Hrivnac, J.; Hryn'ova, T.; Hsu, P.J.; Hsu, S.C.; Huang, G.S.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Hughes, E.W.; Hughes, G.; Hurwitz, M.; Husemann, U.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Idarraga, J.; Iengo, P.; Igonkina, O.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ince, T.; Ioannou, P.; Iodice, M.; Irles Quiles, A.; Ishikawa, A.; Ishino, M.; Ishmukhametov, R.; Isobe, T.; Issakov, V.; Issever, C.; Istin, S.; Itoh, Y.; Ivashin, A.V.; Iwanski, W.; Iwasaki, H.; Izen, J.M.; Izzo, V.; Jackson, B.; Jackson, J.N.; Jackson, P.; Jaekel, M.R.; Jain, V.; Jakobs, K.; Jakobsen, S.; Jakubek, J.; Jana, D.K.; Jansen, E.; Jantsch, A.; Janus, M.; Jared, R.C.; Jarlskog, G.; Jeanty, L.; Jen-La Plante, I.; Jenni, P.; Jez, P.; Jezequel, S.; Ji, W.; Jia, J.; Jiang, Y.; Jimenez Belenguer, M.; Jin, S.; Jinnouchi, O.; Joffe, D.; Johansen, M.; Johansson, K.E.; Johansson, P.; Johnert, S; Johns, K.A.; Jon-And, K.; Jones, G.; Jones, R.W.L.; Jones, T.J.; Jorge, P.M.; Joseph, J.; Juranek, V.; Jussel, P.; Kabachenko, V.V.; Kaci, M.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kaiser, S.; Kajomovitz, E.; Kalinin, S.; Kalinovskaya, L.V.; Kalinowski, A.; Kama, S.; Kanaya, N.; Kaneda, M.; Kantserov, V.A.; Kanzaki, J.; Kaplan, B.; Kapliy, A.; Kaplon, J.; Kar, D.; Karagounis, M.; Karagoz Unel, M.; Kartvelishvili, V.; Karyukhin, A.N.; Kashif, L.; Kasmi, A.; Kass, R.D.; Kastanas, A.; Kastoryano, M.; Kataoka, M.; Kataoka, Y.; Katsoufis, E.; Katzy, J.; Kaushik, V.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kayl, M.S.; Kayumov, F.; Kazanin, V.A.; Kazarinov, M.Y.; Keates, J.R.; Keeler, R.; Keener, P.T.; Kehoe, R.; Keil, M.; Kekelidze, G.D.; Kelly, M.; Kenyon, M.; Kepka, O.; Kerschen, N.; Kersevan, B.P.; Kersten, S.; Kessoku, K.; Khakzad, M.; Khalil-zada, F.; Khandanyan, H.; Khanov, A.; Kharchenko, D.; Khodinov, A.; Khomich, A.; Khoriauli, G.; Khovanskiy, N.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kim, H.; Kim, M.S.; Kim, P.C.; Kim, S.H.; Kind, O.; Kind, P.; King, B.T.; Kirk, J.; Kirsch, G.P.; Kirsch, L.E.; Kiryunin, A.E.; Kisielewska, D.; Kittelmann, T.; Kiyamura, H.; Kladiva, E.; Klein, M.; Klein, U.; Kleinknecht, K.; Klemetti, M.; Klier, A.; Klimentov, A.; Klingenberg, R.; Klinkby, E.B.; Klioutchnikova, T.; Klok, P.F.; Klous, S.; Kluge, E.E.; Kluge, T.; Kluit, P.; Klute, M.; Kluth, S.; Knecht, N.S.; Kneringer, E.; Ko, B.R.; Kobayashi, T.; Kobel, M.; Koblitz, B.; Kocian, M.; Kocnar, A.; Kodys, P.; Koneke, K.; Konig, A.C.; Koenig, S.; Kopke, L.; Koetsveld, F.; Koevesarki, P.; Koffas, T.; Koffeman, E.; Kohn, F.; Kohout, Z.; Kohriki, T.; Kolanoski, H.; Kolesnikov, V.; Koletsou, I.; Koll, J.; Kollar, D.; Kolos, S.; Kolya, S.D.; Komar, A.A.; Komaragiri, J.R.; Kondo, T.; Kono, T.; Konoplich, R.; Konovalov, S.P.; Konstantinidis, N.; Koperny, S.; Korcyl, K.; Kordas, K.; Korn, A.; Korolkov, I.; Korolkova, E.V.; Korotkov, V.A.; Kortner, O.; Kostka, P.; Kostyukhin, V.V.; Kotov, S.; Kotov, V.M.; Kotov, K.Y.; Kourkoumelis, C.; Koutsman, A.; Kowalewski, R.; Kowalski, H.; Kowalski, T.Z.; Kozanecki, W.; Kozhin, A.S.; Kral, V.; Kramarenko, V.A.; Kramberger, G.; Krasny, M.W.; Krasznahorkay, A.; Kreisel, A.; Krejci, F.; Kretzschmar, J.; Krieger, N.; Krieger, P.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Kruger, H.; Krumshteyn, Z.V.; Kubota, T.; Kuehn, S.; Kugel, A.; Kuhl, T.; Kuhn, D.; Kukhtin, V.; Kulchitsky, Y.; Kuleshov, S.; Kummer, C.; Kuna, M.; Kunkle, J.; Kupco, A.; Kurashige, H.; Kurata, M.; Kurchaninov, L.L.; Kurochkin, Y.A.; Kus, V.; Kwee, R.; La Rotonda, L.; Labbe, J.; Lacasta, C.; Lacava, F.; Lacker, H.; Lacour, D.; Lacuesta, V.R.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Lamanna, M.; Lampen, C.L.; Lampl, W.; Lancon, E.; Landgraf, U.; Landon, M.P.J.; Lane, J.L.; Lankford, A.J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Laplace, S.; Lapoire, C.; Laporte, J.F.; Lari, T.; Larner, A.; Lassnig, M.; Laurelli, P.; Lavrijsen, W.; Laycock, P.; Lazarev, A.B.; Lazzaro, A.; Le Dortz, O.; Le Guirriec, E.; Le Menedeu, E.; Le Vine, M.; Lebedev, A.; Lebel, C.; LeCompte, T.; Ledroit-Guillon, F.; Lee, H.; Lee, J.S.H.; Lee, S.C.; Lefebvre, M.; Legendre, M.; LeGeyt, B.C.; Legger, F.; Leggett, C.; Lehmacher, M.; Lehmann Miotto, G.; Lei, X.; Leitner, R.; Lellouch, D.; 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Urkovsky, E.; Urquijo, P.; Urrejola, P.; Usai, G.; Uslenghi, M.; Vacavant, L.; Vacek, V.; Vachon, B.; Vahsen, S.; Valente, P.; Valentinetti, S.; Valkar, S.; Valladolid Gallego, E.; Vallecorsa, S.; Valls Ferrer, J.A.; Van Berg, R.; van der Graaf, H.; van der Kraaij, E.; van der Poel, E.; van der Ster, D.; van Eldik, N.; van Gemmeren, P.; van Kesteren, Z.; van Vulpen, I.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Vari, R.; Varnes, E.W.; Varouchas, D.; Vartapetian, A.; Varvell, K.E.; Vasilyeva, L.; Vassilakopoulos, V.I.; Vazeille, F.; Vellidis, C.; Veloso, F.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J.C.; Vetterli, M.C.; Vichou, I.; Vickey, T.; Viehhauser, G.H.A.; Villa, M.; Villani, E.G.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M.G.; Vinek, E.; Vinogradov, V.B.; Viret, S.; Virzi, J.; Vitale, A.; Vitells, O.; Vivarelli, I.; Vives Vaque, F.; Vlachos, S.; Vlasak, M.; Vlasov, N.; Vogel, A.; Vokac, P.; Volpi, M.; von der Schmitt, H.; von Loeben, J.; von Radziewski, H.; von Toerne, E.; Vorobel, V.; Vorwerk, V.; Vos, M.; Voss, R.; Voss, T.T.; Vossebeld, J.H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vu Anh, T.; Vudragovic, D.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Walbersloh, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Wang, C.; Wang, H.; Wang, J.; Wang, S.M.; Warburton, A.; Ward, C.P.; Warsinsky, M.; Wastie, R.; Watkins, P.M.; Watson, A.T.; Watson, M.F.; Watts, G.; Watts, S.; Waugh, A.T.; Waugh, B.M.; Weber, M.D.; Weber, M.; Weber, M.S.; Weber, P.; Weidberg, A.R.; Weingarten, J.; Weiser, C.; Wellenstein, H.; Wells, P.S.; Wen, M.; Wenaus, T.; Wendler, S.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Werth, M.; Werthenbach, U.; Wessels, M.; Whalen, K.; White, A.; White, M.J.; White, S.; Whitehead, S.R.; Whiteson, D.; Whittington, D.; Wicek, F.; Wicke, D.; Wickens, F.J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik, L.A.M.; Wildauer, A.; Wildt, M.A.; Wilkens, H.G.; Williams, E.; Williams, H.H.; Willocq, S.; Wilson, J.A.; Wilson, M.G.; Wilson, A.; Wingerter-Seez, I.; Winklmeier, F.; Wittgen, M.; Wolter, M.W.; Wolters, H.; Wosiek, B.K.; Wotschack, J.; Woudstra, M.J.; Wraight, K.; Wright, C.; Wright, D.; Wrona, B.; Wu, S.L.; Wu, X.; Wulf, E.; Wynne, B.M.; Xaplanteris, L.; Xella, S.; Xie, S.; Xu, D.; Xu, N.; Yamada, M.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamaoka, J.; Yamazaki, T.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, U.K.; Yang, Z.; Yao, W-M.; Yao, Y.; Yasu, Y.; Ye, J.; Ye, S.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Young, C.; Youssef, S.P.; Yu, D.; Yu, J.; Yuan, L.; Yurkewicz, A.; Zaidan, R.; Zaitsev, A.M.; Zajacova, Z.; Zambrano, V.; Zanello, L.; Zaytsev, A.; Zeitnitz, C.; Zeller, M.; Zemla, A.; Zendler, C.; Zenin, O.; Zenis, T.; Zenonos, Z.; Zenz, S.; Zerwas, D.; Zevi della Porta, G.; Zhan, Z.; Zhang, H.; Zhang, J.; Zhang, Q.; Zhang, X.; Zhao, L.; Zhao, T.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, N.; Zhou, Y.; Zhu, C.G.; Zhu, H.; Zhu, Y.; Zhuang, X.; Zhuravlov, V.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Ziolkowski, M.; Zivkovic, L.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zutshi, V.

    2010-01-01

    The simulation software for the ATLAS Experiment at the Large Hadron Collider is being used for large-scale production of events on the LHC Computing Grid. This simulation requires many components, from the generators that simulate particle collisions, through packages simulating the response of the various detectors and triggers. All of these components come together under the ATLAS simulation infrastructure. In this paper, that infrastructure is discussed, including that supporting the detector description, interfacing the event generation, and combining the GEANT4 simulation of the response of the individual detectors. Also described are the tools allowing the software validation, performance testing, and the validation of the simulated output against known physics processes.

  5. A Case Study Based Analysis of Performance Metrics for Green Infrastructure

    Science.gov (United States)

    Gordon, B. L.; Ajami, N.; Quesnel, K.

    2017-12-01

    Aging infrastructure, population growth, and urbanization are demanding new approaches to management of all components of the urban water cycle, including stormwater. Traditionally, urban stormwater infrastructure was designed to capture and convey rainfall-induced runoff out of a city through a network of curbs, gutters, drains, and pipes, also known as grey infrastructure. These systems were planned with a single-purpose and designed under the assumption of hydrologic stationarity, a notion that no longer holds true in the face of a changing climate. One solution gaining momentum around the world is green infrastructure (GI). Beyond stormwater quality improvement and quantity reduction (or technical benefits), GI solutions offer many environmental, economic, and social benefits. Yet many practical barriers have prevented the widespread adoption of these systems worldwide. At the center of these challenges is the inability of stakeholders to know how to monitor, measure, and assess the multi-sector performance of GI systems. Traditional grey infrastructure projects require different monitoring strategies than natural systems; there are no overarching policies on how to best design GI monitoring and evaluation systems and measure performance. Previous studies have attempted to quantify the performance of GI, mostly using one evaluation method on a specific case study. We use a case study approach to address these knowledge gaps and develop a conceptual model of how to evaluate the performance of GI through the lens of financing. First, we examined many different case studies of successfully implemented GI around the world. Then we narrowed in on 10 exemplary case studies. For each case studies, we determined what performance method the project developer used such as LCA, TBL, Low Impact Design Assessment (LIDA) and others. Then, we determined which performance metrics were used to determine success and what data was needed to calculate those metrics. Finally, we

  6. HCP, grid and data infrastructures for astrophysics: an integrated view

    International Nuclear Information System (INIS)

    Pasian, F.

    2009-01-01

    Also in the case of astrophysics, the capability of performing Big Science requires the availability of large Hcp facilities. But computational resources alone are far from being enough for the community: as a matter of fact, the whole set of e-infrastructures (network, computing nodes, data repositories, applications) need to work in an inter operable way. This implies the development of common (or at least compatible) user interfaces to computing resources, transparent access to observations and numerical simulations through the Virtual Observatory, integrated data processing pipelines, data mining and semantic web applications. Achieving this inter operability goal is a must to build a real Knowledge Infrastructure in the astrophysical domain.

  7. Key performance indicators of charging infrastructure

    NARCIS (Netherlands)

    Helmus, J.; van den Hoed, R.

    2016-01-01

    The Netherlands are one of the frontrunners in stimulating electric mobility in Europe when it comes to the charging infrastructure density and electric vehicle adoption. Municipalities play an instrumental role in the rollout of public charging infrastructure while they have little insight in the

  8. An Open Computing Infrastructure that Facilitates Integrated Product and Process Development from a Decision-Based Perspective

    Science.gov (United States)

    Hale, Mark A.

    1996-01-01

    Computer applications for design have evolved rapidly over the past several decades, and significant payoffs are being achieved by organizations through reductions in design cycle times. These applications are overwhelmed by the requirements imposed during complex, open engineering systems design. Organizations are faced with a number of different methodologies, numerous legacy disciplinary tools, and a very large amount of data. Yet they are also faced with few interdisciplinary tools for design collaboration or methods for achieving the revolutionary product designs required to maintain a competitive advantage in the future. These organizations are looking for a software infrastructure that integrates current corporate design practices with newer simulation and solution techniques. Such an infrastructure must be robust to changes in both corporate needs and enabling technologies. In addition, this infrastructure must be user-friendly, modular and scalable. This need is the motivation for the research described in this dissertation. The research is focused on the development of an open computing infrastructure that facilitates product and process design. In addition, this research explicitly deals with human interactions during design through a model that focuses on the role of a designer as that of decision-maker. The research perspective here is taken from that of design as a discipline with a focus on Decision-Based Design, Theory of Languages, Information Science, and Integration Technology. Given this background, a Model of IPPD is developed and implemented along the lines of a traditional experimental procedure: with the steps of establishing context, formalizing a theory, building an apparatus, conducting an experiment, reviewing results, and providing recommendations. Based on this Model, Design Processes and Specification can be explored in a structured and implementable architecture. An architecture for exploring design called DREAMS (Developing Robust

  9. Cloud Infrastructure & Applications - CloudIA

    Science.gov (United States)

    Sulistio, Anthony; Reich, Christoph; Doelitzscher, Frank

    The idea behind Cloud Computing is to deliver Infrastructure-as-a-Services and Software-as-a-Service over the Internet on an easy pay-per-use business model. To harness the potentials of Cloud Computing for e-Learning and research purposes, and to small- and medium-sized enterprises, the Hochschule Furtwangen University establishes a new project, called Cloud Infrastructure & Applications (CloudIA). The CloudIA project is a market-oriented cloud infrastructure that leverages different virtualization technologies, by supporting Service-Level Agreements for various service offerings. This paper describes the CloudIA project in details and mentions our early experiences in building a private cloud using an existing infrastructure.

  10. PRACE - The European HPC Infrastructure

    Science.gov (United States)

    Stadelmeyer, Peter

    2014-05-01

    The mission of PRACE (Partnership for Advanced Computing in Europe) is to enable high impact scientific discovery and engineering research and development across all disciplines to enhance European competitiveness for the benefit of society. PRACE seeks to realize this mission by offering world class computing and data management resources and services through a peer review process. This talk gives a general overview about PRACE and the PRACE research infrastructure (RI). PRACE is established as an international not-for-profit association and the PRACE RI is a pan-European supercomputing infrastructure which offers access to computing and data management resources at partner sites distributed throughout Europe. Besides a short summary about the organization, history, and activities of PRACE, it is explained how scientists and researchers from academia and industry from around the world can access PRACE systems and which education and training activities are offered by PRACE. The overview also contains a selection of PRACE contributions to societal challenges and ongoing activities. Examples of the latter are beside others petascaling, application benchmark suite, best practice guides for efficient use of key architectures, application enabling / scaling, new programming models, and industrial applications. The Partnership for Advanced Computing in Europe (PRACE) is an international non-profit association with its seat in Brussels. The PRACE Research Infrastructure provides a persistent world-class high performance computing service for scientists and researchers from academia and industry in Europe. The computer systems and their operations accessible through PRACE are provided by 4 PRACE members (BSC representing Spain, CINECA representing Italy, GCS representing Germany and GENCI representing France). The Implementation Phase of PRACE receives funding from the EU's Seventh Framework Programme (FP7/2007-2013) under grant agreements RI-261557, RI-283493 and RI

  11. COMPUTING

    CERN Multimedia

    I. Fisk

    2011-01-01

    Introduction CMS distributed computing system performed well during the 2011 start-up. The events in 2011 have more pile-up and are more complex than last year; this results in longer reconstruction times and harder events to simulate. Significant increases in computing capacity were delivered in April for all computing tiers, and the utilisation and load is close to the planning predictions. All computing centre tiers performed their expected functionalities. Heavy-Ion Programme The CMS Heavy-Ion Programme had a very strong showing at the Quark Matter conference. A large number of analyses were shown. The dedicated heavy-ion reconstruction facility at the Vanderbilt Tier-2 is still involved in some commissioning activities, but is available for processing and analysis. Facilities and Infrastructure Operations Facility and Infrastructure operations have been active with operations and several important deployment tasks. Facilities participated in the testing and deployment of WMAgent and WorkQueue+Request...

  12. Low carbon technology performance vs infrastructure vulnerability: analysis through the local and global properties space.

    Science.gov (United States)

    Dawson, David A; Purnell, Phil; Roelich, Katy; Busch, Jonathan; Steinberger, Julia K

    2014-11-04

    Renewable energy technologies, necessary for low-carbon infrastructure networks, are being adopted to help reduce fossil fuel dependence and meet carbon mitigation targets. The evolution of these technologies has progressed based on the enhancement of technology-specific performance criteria, without explicitly considering the wider system (global) impacts. This paper presents a methodology for simultaneously assessing local (technology) and global (infrastructure) performance, allowing key technological interventions to be evaluated with respect to their effect on the vulnerability of wider infrastructure systems. We use exposure of low carbon infrastructure to critical material supply disruption (criticality) to demonstrate the methodology. A series of local performance changes are analyzed; and by extension of this approach, a method for assessing the combined criticality of multiple materials for one specific technology is proposed. Via a case study of wind turbines at both the material (magnets) and technology (turbine generators) levels, we demonstrate that analysis of a given intervention at different levels can lead to differing conclusions regarding the effect on vulnerability. Infrastructure design decisions should take a systemic approach; without these multilevel considerations, strategic goals aimed to help meet low-carbon targets, that is, through long-term infrastructure transitions, could be significantly jeopardized.

  13. Exploring the Mediation Between KM Infrastructure Capabilities and Organisational Performance: The Penetration of Learning by KM Practices

    OpenAIRE

    Meng-Lin Shih; Shu-Hui Chuang; Chechen Liao

    2009-01-01

    Previous studies have examined the relationship between knowledge management (KM) infrastructure capabilities and organisational performance. However, most studies neglect the mediating effect of organisational learning by KM practices (OLKMP) in the relationship between KM infrastructure capabilities and organisational performance. This study uses the survey method to discuss the relationships governing KM infrastructure capabilities, OLKMP and organisational performance. Results of the anal...

  14. Development of computational infrastructure to support hyper-resolution large-ensemble hydrology simulations from local-to-continental scales

    Data.gov (United States)

    National Aeronautics and Space Administration — Development of computational infrastructure to support hyper-resolution large-ensemble hydrology simulations from local-to-continental scales A move is currently...

  15. Privacy-Preserving Data Aggregation Protocol for Fog Computing-Assisted Vehicle-to-Infrastructure Scenario

    Directory of Open Access Journals (Sweden)

    Yanan Chen

    2018-01-01

    Full Text Available Vehicle-to-infrastructure (V2I communication enables moving vehicles to upload real-time data about road surface situation to the Internet via fixed roadside units (RSU. Thanks to the resource restriction of mobile vehicles, fog computation-enhanced V2I communication scenario has received increasing attention recently. However, how to aggregate the sensed data from vehicles securely and efficiently still remains open to the V2I communication scenario. In this paper, a light-weight and anonymous aggregation protocol is proposed for the fog computing-based V2I communication scenario. With the proposed protocol, the data collected by the vehicles can be efficiently obtained by the RSU in a privacy-preserving manner. Particularly, we first suggest a certificateless aggregate signcryption (CL-A-SC scheme and prove its security in the random oracle model. The suggested CL-A-SC scheme, which is of independent interest, can achieve the merits of certificateless cryptography and signcryption scheme simultaneously. Then we put forward the anonymous aggregation protocol for V2I communication scenario as one extension of the suggested CL-A-SC scheme. Security analysis demonstrates that the proposed aggregation protocol achieves desirable security properties. The performance comparison shows that the proposed protocol significantly reduces the computation and communication overhead compared with the up-to-date protocols in this field.

  16. Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing.

    Science.gov (United States)

    Shatil, Anwar S; Younas, Sohail; Pourreza, Hossein; Figley, Chase R

    2015-01-01

    With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications.

  17. IT infrastructure and competitive aggressiveness in explaining and predicting performance

    NARCIS (Netherlands)

    Ajamieh, Aseel; Benitez, Jose; Braojos, Jessica; Gelhard, Carsten Volker

    2016-01-01

    While prior Information Systems and Operations Management literature emphasizes the role of both the firm's IT infrastructure and the general degree of competition as antecedents of firm performance, the organizational capabilities that mediate these important relationships remain undetermined.

  18. Using Cloud Services for Library IT Infrastructure

    OpenAIRE

    Erik Mitchell

    2010-01-01

    Cloud computing comes in several different forms and this article documents how service, platform, and infrastructure forms of cloud computing have been used to serve library needs. Following an overview of these uses the article discusses the experience of one library in migrating IT infrastructure to a cloud environment and concludes with a model for assessing cloud computing.

  19. Security Services Lifecycle Management in on-demand infrastructure services

    NARCIS (Netherlands)

    Demchenko, Y.; de Laat, C.; Lopez, D.R.; García-Espín, J.A.; Qiu, J.; Zhao, G.; Rong, C.

    2010-01-01

    Modern e-Science and high technology industry require high-performance and complicated network and computer infrastructure to support distributed collaborating groups of researchers and applications that should be provisioned on-demand. The effective use and management of the dynamically provisioned

  20. A data infrastructure for the assessment of health care performance: lessons from the BRIDGE-health project.

    Science.gov (United States)

    Bernal-Delgado, Enrique; Estupiñán-Romero, Francisco

    2018-01-01

    The integration of different administrative data sources from a number of European countries has been shown useful in the assessment of unwarranted variations in health care performance. This essay describes the procedures used to set up a data infrastructure (e.g., data access and exchange, definition of the minimum common wealth of data required, and the development of the relational logic data model) and, the methods to produce trustworthy healthcare performance measurements (e.g., ontologies standardisation and quality assurance analysis). The paper ends providing some hints on how to use these lessons in an eventual European infrastructure on public health research and monitoring. Although the relational data infrastructure developed has been proven accurate, effective to compare health system performance across different countries, and efficient enough to deal with hundred of millions of episodes, the logic data model might not be responsive if the European infrastructure aims at including electronic health records and carrying out multi-cohort multi-intervention comparative effectiveness research. The deployment of a distributed infrastructure based on semantic interoperability, where individual data remain in-country and open-access scripts for data management and analysis travel around the hubs composing the infrastructure, might be a sensible way forward.

  1. Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing

    Science.gov (United States)

    Shatil, Anwar S.; Younas, Sohail; Pourreza, Hossein; Figley, Chase R.

    2015-01-01

    With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications. PMID:27279746

  2. Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing

    Directory of Open Access Journals (Sweden)

    Anwar S. Shatil

    2015-01-01

    Full Text Available With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1 inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2 highlight their main advantages; 3 discuss when it may (and may not be advisable to use them; 4 review some of their potential problems and barriers to access; and finally 5 give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc., a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications.

  3. Global information infrastructure.

    Science.gov (United States)

    Lindberg, D A

    1994-01-01

    The High Performance Computing and Communications Program (HPCC) is a multiagency federal initiative under the leadership of the White House Office of Science and Technology Policy, established by the High Performance Computing Act of 1991. It has been assigned a critical role in supporting the international collaboration essential to science and to health care. Goals of the HPCC are to extend USA leadership in high performance computing and networking technologies; to improve technology transfer for economic competitiveness, education, and national security; and to provide a key part of the foundation for the National Information Infrastructure. The first component of the National Institutes of Health to participate in the HPCC, the National Library of Medicine (NLM), recently issued a solicitation for proposals to address a range of issues, from privacy to 'testbed' networks, 'virtual reality,' and more. These efforts will build upon the NLM's extensive outreach program and other initiatives, including the Unified Medical Language System (UMLS), MEDLARS, and Grateful Med. New Internet search tools are emerging, such as Gopher and 'Knowbots'. Medicine will succeed in developing future intelligent agents to assist in utilizing computer networks. Our ability to serve patients is so often restricted by lack of information and knowledge at the time and place of medical decision-making. The new technologies, properly employed, will also greatly enhance our ability to serve the patient.

  4. Smart Cyber Infrastructure for Big Data processing

    NARCIS (Netherlands)

    Makkes, M.X.; Cushing, R.; Oprescu, A.M.; Koning, R.; Grosso, P.; Meijer, R.J.; Laat, C. de

    2014-01-01

    The landscape of research cyber infrastructure is rapidly changing. There is a move towards virtualized and programmable infrastructure. The cloud paradigm enables the use of computing resources in different places and allows for optimizing workflows in either bringing computing to the data or the

  5. Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment

    Science.gov (United States)

    Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Usman, Mohammed Joda

    2017-01-01

    Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing. PMID:28467505

  6. Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment.

    Science.gov (United States)

    Madni, Syed Hamid Hussain; Abd Latiff, Muhammad Shafie; Abdullahi, Mohammed; Abdulhamid, Shafi'i Muhammad; Usman, Mohammed Joda

    2017-01-01

    Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.

  7. Evolution of the Atlas data and computing model for a Tier-2 in the EGI infrastructure

    CERN Document Server

    Fernandez, A; The ATLAS collaboration; AMOROS, G; VILLAPLANA, M; FASSI, F; KACI, M; LAMAS, A; OLIVER, E; SALT, J; SANCHEZ, J; SANCHEZ, V

    2012-01-01

    ABSTRAC ISCG 2012 Evolution of the Atlas data and computing model for a Tier2 in the EGI infrastructure During last years the Atlas computing model has moved from a more strict design, where every Tier2 had a liaison and a network dependence from a Tier1, to a more meshed approach where every cloud could be connected. Evolution of ATLAS data models requires changes in ATLAS Tier2s policy for the data replication, dynamic data caching and remote data access. It also requires rethinking the network infrastructure to enable any Tier2 and associated Tier3 to easily connect to any Tier1 or Tier2. Tier2s are becoming more and more important in the ATLAS computing model as it allows more data to be readily accessible for analysis jobs to all users, independently of their geographical location. The Tier2s disk space has been reserved for real, simulated, calibration and alignment, group, and user data. A buffer disk space is needed for input and output data for simulations jobs. Tier2s are going to be used more effic...

  8. Security audits of multi-tier virtual infrastructures in public infrastructure clouds

    DEFF Research Database (Denmark)

    Bleikertz, Sören; Schunter, Matthias; Probst, Christian W.

    2010-01-01

    Cloud computing has gained remarkable popularity in the recent years by a wide spectrum of consumers, ranging from small start-ups to governments. However, its benefits in terms of flexibility, scalability, and low upfront investments, are shadowed by security challenges which inhibit its adoption....... Managed through a web-services interface, users can configure highly flexible but complex cloud computing environments. Furthermore, users misconfiguring such cloud services poses a severe security risk that can lead to security incidents, e.g., erroneous exposure of services due to faulty network...... security configurations. In this article we present a novel approach in the security assessment of the end-user configuration of multi-tier architectures deployed on infrastructure clouds such as Amazon EC2. In order to perform this assessment for the currently deployed configuration, we automated...

  9. The Czech National Grid Infrastructure

    Science.gov (United States)

    Chudoba, J.; Křenková, I.; Mulač, M.; Ruda, M.; Sitera, J.

    2017-10-01

    The Czech National Grid Infrastructure is operated by MetaCentrum, a CESNET department responsible for coordinating and managing activities related to distributed computing. CESNET as the Czech National Research and Education Network (NREN) provides many e-infrastructure services, which are used by 94% of the scientific and research community in the Czech Republic. Computing and storage resources owned by different organizations are connected by fast enough network to provide transparent access to all resources. We describe in more detail the computing infrastructure, which is based on several different technologies and covers grid, cloud and map-reduce environment. While the largest part of CPUs is still accessible via distributed torque servers, providing environment for long batch jobs, part of infrastructure is available via standard EGI tools in EGI, subset of NGI resources is provided into EGI FedCloud environment with cloud interface and there is also Hadoop cluster provided by the same e-infrastructure.A broad spectrum of computing servers is offered; users can choose from standard 2 CPU servers to large SMP machines with up to 6 TB of RAM or servers with GPU cards. Different groups have different priorities on various resources, resource owners can even have an exclusive access. The software is distributed via AFS. Storage servers offering up to tens of terabytes of disk space to individual users are connected via NFS4 on top of GPFS and access to long term HSM storage with peta-byte capacity is also provided. Overview of available resources and recent statistics of usage will be given.

  10. Technology Trends in Cloud Infrastructure

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Cloud computing is growing at an exponential pace with an increasing number of workloads being hosted in mega-scale public clouds such as Microsoft Azure. Designing and operating such large infrastructures requires not only a significant capital spend for provisioning datacenters, servers, networking and operating systems, but also R&D investments to capitalize on disruptive technology trends and emerging workloads such as AI/ML. This talk will cover the various infrastructure innovations being implemented in large scale public clouds and opportunities/challenges ahead to deliver the next generation of scale computing. About the speaker Kushagra Vaid is the general manager and distinguished engineer for Hardware Infrastructure in the Microsoft Azure division. He is accountable for the architecture and design of compute and storage platforms, which are the foundation for Microsoft’s global cloud-scale services. He and his team have successfully delivered four generations of hyperscale cloud hardwar...

  11. Dedicated IT infrastructure for Smart Levee Monitoring and Flood Decision Support

    Directory of Open Access Journals (Sweden)

    Balis Bartosz

    2016-01-01

    Full Text Available Smart levees are being increasingly investigated as a flood protection technology. However, in large-scale emergency situations, a flood decision support system may need to collect and process data from hundreds of kilometers of smart levees; such a scenario requires a resilient and scalable IT infrastructure, capable of providing urgent computing services in order to perform frequent data analyses required in decision making, and deliver their results in a timely fashion. We present the ISMOP IT infrastructure for smart levee monitoring, designed to support decision making in large-scale emergency situations. Most existing approaches to urgent computing services in decision support systems dealing with natural disasters focus on delivering quality of service for individual, isolated subsystems of the IT infrastructure (such as computing, storage, or data transmission. We propose a holistic approach to dynamic system management during both urgent (emergency and normal (non-emergency operation. In this approach, we introduce a Holistic Computing Controller which calculates and deploys a globally optimal configuration for the entire IT infrastructure, based on cost-of-operation and quality-of-service (QoS requirements of individual IT subsystems, expressed in the form of Service Level Agreements (SLAs. Our approach leads to improved configuration settings and, consequently, better fulfilment of the system’s cost and QoS requirements than would have otherwise been possible had the configuration of all subsystems been managed in isolation.

  12. SAME4HPC: A Promising Approach in Building a Scalable and Mobile Environment for High-Performance Computing

    Energy Technology Data Exchange (ETDEWEB)

    Karthik, Rajasekar [ORNL

    2014-01-01

    In this paper, an architecture for building Scalable And Mobile Environment For High-Performance Computing with spatial capabilities called SAME4HPC is described using cutting-edge technologies and standards such as Node.js, HTML5, ECMAScript 6, and PostgreSQL 9.4. Mobile devices are increasingly becoming powerful enough to run high-performance apps. At the same time, there exist a significant number of low-end and older devices that rely heavily on the server or the cloud infrastructure to do the heavy lifting. Our architecture aims to support both of these types of devices to provide high-performance and rich user experience. A cloud infrastructure consisting of OpenStack with Ubuntu, GeoServer, and high-performance JavaScript frameworks are some of the key open-source and industry standard practices that has been adopted in this architecture.

  13. The Computational Infrastructure for Geodynamics as a Community of Practice

    Science.gov (United States)

    Hwang, L.; Kellogg, L. H.

    2016-12-01

    Computational Infrastructure for Geodynamics (CIG), geodynamics.org, originated in 2005 out of community recognition that the efforts of individual or small groups of researchers to develop scientifically-sound software is impossible to sustain, duplicates effort, and makes it difficult for scientists to adopt state-of-the art computational methods that promote new discovery. As a community of practice, participants in CIG share an interest in computational modeling in geodynamics and work together on open source software to build the capacity to support complex, extensible, scalable, interoperable, reliable, and reusable software in an effort to increase the return on investment in scientific software development and increase the quality of the resulting software. The group interacts regularly to learn from each other and better their practices formally through webinar series, workshops, and tutorials and informally through listservs and hackathons. Over the past decade, we have learned that successful scientific software development requires at a minimum: collaboration between domain-expert researchers, software developers and computational scientists; clearly identified and committed lead developer(s); well-defined scientific and computational goals that are regularly evaluated and updated; well-defined benchmarks and testing throughout development; attention throughout development to usability and extensibility; understanding and evaluation of the complexity of dependent libraries; and managed user expectations through education, training, and support. CIG's code donation standards provide the basis for recently formalized best practices in software development (geodynamics.org/cig/dev/best-practices/). Best practices include use of version control; widely used, open source software libraries; extensive test suites; portable configuration and build systems; extensive documentation internal and external to the code; and structured, human readable input formats.

  14. Impact of Infrastructure and Production Processes on Rioja Wine Supply Chain Performance

    Directory of Open Access Journals (Sweden)

    José Roberto Díaz-Reza

    2018-01-01

    Full Text Available This paper presents a structural equation model for analyzing the relationship between four latent variables: infrastructure, production processes, transport benefits, and economic benefits within the supply chain for wine from La Rioja, Spain, by incorporating 12 observed variables. The model proposes six hypothesis that were tested using information gathered from 64 surveys completed by managers of several wineries in the region. The WarpPLS v.5® software (Version 5.0, Script Warp Systems, Laredo, TX, USA was used to execute the model and analyze the direct, indirect, and total effects among latent variables. The results show that the control of production processes is a direct source of economic and transport benefits because of its higher explanatory power of those variables. Similarly, infrastructure is a direct source of transport and production benefits, and some of them are given indirectly. In addition, infrastructure does not have a direct effect on economic benefits; however, there were indirect effects given through production process and transport benefits. Infrastructure is a very important variable because of its influence in the final performance, but also because of its high environmental impact. Finally, economic benefits were explained in 43.8%, 19.1% belonging to production process, 21.1% coming from transport benefits, and 3.7% from infrastructure.

  15. Cloud computing: Grijs of Groen? over energie-efficiëntie en duurzaamheid van Infrastructure as a Service

    NARCIS (Netherlands)

    Spitzer, A.M.; Worm, D.T.H.; Bomhof, F.W.; Bastiaans, M.

    2012-01-01

    Cloud computing is het op afroep, dynamisch ontsluiten van een verzameling ICT-middelen (zoals netwerken, opslag, verwerking, applicaties en diensten) over een netwerk. In dit rapport is uitgegaan van “Infrastructure as a Service”-clouds: opslag- en verwerkingscapaciteit wordt als dienst ter

  16. A Case Study on Neural Inspired Dynamic Memory Management Strategies for High Performance Computing.

    Energy Technology Data Exchange (ETDEWEB)

    Vineyard, Craig Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Verzi, Stephen Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-09-01

    As high performance computing architectures pursue more computational power there is a need for increased memory capacity and bandwidth as well. A multi-level memory (MLM) architecture addresses this need by combining multiple memory types with different characteristics as varying levels of the same architecture. How to efficiently utilize this memory infrastructure is an unknown challenge, and in this research we sought to investigate whether neural inspired approaches can meaningfully help with memory management. In particular we explored neurogenesis inspired re- source allocation, and were able to show a neural inspired mixed controller policy can beneficially impact how MLM architectures utilize memory.

  17. A multi VO Grid infrastructure at DESY

    International Nuclear Information System (INIS)

    Gellrich, Andreas

    2010-01-01

    As a centre for research with particle accelerators and synchrotron light, DESY operates a Grid infrastructure in the context of the EU-project EGEE and the national Grid initiative D-GRID. All computing and storage resources are located in one Grid infrastructure which supports a number of Virtual Organizations of different disciplines, including non-HEP groups such as the Photon Science community. Resource distribution is based on fair share methods without dedicating hardware to user groups. Production quality of the infrastructure is guaranteed by embedding it into the DESY computer centre.

  18. Development of multi-functional streetscape green infrastructure using a performance index approach

    Czech Academy of Sciences Publication Activity Database

    Tiwary, A.; Williams, L. D.; Heidrich, O.; Namdeo, A.; Bandaru, V.; Calfapietra, Carlo

    2016-01-01

    Roč. 208, jan (2016), s. 209-220 ISSN 0269-7491 Institutional support: RVO:67179843 Keywords : Green infrastructure * Multi-functional * Pollution * Performance index * Streetscape Subject RIV: EH - Ecology, Behaviour Impact factor: 5.099, year: 2016

  19. UNH Data Cooperative: A Cyber Infrastructure for Earth System Studies

    Science.gov (United States)

    Braswell, B. H.; Fekete, B. M.; Prusevich, A.; Gliden, S.; Magill, A.; Vorosmarty, C. J.

    2007-12-01

    Earth system scientists and managers have a continuously growing demand for a wide array of earth observations derived from various data sources including (a) modern satellite retrievals, (b) "in-situ" records, (c) various simulation outputs, and (d) assimilated data products combining model results with observational records. The sheer quantity of data, and formatting inconsistencies make it difficult for users to take full advantage of this important information resource. Thus the system could benefit from a thorough retooling of our current data processing procedures and infrastructure. Emerging technologies, like OPeNDAP and OGC map services, open standard data formats (NetCDF, HDF) data cataloging systems (NASA-Echo, Global Change Master Directory, etc.) are providing the basis for a new approach in data management and processing, where web- services are increasingly designed to serve computer-to-computer communications without human interactions and complex analysis can be carried out over distributed computer resources interconnected via cyber infrastructure. The UNH Earth System Data Collaborative is designed to utilize the aforementioned emerging web technologies to offer new means of access to earth system data. While the UNH Data Collaborative serves a wide array of data ranging from weather station data (Climate Portal) to ocean buoy records and ship tracks (Portsmouth Harbor Initiative) to land cover characteristics, etc. the underlaying data architecture shares common components for data mining and data dissemination via web-services. Perhaps the most unique element of the UNH Data Cooperative's IT infrastructure is its prototype modeling environment for regional ecosystem surveillance over the Northeast corridor, which allows the integration of complex earth system model components with the Cooperative's data services. While the complexity of the IT infrastructure to perform complex computations is continuously increasing, scientists are often forced

  20. Transactional approach in assessment of operational performance of companies in transport infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Dubrovsky, V.; Yaroshevich, N.; Kuzmin, E.

    2016-07-01

    Offer an alternative method to assess operational performance of companies in transport infrastructure of a region by making a comparison between transaction costs. The method is supposed to be a cross-functional and possibly applied to an analysis of economic entities of a different order (country, region, sector, companies) while evaluating “viscosity” / complexity of the outside and the inside. The paper includes an analysis of various methodological approaches to assess a development level of the transport infrastructure in a region. Within the author's approach and for purposed of the research, an index of transaction capacity or the transactionalness index is proposed, which determines a level of transaction costs calculated against the cost of production and revenue. The approach is piloted using the region-wise consolidated financial data of companies involved in the Russian transport infrastructure for 2005/2013. The proposed alternative way to measure corporate operating efficiency has proved its academic consistency. A specific comparison between the transaction costs using the transactionalness index allows first to identify companies or regions/sectors, where there is excess complexity of economical communication in bargaining. Secondly, the index does not only point out indirectly to a degree of development in the institutional environment, but also the infrastructure (the transport one in the example given). Third, the transactionalness level may say of uncertainty and risks. As an addition to theoretical and methodological aspects of transaction costs, the authors justify an approach to their size estimation, as well as their differentiation dividing them into two groups: those of a natural type and a background type. In a course of their discussion, the authors have concluded that there are such transaction costs in place, which are standard in a manner of speaking. There is a discussion whether it is scientifically reasonable to use an

  1. Information infrastructure development in NRU «MPEI»

    Directory of Open Access Journals (Sweden)

    E. G. Gridina

    2016-01-01

    Full Text Available The article describes the work on support and development of information infrastructure NRU «MPEI». Information infrastructure have different approaches to the defi nition. The authors defi ne the information infrastructure as a set of basic information services, computing, storage and data transmission systems that provide user access to information resources. New conditions dictate new approaches to building the education system in general and the educational process in each educational institution. NRU «MPEI» working to create a modern information infrastructure, including automated control systems, information resources and services, modular systems disciplines. This article describes the requirements for a modern information infrastructure of the NRU «MPEI», that provides students and teachers with the necessary services. Information infrastructure includes a set of software and hardware to ensure interaction between the participants of the educational process. All services and NRU «MPEI» system included in the unifi ed information educational environment (UIEE. Architecture UIEE NRU «MPEI» is displayed in the article. UIEE NRU «MPEI» is deployed on the basis of information network NRU «MPEI» and enables a comprehensive optimization of university management in various areas. Information and Computing Center supporting information and computer network NRU «MPEI», bought more than 4800 licenses in 43 different license versions of the software manufacturers. The server segment information network NRU «MPEI» contains a complex infrastructure and application servers for processing and storing information.The segment there are 20 high-performance server and storage system capacity of over 30 TB. In the server segment deployed complex systems to meet the needs in the various fi elds of activity NRU «MPEI», and the educational system to support the economic , scientifi c and human complex. Currently, ICC also pays great

  2. Assessing infrastructure vulnerability to major floods

    Energy Technology Data Exchange (ETDEWEB)

    Jenssen, Lars

    1998-12-31

    This thesis proposes a method for assessing the direct effects of serious floods on a physical infrastructure or utility. This method should be useful in contingency planning and in the design of structures likely to be damaged by flooding. A review is given of (1) methods of floodplain management and strategies for mitigating floods, (2) methods of risk analysis that will become increasingly important in flood management, (3) methods for hydraulic computations, (4) a variety of scour assessment methods and (5) applications of geographic information systems (GIS) to the analysis of flood vulnerability. Three computer codes were developed: CULVCAP computes the headwater level for circular and box culverts, SCOUR for assessing riprap stability and scour depths, and FASTFLOOD prepares input rainfall series and input files for the rainfall-runoff model used in the case study. A road system in central Norway was chosen to study how to analyse the flood vulnerability of an infrastructure. Finally, the thesis proposes a method for analysing the flood vulnerability of physical infrastructure. The method involves a general stage that will provide data on which parts of the infrastructure are potentially vulnerable to flooding and how to analyse them, and a specific stage which is concerned with analysing one particular kind of physical infrastructure in a study area. 123 refs., 59 figs., 17 tabs= .

  3. Controlling Infrastructure Costs: Right-Sizing the Mission Control Facility

    Science.gov (United States)

    Martin, Keith; Sen-Roy, Michael; Heiman, Jennifer

    2009-01-01

    Johnson Space Center's Mission Control Center is a space vehicle, space program agnostic facility. The current operational design is essentially identical to the original facility architecture that was developed and deployed in the mid-90's. In an effort to streamline the support costs of the mission critical facility, the Mission Operations Division (MOD) of Johnson Space Center (JSC) has sponsored an exploratory project to evaluate and inject current state-of-the-practice Information Technology (IT) tools, processes and technology into legacy operations. The general push in the IT industry has been trending towards a data-centric computer infrastructure for the past several years. Organizations facing challenges with facility operations costs are turning to creative solutions combining hardware consolidation, virtualization and remote access to meet and exceed performance, security, and availability requirements. The Operations Technology Facility (OTF) organization at the Johnson Space Center has been chartered to build and evaluate a parallel Mission Control infrastructure, replacing the existing, thick-client distributed computing model and network architecture with a data center model utilizing virtualization to provide the MCC Infrastructure as a Service. The OTF will design a replacement architecture for the Mission Control Facility, leveraging hardware consolidation through the use of blade servers, increasing utilization rates for compute platforms through virtualization while expanding connectivity options through the deployment of secure remote access. The architecture demonstrates the maturity of the technologies generally available in industry today and the ability to successfully abstract the tightly coupled relationship between thick-client software and legacy hardware into a hardware agnostic "Infrastructure as a Service" capability that can scale to meet future requirements of new space programs and spacecraft. This paper discusses the benefits

  4. Galaxy CloudMan: delivering cloud compute clusters.

    Science.gov (United States)

    Afgan, Enis; Baker, Dannon; Coraor, Nate; Chapman, Brad; Nekrutenko, Anton; Taylor, James

    2010-12-21

    Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is "cloud computing", which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate "as is" use by experimental biologists. We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon's EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge.

  5. Data grids a new computational infrastructure for data-intensive science

    CERN Document Server

    Avery, P

    2002-01-01

    Twenty-first-century scientific and engineering enterprises are increasingly characterized by their geographic dispersion and their reliance on large data archives. These characteristics bring with them unique challenges. First, the increasing size and complexity of modern data collections require significant investments in information technologies to store, retrieve and analyse them. Second, the increased distribution of people and resources in these projects has made resource sharing and collaboration across significant geographic and organizational boundaries critical to their success. In this paper I explore how computing infrastructures based on data grids offer data-intensive enterprises a comprehensive, scalable framework for collaboration and resource sharing. A detailed example of a data grid framework is presented for a Large Hadron Collider experiment, where a hierarchical set of laboratory and university resources comprising petaflops of processing power and a multi- petabyte data archive must be ...

  6. A Cloud-based Infrastructure and Architecture for Environmental System Research

    Science.gov (United States)

    Wang, D.; Wei, Y.; Shankar, M.; Quigley, J.; Wilson, B. E.

    2016-12-01

    The present availability of high-capacity networks, low-cost computers and storage devices, and the widespread adoption of hardware virtualization and service-oriented architecture provide a great opportunity to enable data and computing infrastructure sharing between closely related research activities. By taking advantage of these approaches, along with the world-class high computing and data infrastructure located at Oak Ridge National Laboratory, a cloud-based infrastructure and architecture has been developed to efficiently deliver essential data and informatics service and utilities to the environmental system research community, and will provide unique capabilities that allows terrestrial ecosystem research projects to share their software utilities (tools), data and even data submission workflow in a straightforward fashion. The infrastructure will minimize large disruptions from current project-based data submission workflows for better acceptances from existing projects, since many ecosystem research projects already have their own requirements or preferences for data submission and collection. The infrastructure will eliminate scalability problems with current project silos by provide unified data services and infrastructure. The Infrastructure consists of two key components (1) a collection of configurable virtual computing environments and user management systems that expedite data submission and collection from environmental system research community, and (2) scalable data management services and system, originated and development by ORNL data centers.

  7. Structured Cloud Federation for Carrier and ISP Infrastructure

    OpenAIRE

    Xhagjika, Vamis; Vlassov, Vladimir; Molin, Magnus; Toma, Simona

    2014-01-01

    Cloud Computing in recent years has seen enhanced growth and extensive support by the research community and industry. The advent of cloud computing realized the concept of commodity computing, in which infrastructure (resources) can be allocated on demand giving the illusion of infinite resource availability. The state-of-art Carrier and ISP infrastructure technology is composed of tightly coupled software services with the underlying customized hardware architecture. The fast growth of clou...

  8. A Comprehensive and Cost-Effective Computer Infrastructure for K-12 Schools

    Science.gov (United States)

    Warren, G. P.; Seaton, J. M.

    1996-01-01

    Since 1993, NASA Langley Research Center has been developing and implementing a low-cost Internet connection model, including system architecture, training, and support, to provide Internet access for an entire network of computers. This infrastructure allows local area networks which exceed 50 machines per school to independently access the complete functionality of the Internet by connecting to a central site, using state-of-the-art commercial modem technology, through a single standard telephone line. By locating high-cost resources at this central site and sharing these resources and their costs among the school districts throughout a region, a practical, efficient, and affordable infrastructure for providing scale-able Internet connectivity has been developed. As the demand for faster Internet access grows, the model has a simple expansion path that eliminates the need to replace major system components and re-train personnel. Observations of optical Internet usage within an environment, particularly school classrooms, have shown that after an initial period of 'surfing,' the Internet traffic becomes repetitive. By automatically storing requested Internet information on a high-capacity networked disk drive at the local site (network based disk caching), then updating this information only when it changes, well over 80 percent of the Internet traffic that leaves a location can be eliminated by retrieving the information from the local disk cache.

  9. Security threats and their mitigation in infrastructure as a service

    Directory of Open Access Journals (Sweden)

    Bineet Kumar Joshi

    2016-09-01

    Full Text Available Cloud computing is a hot technology in the market. It permits user to use all IT resources as computing services on the basis of pay per use manner and access the applications remotely. Infrastructure as a service (IaaS is the basic requirement for all delivery models. Infrastructure as a service delivers all possible it resources (Network Components, Operating System, etc. as a service to users. From both users and providers point of view: integrity, privacy and other security issues in IaaS are the important concern. In this paper we studied in detail about the different types of security related issues in IaaS layer and methods to resolve them to maximize the performance and to maintain the highest level of security in IaaS.

  10. The computing and data infrastructure to interconnect EEE stations

    Science.gov (United States)

    Noferini, F.; EEE Collaboration

    2016-07-01

    The Extreme Energy Event (EEE) experiment is devoted to the search of high energy cosmic rays through a network of telescopes installed in about 50 high schools distributed throughout the Italian territory. This project requires a peculiar data management infrastructure to collect data registered in stations very far from each other and to allow a coordinated analysis. Such an infrastructure is realized at INFN-CNAF, which operates a Cloud facility based on the OpenStack opensource Cloud framework and provides Infrastructure as a Service (IaaS) for its users. In 2014 EEE started to use it for collecting, monitoring and reconstructing the data acquired in all the EEE stations. For the synchronization between the stations and the INFN-CNAF infrastructure we used BitTorrent Sync, a free peer-to-peer software designed to optimize data syncronization between distributed nodes. All data folders are syncronized with the central repository in real time to allow an immediate reconstruction of the data and their publication in a monitoring webpage. We present the architecture and the functionalities of this data management system that provides a flexible environment for the specific needs of the EEE project.

  11. The computing and data infrastructure to interconnect EEE stations

    Energy Technology Data Exchange (ETDEWEB)

    Noferini, F., E-mail: noferini@bo.infn.it [Museo Storico della Fisica e Centro Studi e Ricerche “Enrico Fermi”, Rome (Italy); INFN CNAF, Bologna (Italy)

    2016-07-11

    The Extreme Energy Event (EEE) experiment is devoted to the search of high energy cosmic rays through a network of telescopes installed in about 50 high schools distributed throughout the Italian territory. This project requires a peculiar data management infrastructure to collect data registered in stations very far from each other and to allow a coordinated analysis. Such an infrastructure is realized at INFN-CNAF, which operates a Cloud facility based on the OpenStack opensource Cloud framework and provides Infrastructure as a Service (IaaS) for its users. In 2014 EEE started to use it for collecting, monitoring and reconstructing the data acquired in all the EEE stations. For the synchronization between the stations and the INFN-CNAF infrastructure we used BitTorrent Sync, a free peer-to-peer software designed to optimize data syncronization between distributed nodes. All data folders are syncronized with the central repository in real time to allow an immediate reconstruction of the data and their publication in a monitoring webpage. We present the architecture and the functionalities of this data management system that provides a flexible environment for the specific needs of the EEE project.

  12. The computing and data infrastructure to interconnect EEE stations

    International Nuclear Information System (INIS)

    Noferini, F.

    2016-01-01

    The Extreme Energy Event (EEE) experiment is devoted to the search of high energy cosmic rays through a network of telescopes installed in about 50 high schools distributed throughout the Italian territory. This project requires a peculiar data management infrastructure to collect data registered in stations very far from each other and to allow a coordinated analysis. Such an infrastructure is realized at INFN-CNAF, which operates a Cloud facility based on the OpenStack opensource Cloud framework and provides Infrastructure as a Service (IaaS) for its users. In 2014 EEE started to use it for collecting, monitoring and reconstructing the data acquired in all the EEE stations. For the synchronization between the stations and the INFN-CNAF infrastructure we used BitTorrent Sync, a free peer-to-peer software designed to optimize data syncronization between distributed nodes. All data folders are syncronized with the central repository in real time to allow an immediate reconstruction of the data and their publication in a monitoring webpage. We present the architecture and the functionalities of this data management system that provides a flexible environment for the specific needs of the EEE project.

  13. Human Computer Music Performance

    OpenAIRE

    Dannenberg, Roger B.

    2012-01-01

    Human Computer Music Performance (HCMP) is the study of music performance by live human performers and real-time computer-based performers. One goal of HCMP is to create a highly autonomous artificial performer that can fill the role of a human, especially in a popular music setting. This will require advances in automated music listening and understanding, new representations for music, techniques for music synchronization, real-time human-computer communication, music generation, sound synt...

  14. National cyber defense high performance computing and analysis : concepts, planning and roadmap.

    Energy Technology Data Exchange (ETDEWEB)

    Hamlet, Jason R.; Keliiaa, Curtis M.

    2010-09-01

    There is a national cyber dilemma that threatens the very fabric of government, commercial and private use operations worldwide. Much is written about 'what' the problem is, and though the basis for this paper is an assessment of the problem space, we target the 'how' solution space of the wide-area national information infrastructure through the advancement of science, technology, evaluation and analysis with actionable results intended to produce a more secure national information infrastructure and a comprehensive national cyber defense capability. This cybersecurity High Performance Computing (HPC) analysis concepts, planning and roadmap activity was conducted as an assessment of cybersecurity analysis as a fertile area of research and investment for high value cybersecurity wide-area solutions. This report and a related SAND2010-4765 Assessment of Current Cybersecurity Practices in the Public Domain: Cyber Indications and Warnings Domain report are intended to provoke discussion throughout a broad audience about developing a cohesive HPC centric solution to wide-area cybersecurity problems.

  15. Helix Nebula: Enabling federation of existing data infrastructures and data services to an overarching cross-domain e-infrastructure

    Science.gov (United States)

    Lengert, Wolfgang; Farres, Jordi; Lanari, Riccardo; Casu, Francesco; Manunta, Michele; Lassalle-Balier, Gerard

    2014-05-01

    Helix Nebula has established a growing public private partnership of more than 30 commercial cloud providers, SMEs, and publicly funded research organisations and e-infrastructures. The Helix Nebula strategy is to establish a federated cloud service across Europe. Three high-profile flagships, sponsored by CERN (high energy physics), EMBL (life sciences) and ESA/DLR/CNES/CNR (earth science), have been deployed and extensively tested within this federated environment. The commitments behind these initial flagships have created a critical mass that attracts suppliers and users to the initiative, to work together towards an "Information as a Service" market place. Significant progress in implementing the following 4 programmatic goals (as outlined in the strategic Plan Ref.1) has been achieved: × Goal #1 Establish a Cloud Computing Infrastructure for the European Research Area (ERA) serving as a platform for innovation and evolution of the overall infrastructure. × Goal #2 Identify and adopt suitable policies for trust, security and privacy on a European-level can be provided by the European Cloud Computing framework and infrastructure. × Goal #3 Create a light-weight governance structure for the future European Cloud Computing Infrastructure that involves all the stakeholders and can evolve over time as the infrastructure, services and user-base grows. × Goal #4 Define a funding scheme involving the three stake-holder groups (service suppliers, users, EC and national funding agencies) into a Public-Private-Partnership model to implement a Cloud Computing Infrastructure that delivers a sustainable business environment adhering to European level policies. Now in 2014 a first version of this generic cross-domain e-infrastructure is ready to go into operations building on federation of European industry and contributors (data, tools, knowledge, ...). This presentation describes how Helix Nebula is being used in the domain of earth science focusing on geohazards. The

  16. E-Infrastructure Concertation Meeting

    CERN Multimedia

    Katarina Anthony

    2010-01-01

    The 8th e-Infrastructure Concertation Meeting was held in the Globe from 4 to 5 November to discuss the development of Europe’s distributed computing and storage resources.   Project leaders attend the E-Concertation Meeting at the Globe on 5 November 2010. © Corentin Chevalier E-Infrastructures have become an indispensable tool for scientific research, linking researchers to virtually unlimited e-resources like the grid. The recent e-Infrastructure Concertation Meeting brought together e-Science project leaders to discuss the development of this tool in the European context. The meeting was part of an ongoing initiative to develop a world-class e-infrastructure resource that would establish European leadership in e-Science. The e-Infrastructure Concertation Meeting was organised by the Commission Services (EC) with the support of e-ScienceTalk. “The Concertation meeting at CERN has been a great opportunity for e-ScienceTalk to meet many of the 38 new proje...

  17. Development and Operation of the D-Grid Infrastructure

    Science.gov (United States)

    Fieseler, Thomas; Gűrich, Wolfgang

    D-Grid is the German national grid initiative, granted by the German Federal Ministry of Education and Research. In this paper we present the Core D-Grid which acts as a condensation nucleus to build a production grid and the latest developments of the infrastructure. The main difference compared to other international grid initiatives is the support of three middleware systems, namely LCG/gLite, Globus, and UNICORE for compute resources. Storage resources are connected via SRM/dCache and OGSA-DAI. In contrast to homogeneous communities, the partners in Core D-Grid have different missions and backgrounds (computing centres, universities, research centres), providing heterogeneous hardware from single processors to high performance supercomputing systems with different operating systems. We present methods to integrate these resources and services for the DGrid infrastructure like a point of information, centralized user and virtual organization management, resource registration, software provision, and policies for the implementation (firewalls, certificates, user mapping).

  18. INFORMATION INFRASTRUCTURE OF THE EDUCATIONAL ENVIRONMENT WITH VIRTUAL MACHINE TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    Artem D. Beresnev

    2014-09-01

    Full Text Available Subject of research. Information infrastructure for the training environment with application of technology of virtual computers for small pedagogical systems (separate classes, author's courses is created and investigated. Research technique. The life cycle model of information infrastructure for small pedagogical systems with usage of virtual computers in ARIS methodology is constructed. The technique of information infrastructure formation with virtual computers on the basis of process approach is offered. The model of an event chain in combination with the environment chart is used as the basic model. For each function of the event chain the necessary set of means of information and program support is defined. Technique application is illustrated on the example of information infrastructure design for the educational environment taking into account specific character of small pedagogical systems. Advantages of the designed information infrastructure are: the maximum usage of open or free components; the usage of standard protocols (mainly, HTTP and HTTPS; the maximum portability (application servers can be started up on any of widespread operating systems; uniform interface to management of various virtualization platforms, possibility of inventory of contents of the virtual computer without its start, flexible inventory management of the virtual computer by means of adjusted chains of rules. Approbation. Approbation of obtained results was carried out on the basis of training center "Institute of Informatics and Computer Facilities" (Tallinn, Estonia. Technique application within the course "Computer and Software Usage" gave the possibility to get half as much the number of refusals for components of the information infrastructure demanding intervention of the technical specialist, and also the time for elimination of such malfunctions. Besides, the pupils who have got broader experience with computer and software, showed better results

  19. Use of VMware for providing cloud infrastructure for the Grid

    International Nuclear Information System (INIS)

    Long, Robin; Storey, Matthew

    2014-01-01

    The need to maximise computing resources whilst maintaining versatile setups leads to the need for flexible on demand facilities through the use of cloud computing. GridPP is currently investigating the role that Cloud Computing, in the form of Virtual Machines, can play in supporting Particle Physics analyses. As part of this research we look at the ability of VMware's ESXi hyper-visors[6] to provide such an infrastructure through the use of Virtual Machines (VMs); the advantages of such systems and their potential performance compared to physical environments.

  20. A Performance/Cost Evaluation for a GPU-Based Drug Discovery Application on Volunteer Computing

    Science.gov (United States)

    Guerrero, Ginés D.; Imbernón, Baldomero; García, José M.

    2014-01-01

    Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and, thus, the use of high performance computing (HPC) platforms is mandatory for the generation of useful biological knowledge. The latest generation of graphics processing units (GPUs) has democratized the use of HPC as they push desktop computers to cluster-level performance. Many applications within this field have been developed to leverage these powerful and low-cost architectures. However, these applications still need to scale to larger GPU-based systems to enable remarkable advances in the fields of healthcare, drug discovery, genome research, etc. The inclusion of GPUs in HPC systems exacerbates power and temperature issues, increasing the total cost of ownership (TCO). This paper explores the benefits of volunteer computing to scale bioinformatics applications as an alternative to own large GPU-based local infrastructures. We use as a benchmark a GPU-based drug discovery application called BINDSURF that their computational requirements go beyond a single desktop machine. Volunteer computing is presented as a cheap and valid HPC system for those bioinformatics applications that need to process huge amounts of data and where the response time is not a critical factor. PMID:25025055

  1. LEMON - LHC Era Monitoring for Large-Scale Infrastructures

    International Nuclear Information System (INIS)

    Babik, Marian; Hook, Nicholas; Lansdale, Thomas Hector; Lenkes, Daniel; Siket, Miroslav; Waldron, Denis; Fedorko, Ivan

    2011-01-01

    At the present time computer centres are facing a massive rise in virtualization and cloud computing as these solutions bring advantages to service providers and consolidate the computer centre resources. However, as a result the monitoring complexity is increasing. Computer centre management requires not only to monitor servers, network equipment and associated software but also to collect additional environment and facilities data (e.g. temperature, power consumption, cooling efficiency, etc.) to have also a good overview of the infrastructure performance. The LHC Era Monitoring (Lemon) system is addressing these requirements for a very large scale infrastructure. The Lemon agent that collects data on every client and forwards the samples to the central measurement repository provides a flexible interface that allows rapid development of new sensors. The system allows also to report on behalf of remote devices such as switches and power supplies. Online and historical data can be visualized via a web-based interface or retrieved via command-line tools. The Lemon Alarm System component can be used for notifying the operator about error situations. In this article, an overview of the Lemon monitoring is provided together with a description of the CERN LEMON production instance. No direct comparison is made with other monitoring tool.

  2. Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

    Energy Technology Data Exchange (ETDEWEB)

    Duque, Earl P.N. [J.M. Smith International, LLC, Rutherford, NJ (United States). DBA Intelligent Light; Whitlock, Brad J. [J.M. Smith International, LLC, Rutherford, NJ (United States). DBA Intelligent Light

    2017-08-25

    High performance computers have for many years been on a trajectory that gives them extraordinary compute power with the addition of more and more compute cores. At the same time, other system parameters such as the amount of memory per core and bandwidth to storage have remained constant or have barely increased. This creates an imbalance in the computer, giving it the ability to compute a lot of data that it cannot reasonably save out due to time and storage constraints. While technologies have been invented to mitigate this problem (burst buffers, etc.), software has been adapting to employ in situ libraries which perform data analysis and visualization on simulation data while it is still resident in memory. This avoids the need to ever have to pay the costs of writing many terabytes of data files. Instead, in situ enables the creation of more concentrated data products such as statistics, plots, and data extracts, which are all far smaller than the full-sized volume data. With the increasing popularity of in situ, multiple in situ infrastructures have been created, each with its own mechanism for integrating with a simulation. To make it easier to instrument a simulation with multiple in situ infrastructures and include custom analysis algorithms, this project created the SENSEI framework.

  3. Protective design of critical infrastructure with high performance concretes

    International Nuclear Information System (INIS)

    Riedel, W.; Nöldgen, M.; Stolz, A.; Roller, C.

    2012-01-01

    Conclusions: High performance concrete constructions will allow innovative design solutions for critical infrastructures. Validation of engineering methods can reside on large and model scale experiments conducted on conventional concrete structures. New consistent impact experiments show extreme protection potential for UHPC. Modern FEM with concrete models and explicit rebar can model HPC and UHPC penetration resistance. SDOF and TDOF approaches are valuable design tools on local and global level. Combination of at least 2 out of 3 design methods FEM – XDOF- EXP allow reliable prediction and efficient innovative designs

  4. Computational Environments and Analysis methods available on the NCI High Performance Computing (HPC) and High Performance Data (HPD) Platform

    Science.gov (United States)

    Evans, B. J. K.; Foster, C.; Minchin, S. A.; Pugh, T.; Lewis, A.; Wyborn, L. A.; Evans, B. J.; Uhlherr, A.

    2014-12-01

    The National Computational Infrastructure (NCI) has established a powerful in-situ computational environment to enable both high performance computing and data-intensive science across a wide spectrum of national environmental data collections - in particular climate, observational data and geoscientific assets. This paper examines 1) the computational environments that supports the modelling and data processing pipelines, 2) the analysis environments and methods to support data analysis, and 3) the progress in addressing harmonisation of the underlying data collections for future transdisciplinary research that enable accurate climate projections. NCI makes available 10+ PB major data collections from both the government and research sectors based on six themes: 1) weather, climate, and earth system science model simulations, 2) marine and earth observations, 3) geosciences, 4) terrestrial ecosystems, 5) water and hydrology, and 6) astronomy, social and biosciences. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. The data is largely sourced from NCI's partners (which include the custodians of many of the national scientific records), major research communities, and collaborating overseas organisations. The data is accessible within an integrated HPC-HPD environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large scale and high-bandwidth Lustre filesystems. This computational environment supports a catalogue of integrated reusable software and workflows from earth system and ecosystem modelling, weather research, satellite and other observed data processing and analysis. To enable transdisciplinary research on this scale, data needs to be harmonised so that researchers can readily apply techniques and software across the corpus of data available and not be constrained to work within artificial disciplinary boundaries. Future challenges will

  5. Data Center Consolidation: A Step towards Infrastructure Clouds

    Science.gov (United States)

    Winter, Markus

    Application service providers face enormous challenges and rising costs in managing and operating a growing number of heterogeneous system and computing landscapes. Limitations of traditional computing environments force IT decision-makers to reorganize computing resources within the data center, as continuous growth leads to an inefficient utilization of the underlying hardware infrastructure. This paper discusses a way for infrastructure providers to improve data center operations based on the findings of a case study on resource utilization of very large business applications and presents an outlook beyond server consolidation endeavors, transforming corporate data centers into compute clouds.

  6. Commissioning the CERN IT Agile Infrastructure with experiment workloads

    Science.gov (United States)

    Medrano Llamas, Ramón; Harald Barreiro Megino, Fernando; Kucharczyk, Katarzyna; Kamil Denis, Marek; Cinquilli, Mattia

    2014-06-01

    In order to ease the management of their infrastructure, most of the WLCG sites are adopting cloud based strategies. In the case of CERN, the Tier 0 of the WLCG, is completely restructuring the resource and configuration management of their computing center under the codename Agile Infrastructure. Its goal is to manage 15,000 Virtual Machines by means of an OpenStack middleware in order to unify all the resources in CERN's two datacenters: the one placed in Meyrin and the new on in Wigner, Hungary. During the commissioning of this infrastructure, CERN IT is offering an attractive amount of computing resources to the experiments (800 cores for ATLAS and CMS) through a private cloud interface. ATLAS and CMS have joined forces to exploit them by running stress tests and simulation workloads since November 2012. This work will describe the experience of the first deployments of the current experiment workloads on the CERN private cloud testbed. The paper is organized as follows: the first section will explain the integration of the experiment workload management systems (WMS) with the cloud resources. The second section will revisit the performance and stress testing performed with HammerCloud in order to evaluate and compare the suitability for the experiment workloads. The third section will go deeper into the dynamic provisioning techniques, such as the use of the cloud APIs directly by the WMS. The paper finishes with a review of the conclusions and the challenges ahead.

  7. Commissioning the CERN IT Agile Infrastructure with experiment workloads

    International Nuclear Information System (INIS)

    Llamas, Ramón Medrano; Megino, Fernando Harald Barreiro; Cinquilli, Mattia; Kucharczyk, Katarzyna; Denis, Marek Kamil

    2014-01-01

    In order to ease the management of their infrastructure, most of the WLCG sites are adopting cloud based strategies. In the case of CERN, the Tier 0 of the WLCG, is completely restructuring the resource and configuration management of their computing center under the codename Agile Infrastructure. Its goal is to manage 15,000 Virtual Machines by means of an OpenStack middleware in order to unify all the resources in CERN's two datacenters: the one placed in Meyrin and the new on in Wigner, Hungary. During the commissioning of this infrastructure, CERN IT is offering an attractive amount of computing resources to the experiments (800 cores for ATLAS and CMS) through a private cloud interface. ATLAS and CMS have joined forces to exploit them by running stress tests and simulation workloads since November 2012. This work will describe the experience of the first deployments of the current experiment workloads on the CERN private cloud testbed. The paper is organized as follows: the first section will explain the integration of the experiment workload management systems (WMS) with the cloud resources. The second section will revisit the performance and stress testing performed with HammerCloud in order to evaluate and compare the suitability for the experiment workloads. The third section will go deeper into the dynamic provisioning techniques, such as the use of the cloud APIs directly by the WMS. The paper finishes with a review of the conclusions and the challenges ahead.

  8. IMPLEMENTATION OF CLOUD COMPUTING AS A COMPONENT OF THE UNIVERSITY IT INFRASTRUCTURE

    Directory of Open Access Journals (Sweden)

    Vasyl P. Oleksyuk

    2014-05-01

    Full Text Available The article investigated the concept of IT infrastructure of higher educational institution. The article described models of deploying of cloud technologies in IT infrastructure. The hybrid model is most recent for higher educational institution. The unified authentication is an important component of IT infrastructure. The author suggests the public (Google Apps, Office 365 and private (Cloudstack, Eucalyptus, OpenStack cloud platforms to deploying in IT infrastructure of higher educational institution. Open source platform for organizing enterprise clouds were analyzed by the author. The article describes the experience of the deployment enterprise cloud in IT infrastructure of Department of Physics and Mathematics of Ternopil V. Hnatyuk National Pedagogical University.

  9. Computer-Related Task Performance

    DEFF Research Database (Denmark)

    Longstreet, Phil; Xiao, Xiao; Sarker, Saonee

    2016-01-01

    The existing information system (IS) literature has acknowledged computer self-efficacy (CSE) as an important factor contributing to enhancements in computer-related task performance. However, the empirical results of CSE on performance have not always been consistent, and increasing an individual......'s CSE is often a cumbersome process. Thus, we introduce the theoretical concept of self-prophecy (SP) and examine how this social influence strategy can be used to improve computer-related task performance. Two experiments are conducted to examine the influence of SP on task performance. Results show...... that SP and CSE interact to influence performance. Implications are then discussed in terms of organizations’ ability to increase performance....

  10. HwPMI: An Extensible Performance Monitoring Infrastructure for Improving Hardware Design and Productivity on FPGAs

    Directory of Open Access Journals (Sweden)

    Andrew G. Schmidt

    2012-01-01

    Full Text Available Designing hardware cores for FPGAs can quickly become a complicated task, difficult even for experienced engineers. With the addition of more sophisticated development tools and maturing high-level language-to-gates techniques, designs can be rapidly assembled; however, when the design is evaluated on the FPGA, the performance may not be what was expected. Therefore, an engineer may need to augment the design to include performance monitors to better understand the bottlenecks in the system or to aid in the debugging of the design. Unfortunately, identifying what to monitor and adding the infrastructure to retrieve the monitored data can be a challenging and time-consuming task. Our work alleviates this effort. We present the Hardware Performance Monitoring Infrastructure (HwPMI, which includes a collection of software tools and hardware cores that can be used to profile the current design, recommend and insert performance monitors directly into the HDL or netlist, and retrieve the monitored data with minimal invasiveness to the design. Three applications are used to demonstrate and evaluate HwPMI’s capabilities. The results are highly encouraging as the infrastructure adds numerous capabilities while requiring minimal effort by the designer and low resource overhead to the existing design.

  11. Open | SpeedShop: An Open Source Infrastructure for Parallel Performance Analysis

    Directory of Open Access Journals (Sweden)

    Martin Schulz

    2008-01-01

    Full Text Available Over the last decades a large number of performance tools has been developed to analyze and optimize high performance applications. Their acceptance by end users, however, has been slow: each tool alone is often limited in scope and comes with widely varying interfaces and workflow constraints, requiring different changes in the often complex build and execution infrastructure of the target application. We started the Open | SpeedShop project about 3 years ago to overcome these limitations and provide efficient, easy to apply, and integrated performance analysis for parallel systems. Open | SpeedShop has two different faces: it provides an interoperable tool set covering the most common analysis steps as well as a comprehensive plugin infrastructure for building new tools. In both cases, the tools can be deployed to large scale parallel applications using DPCL/Dyninst for distributed binary instrumentation. Further, all tools developed within or on top of Open | SpeedShop are accessible through multiple fully equivalent interfaces including an easy-to-use GUI as well as an interactive command line interface reducing the usage threshold for those tools.

  12. Exploring Infiniband Hardware Virtualization in OpenNebula towards Efficient High-Performance Computing

    Energy Technology Data Exchange (ETDEWEB)

    Pais Pitta de Lacerda Ruivo, Tiago [IIT, Chicago; Bernabeu Altayo, Gerard [Fermilab; Garzoglio, Gabriele [Fermilab; Timm, Steven [Fermilab; Kim, Hyun-Woo [Fermilab; Noh, Seo-Young [KISTI, Daejeon; Raicu, Ioan [IIT, Chicago

    2014-11-11

    has been widely accepted that software virtualization has a big negative impact on high-performance computing (HPC) application performance. This work explores the potential use of Infiniband hardware virtualization in an OpenNebula cloud towards the efficient support of MPI-based workloads. We have implemented, deployed, and tested an Infiniband network on the FermiCloud private Infrastructure-as-a-Service (IaaS) cloud. To avoid software virtualization towards minimizing the virtualization overhead, we employed a technique called Single Root Input/Output Virtualization (SRIOV). Our solution spanned modifications to the Linux’s Hypervisor as well as the OpenNebula manager. We evaluated the performance of the hardware virtualization on up to 56 virtual machines connected by up to 8 DDR Infiniband network links, with micro-benchmarks (latency and bandwidth) as well as w a MPI-intensive application (the HPL Linpack benchmark).

  13. Development of multi-functional streetscape green infrastructure using a performance index approach

    International Nuclear Information System (INIS)

    Tiwary, A.; Williams, I.D.; Heidrich, O.; Namdeo, A.; Bandaru, V.; Calfapietra, C.

    2016-01-01

    This paper presents a performance evaluation framework for streetscape vegetation. A performance index (PI) is conceived using the following seven traits, specific to the street environments – Pollution Flux Potential (PFP), Carbon Sequestration Potential (CSP), Thermal Comfort Potential (TCP), Noise Attenuation Potential (NAP), Biomass Energy Potential (BEP), Environmental Stress Tolerance (EST) and Crown Projection Factor (CPF). Its application is demonstrated through a case study using fifteen street vegetation species from the UK, utilising a combination of direct field measurements and inventoried literature data. Our results indicate greater preference to small-to-medium size trees and evergreen shrubs over larger trees for streetscaping. The proposed PI approach can be potentially applied two-fold: one, for evaluation of the performance of the existing street vegetation, facilitating the prospects for further improving them through management strategies and better species selection; two, for planning new streetscapes and multi-functional biomass as part of extending the green urban infrastructure. - Highlights: • A performance evaluation framework for streetscape vegetation is presented. • Seven traits, relevant to street vegetation, are included in a performance index (PI). • The PI approach is applied to quantify and rank fifteen street vegetation species. • Medium size trees and evergreen shrubs are found more favourable for streetscapes. • The PI offers a metric for developing sustainable streetscape green infrastructure. - A performance index is developed and applied to fifteen vegetation species indicating greater preference to medium size trees and evergreen shrubs for streetscaping.

  14. A Performance/Cost Evaluation for a GPU-Based Drug Discovery Application on Volunteer Computing

    Directory of Open Access Journals (Sweden)

    Ginés D. Guerrero

    2014-01-01

    Full Text Available Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and, thus, the use of high performance computing (HPC platforms is mandatory for the generation of useful biological knowledge. The latest generation of graphics processing units (GPUs has democratized the use of HPC as they push desktop computers to cluster-level performance. Many applications within this field have been developed to leverage these powerful and low-cost architectures. However, these applications still need to scale to larger GPU-based systems to enable remarkable advances in the fields of healthcare, drug discovery, genome research, etc. The inclusion of GPUs in HPC systems exacerbates power and temperature issues, increasing the total cost of ownership (TCO. This paper explores the benefits of volunteer computing to scale bioinformatics applications as an alternative to own large GPU-based local infrastructures. We use as a benchmark a GPU-based drug discovery application called BINDSURF that their computational requirements go beyond a single desktop machine. Volunteer computing is presented as a cheap and valid HPC system for those bioinformatics applications that need to process huge amounts of data and where the response time is not a critical factor.

  15. Data that warms: Waste heat, infrastructural convergence and the computation traffic commodity

    Directory of Open Access Journals (Sweden)

    Julia Velkova

    2016-12-01

    Full Text Available This article explores the ways in which data centre operators are currently reconfiguring the systems of energy and heat supply in European capitals, replacing conventional forms of heating with data-driven heat production, and becoming important energy suppliers. Taking as an empirical object the heat generated from server halls, the article traces the expanding phenomenon of ‘waste heat recycling’ and charts the ways in which data centre operators in Stockholm and Paris direct waste heat through metropolitan district heating systems and urban homes, and valorise it. Drawing on new materialisms, infrastructure studies and classical theory of production and destruction of value in capitalism, the article outlines two modes in which this process happens, namely infrastructural convergence and decentralisation of the data centre. These modes arguably help data centre operators convert big data from a source of value online into a raw material that needs to flow in the network irrespective of meaning. In this conversion process, the article argues, a new commodity is in a process of formation, that of computation traffic. Altogether data-driven heat production is suggested to raise the importance of certain data processing nodes in Northern Europe, simultaneously intervening in the global politics of access, while neutralising external criticism towards big data by making urban life literally dependent on power from data streams.

  16. High Performance Computing Facility Operational Assessment, FY 2010 Oak Ridge Leadership Computing Facility

    Energy Technology Data Exchange (ETDEWEB)

    Bland, Arthur S Buddy [ORNL; Hack, James J [ORNL; Baker, Ann E [ORNL; Barker, Ashley D [ORNL; Boudwin, Kathlyn J. [ORNL; Kendall, Ricky A [ORNL; Messer, Bronson [ORNL; Rogers, James H [ORNL; Shipman, Galen M [ORNL; White, Julia C [ORNL

    2010-08-01

    Oak Ridge National Laboratory's (ORNL's) Cray XT5 supercomputer, Jaguar, kicked off the era of petascale scientific computing in 2008 with applications that sustained more than a thousand trillion floating point calculations per second - or 1 petaflop. Jaguar continues to grow even more powerful as it helps researchers broaden the boundaries of knowledge in virtually every domain of computational science, including weather and climate, nuclear energy, geosciences, combustion, bioenergy, fusion, and materials science. Their insights promise to broaden our knowledge in areas that are vitally important to the Department of Energy (DOE) and the nation as a whole, particularly energy assurance and climate change. The science of the 21st century, however, will demand further revolutions in computing, supercomputers capable of a million trillion calculations a second - 1 exaflop - and beyond. These systems will allow investigators to continue attacking global challenges through modeling and simulation and to unravel longstanding scientific questions. Creating such systems will also require new approaches to daunting challenges. High-performance systems of the future will need to be codesigned for scientific and engineering applications with best-in-class communications networks and data-management infrastructures and teams of skilled researchers able to take full advantage of these new resources. The Oak Ridge Leadership Computing Facility (OLCF) provides the nation's most powerful open resource for capability computing, with a sustainable path that will maintain and extend national leadership for DOE's Office of Science (SC). The OLCF has engaged a world-class team to support petascale science and to take a dramatic step forward, fielding new capabilities for high-end science. This report highlights the successful delivery and operation of a petascale system and shows how the OLCF fosters application development teams, developing cutting-edge tools

  17. Electricity Infrastructure Operations Center (EIOC)

    Data.gov (United States)

    Federal Laboratory Consortium — The Electricity Infrastructure Operations Center (EIOC) at PNNL brings together industry-leading software, real-time grid data, and advanced computation into a fully...

  18. Stochastic Processes and Queueing Theory used in Cloud Computer Performance Simulations

    Directory of Open Access Journals (Sweden)

    Florin-Catalin ENACHE

    2015-10-01

    Full Text Available The growing character of the cloud business has manifested exponentially in the last 5 years. The capacity managers need to concentrate on a practical way to simulate the random demands a cloud infrastructure could face, even if there are not too many mathematical tools to simulate such demands.This paper presents an introduction into the most important stochastic processes and queueing theory concepts used for modeling computer performance. Moreover, it shows the cases where such concepts are applicable and when not, using clear programming examples on how to simulate a queue, and how to use and validate a simulation, when there are no mathematical concepts to back it up.

  19. The National Information Infrastructure: Agenda for Action.

    Science.gov (United States)

    Department of Commerce, Washington, DC. Information Infrastructure Task Force.

    The National Information Infrastructure (NII) is planned as a web of communications networks, computers, databases, and consumer electronics that will put vast amounts of information at the users' fingertips. Private sector firms are beginning to develop this infrastructure, but essential roles remain for the Federal Government. The National…

  20. Improving the Eco-Efficiency of High Performance Computing Clusters Using EECluster

    Directory of Open Access Journals (Sweden)

    Alberto Cocaña-Fernández

    2016-03-01

    Full Text Available As data and supercomputing centres increase their performance to improve service quality and target more ambitious challenges every day, their carbon footprint also continues to grow, and has already reached the magnitude of the aviation industry. Also, high power consumptions are building up to a remarkable bottleneck for the expansion of these infrastructures in economic terms due to the unavailability of sufficient energy sources. A substantial part of the problem is caused by current energy consumptions of High Performance Computing (HPC clusters. To alleviate this situation, we present in this work EECluster, a tool that integrates with multiple open-source Resource Management Systems to significantly reduce the carbon footprint of clusters by improving their energy efficiency. EECluster implements a dynamic power management mechanism based on Computational Intelligence techniques by learning a set of rules through multi-criteria evolutionary algorithms. This approach enables cluster operators to find the optimal balance between a reduction in the cluster energy consumptions, service quality, and number of reconfigurations. Experimental studies using both synthetic and actual workloads from a real world cluster support the adoption of this tool to reduce the carbon footprint of HPC clusters.

  1. CERN printing infrastructure

    International Nuclear Information System (INIS)

    Otto, R; Sucik, J

    2008-01-01

    For many years CERN had a very sophisticated print server infrastructure [13] which supported several different protocols (AppleTalk, IPX and TCP/IP) and many different printing standards. Today's situation differs a lot: we have a much more homogenous network infrastructure, where TCP/IP is used everywhere and we have less printer models, which almost all work using current standards (i.e. they all provide PostScript drivers). This change gave us the possibility to review the printing architecture aiming at simplifying the infrastructure in order to achieve full automation of the service. The new infrastructure offers both: LPD service exposing print queues to Linux and Mac OS X computers and native printing for Windows based clients. The printer driver distribution is automatic and native on Windows and automated by custom mechanisms on Linux, where the appropriate Foomatic drivers are configured. Also the process of printer registration and queue creation is completely automated following the printer registration in the network database. At the end of 2006 we have moved all (∼1200) CERN printers and all users' connections at CERN to the new service. This paper will describe the new architecture and summarize the process of migration

  2. An infrastructure with a unified control plane to integrate IP into optical metro networks to provide flexible and intelligent bandwidth on demand for cloud computing

    Science.gov (United States)

    Yang, Wei; Hall, Trevor

    2012-12-01

    The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users and the nature of the Internet traffic will undertake a fundamental transformation. Consequently, the current Internet will no longer suffice for serving cloud traffic in metro areas. This work proposes an infrastructure with a unified control plane that integrates simple packet aggregation technology with optical express through the interoperation between IP routers and electrical traffic controllers in optical metro networks. The proposed infrastructure provides flexible, intelligent, and eco-friendly bandwidth on demand for cloud computing in metro areas.

  3. High-performance computing using FPGAs

    CERN Document Server

    Benkrid, Khaled

    2013-01-01

    This book is concerned with the emerging field of High Performance Reconfigurable Computing (HPRC), which aims to harness the high performance and relative low power of reconfigurable hardware–in the form Field Programmable Gate Arrays (FPGAs)–in High Performance Computing (HPC) applications. It presents the latest developments in this field from applications, architecture, and tools and methodologies points of view. We hope that this work will form a reference for existing researchers in the field, and entice new researchers and developers to join the HPRC community.  The book includes:  Thirteen application chapters which present the most important application areas tackled by high performance reconfigurable computers, namely: financial computing, bioinformatics and computational biology, data search and processing, stencil computation e.g. computational fluid dynamics and seismic modeling, cryptanalysis, astronomical N-body simulation, and circuit simulation.     Seven architecture chapters which...

  4. DLVM: A modern compiler infrastructure for deep learning systems

    OpenAIRE

    Wei, Richard; Schwartz, Lane; Adve, Vikram

    2017-01-01

    Deep learning software demands reliability and performance. However, many of the existing deep learning frameworks are software libraries that act as an unsafe DSL in Python and a computation graph interpreter. We present DLVM, a design and implementation of a compiler infrastructure with a linear algebra intermediate representation, algorithmic differentiation by adjoint code generation, domain-specific optimizations and a code generator targeting GPU via LLVM. Designed as a modern compiler ...

  5. Handbook on Securing Cyber-Physical Critical Infrastructure

    CERN Document Server

    Das, Sajal K; Zhang, Nan

    2012-01-01

    The worldwide reach of the Internet allows malicious cyber criminals to coordinate and launch attacks on both cyber and cyber-physical infrastructure from anywhere in the world. This purpose of this handbook is to introduce the theoretical foundations and practical solution techniques for securing critical cyber and physical infrastructures as well as their underlying computing and communication architectures and systems. Examples of such infrastructures include utility networks (e.g., electrical power grids), ground transportation systems (automotives, roads, bridges and tunnels), airports a

  6. EV Charging Infrastructure Roadmap

    International Nuclear Information System (INIS)

    Karner, Donald; Garetson, Thomas; Francfort, Jim

    2016-01-01

    As highlighted in the U.S. Department of Energy's EV Everywhere Grand Challenge, vehicle technology is advancing toward an objective to ''... produce plug-in electric vehicles that are as affordable and convenient for the average American family as today's gasoline-powered vehicles ...'' [1] by developing more efficient drivetrains, greater battery energy storage per dollar, and lighter-weight vehicle components and construction. With this technology advancement and improved vehicle performance, the objective for charging infrastructure is to promote vehicle adoption and maximize the number of electric miles driven. The EV Everywhere Charging Infrastructure Roadmap (hereafter referred to as Roadmap) looks forward and assumes that the technical challenges and vehicle performance improvements set forth in the EV Everywhere Grand Challenge will be met. The Roadmap identifies and prioritizes deployment of charging infrastructure in support of this charging infrastructure objective for the EV Everywhere Grand Challenge

  7. Monitoring the US ATLAS Network Infrastructure with perfSONAR-PS

    CERN Document Server

    McKee, S; The ATLAS collaboration; Laurens, P; Severini, H; Wlodek, T; Wolff, S; Zurawski, J

    2012-01-01

    We will present our motivations for deploying and using the perfSONAR-PS Performance Toolkit at ATLAS sites in the United States and describe our experience in using it. This software creates a dedicated monitoring server, capable of collecting and performing a wide range of passive and active network measurements. Each independent instance is managed locally, but able to federate on a global scale; enabling a full view of the network infrastructure that spans domain boundaries. This information, available through web service interfaces, can easily be retrieved to create customized applications. USATLAS has developed a centralized “dashboard” offering network administrators, users, and decision makers the ability to see the performance of the network at a glance. The dashboard framework includes the ability to notify users (alarm) when problems are found, thus allowing rapid response to potential problems and making perfSONAR-PS crucial to the operation of our distributed computing infrastructure.

  8. A scalable infrastructure for CMS data analysis based on OpenStack Cloud and Gluster file system

    Science.gov (United States)

    Toor, S.; Osmani, L.; Eerola, P.; Kraemer, O.; Lindén, T.; Tarkoma, S.; White, J.

    2014-06-01

    The challenge of providing a resilient and scalable computational and data management solution for massive scale research environments requires continuous exploration of new technologies and techniques. In this project the aim has been to design a scalable and resilient infrastructure for CERN HEP data analysis. The infrastructure is based on OpenStack components for structuring a private Cloud with the Gluster File System. We integrate the state-of-the-art Cloud technologies with the traditional Grid middleware infrastructure. Our test results show that the adopted approach provides a scalable and resilient solution for managing resources without compromising on performance and high availability.

  9. A scalable infrastructure for CMS data analysis based on OpenStack Cloud and Gluster file system

    International Nuclear Information System (INIS)

    Toor, S; Eerola, P; Kraemer, O; Lindén, T; Osmani, L; Tarkoma, S; White, J

    2014-01-01

    The challenge of providing a resilient and scalable computational and data management solution for massive scale research environments requires continuous exploration of new technologies and techniques. In this project the aim has been to design a scalable and resilient infrastructure for CERN HEP data analysis. The infrastructure is based on OpenStack components for structuring a private Cloud with the Gluster File System. We integrate the state-of-the-art Cloud technologies with the traditional Grid middleware infrastructure. Our test results show that the adopted approach provides a scalable and resilient solution for managing resources without compromising on performance and high availability.

  10. Computational Biology and High Performance Computing 2000

    Energy Technology Data Exchange (ETDEWEB)

    Simon, Horst D.; Zorn, Manfred D.; Spengler, Sylvia J.; Shoichet, Brian K.; Stewart, Craig; Dubchak, Inna L.; Arkin, Adam P.

    2000-10-19

    The pace of extraordinary advances in molecular biology has accelerated in the past decade due in large part to discoveries coming from genome projects on human and model organisms. The advances in the genome project so far, happening well ahead of schedule and under budget, have exceeded any dreams by its protagonists, let alone formal expectations. Biologists expect the next phase of the genome project to be even more startling in terms of dramatic breakthroughs in our understanding of human biology, the biology of health and of disease. Only today can biologists begin to envision the necessary experimental, computational and theoretical steps necessary to exploit genome sequence information for its medical impact, its contribution to biotechnology and economic competitiveness, and its ultimate contribution to environmental quality. High performance computing has become one of the critical enabling technologies, which will help to translate this vision of future advances in biology into reality. Biologists are increasingly becoming aware of the potential of high performance computing. The goal of this tutorial is to introduce the exciting new developments in computational biology and genomics to the high performance computing community.

  11. Enhancing Trusted Cloud Computing Platform for Infrastructure as a Service

    Directory of Open Access Journals (Sweden)

    KIM, H.

    2017-02-01

    Full Text Available The characteristics of cloud computing including on-demand self-service, resource pooling, and rapid elasticity have made it grow in popularity. However, security concerns still obstruct widespread adoption of cloud computing in the industry. Especially, security risks related to virtual machine make cloud users worry about exposure of their private data in IaaS environment. In this paper, we propose an enhanced trusted cloud computing platform to provide confidentiality and integrity of the user's data and computation. The presented platform provides secure and efficient virtual machine management protocols not only to protect against eavesdropping and tampering during transfer but also to guarantee the virtual machine is hosted only on the trusted cloud nodes against inside attackers. The protocols utilize both symmetric key operations and public key operations together with efficient node authentication model, hence both the computational cost for cryptographic operations and the communication steps are significantly reduced. As a result, the simulation shows the performance of the proposed platform is approximately doubled compared to the previous platforms. The proposed platform eliminates cloud users' worry above by providing confidentiality and integrity of their private data with better performance, and thus it contributes to wider industry adoption of cloud computing.

  12. OOI CyberInfrastructure - Next Generation Oceanographic Research

    Science.gov (United States)

    Farcas, C.; Fox, P.; Arrott, M.; Farcas, E.; Klacansky, I.; Krueger, I.; Meisinger, M.; Orcutt, J.

    2008-12-01

    Software has become a key enabling technology for scientific discovery, observation, modeling, and exploitation of natural phenomena. New value emerges from the integration of individual subsystems into networked federations of capabilities exposed to the scientific community. Such data-intensive interoperability networks are crucial for future scientific collaborative research, as they open up new ways of fusing data from different sources and across various domains, and analysis on wide geographic areas. The recently established NSF OOI program, through its CyberInfrastructure component addresses this challenge by providing broad access from sensor networks for data acquisition up to computational grids for massive computations and binding infrastructure facilitating policy management and governance of the emerging system-of-scientific-systems. We provide insight into the integration core of this effort, namely, a hierarchic service-oriented architecture for a robust, performant, and maintainable implementation. We first discuss the relationship between data management and CI crosscutting concerns such as identity management, policy and governance, which define the organizational contexts for data access and usage. Next, we detail critical services including data ingestion, transformation, preservation, inventory, and presentation. To address interoperability issues between data represented in various formats we employ a semantic framework derived from the Earth System Grid technology, a canonical representation for scientific data based on DAP/OPeNDAP, and related data publishers such as ERDDAP. Finally, we briefly present the underlying transport based on a messaging infrastructure over the AMQP protocol, and the preservation based on a distributed file system through SDSC iRODS.

  13. Transport Infrastructure and Economic Growth: Spatial Effects

    Directory of Open Access Journals (Sweden)

    Artyom Gennadyevich Isaev

    2015-09-01

    Full Text Available The author specifies an empirical framework of neoclassical growth model in order to examine impact of transport infrastructure on economic growth in Russian regions during period of 2000-2013. Two different effects of infrastructure are considered. First, infrastructure is viewed as part of region’s own production function. Second, infrastructure generates spillover effect on adjacent regions’ economic performance which can be negative or positive. Results imply that road infrastructure has a positive influence on regional growth, but sign of railroad infrastructure coefficient depends on whether or not congestion effect is considered. Negative spillover effect is shown to exist in the case of road infrastructure. This apparently means that rapid road infrastructure development in some regions moves mobile factors of production away from adjacent regions retarding their economic development. The spillover effect of railroad infrastructure is significant and negative again only if congestion effect is considered. The results of estimation for the Far East and Baikal Regions separately demonstrate no significant effect of both types of infrastructure for economic performance and negative spillover effect of road infrastructure

  14. EV Charging Infrastructure Roadmap

    Energy Technology Data Exchange (ETDEWEB)

    Karner, Donald [Electric Transportation Inc., Rogers, AR (United States); Garetson, Thomas [Electric Transportation Inc., Rogers, AR (United States); Francfort, Jim [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-08-01

    As highlighted in the U.S. Department of Energy’s EV Everywhere Grand Challenge, vehicle technology is advancing toward an objective to “… produce plug-in electric vehicles that are as affordable and convenient for the average American family as today’s gasoline-powered vehicles …” [1] by developing more efficient drivetrains, greater battery energy storage per dollar, and lighter-weight vehicle components and construction. With this technology advancement and improved vehicle performance, the objective for charging infrastructure is to promote vehicle adoption and maximize the number of electric miles driven. The EV Everywhere Charging Infrastructure Roadmap (hereafter referred to as Roadmap) looks forward and assumes that the technical challenges and vehicle performance improvements set forth in the EV Everywhere Grand Challenge will be met. The Roadmap identifies and prioritizes deployment of charging infrastructure in support of this charging infrastructure objective for the EV Everywhere Grand Challenge

  15. Coordinated Use of Heterogeneous Infrastructures for Scientific Computing at CIEMAT by means of Grid Technologies; Aprovechamiento Coordinado de las Infraestructuras Heterogeneas para Calculo Cientifico Participadas por el CIEMAT por medio de Tecnologias Grid

    Energy Technology Data Exchange (ETDEWEB)

    Rubio-Montero, A. J.

    2008-08-06

    Usually, research data centres maintain platforms from a wide range of architectures to cover the computational needs of their scientists. These centres are also frequently involved in diverse national and international Grid projects. Besides, it is very difficult to achieve a complete and efficient utilization of these recourses, due to the heterogeneity in their hardware and software configurations and their unequal use along the time. This report offers a solution to the problem of enabling a simultaneous and coordinated access to the variety of computing infrastructures and platforms available in great Research Organisms such as CIEMAT. For this purpose, new Grid technologies have been deployed in order to facilitate a common interface which enables the final user to access the internal and external resources. The previous computing infrastructure has not been modified and the independence on its administration has been guaranteed. For a sake of comparison, a feasibility study has been performed with the execution of the Drift Kinetic Equation solver (Dikes) tool, a high throughput scientific application used in the TJ-II Flexible Heliac at National Fusion Laboratory. (Author) 35 refs.

  16. A multi-infrastructure gateway for virtual drug screening

    NARCIS (Netherlands)

    Jaghoori, Mohammad Mahdi; van Altena, Allard J.; Bleijlevens, Boris; Ramezani, Sara; Font, Juan Luis; Olabarriaga, Silvia D.

    2015-01-01

    In computer-aided drug design, software tools are used to narrow down possible drug candidates, thereby reducing the amount of expensive in vitro research, by a process called virtual screening. This process includes large computations that require advanced computing infrastructure; however, using

  17. CERN printing infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Otto, R; Sucik, J [CERN, Geneva (Switzerland)], E-mail: Rafal.Otto@cern.ch, E-mail: Juraj.Sucik@cern.ch

    2008-07-15

    For many years CERN had a very sophisticated print server infrastructure [13] which supported several different protocols (AppleTalk, IPX and TCP/IP) and many different printing standards. Today's situation differs a lot: we have a much more homogenous network infrastructure, where TCP/IP is used everywhere and we have less printer models, which almost all work using current standards (i.e. they all provide PostScript drivers). This change gave us the possibility to review the printing architecture aiming at simplifying the infrastructure in order to achieve full automation of the service. The new infrastructure offers both: LPD service exposing print queues to Linux and Mac OS X computers and native printing for Windows based clients. The printer driver distribution is automatic and native on Windows and automated by custom mechanisms on Linux, where the appropriate Foomatic drivers are configured. Also the process of printer registration and queue creation is completely automated following the printer registration in the network database. At the end of 2006 we have moved all ({approx}1200) CERN printers and all users' connections at CERN to the new service. This paper will describe the new architecture and summarize the process of migration.

  18. High Performance Computing in Science and Engineering '15 : Transactions of the High Performance Computing Center

    CERN Document Server

    Kröner, Dietmar; Resch, Michael

    2016-01-01

    This book presents the state-of-the-art in supercomputer simulation. It includes the latest findings from leading researchers using systems from the High Performance Computing Center Stuttgart (HLRS) in 2015. The reports cover all fields of computational science and engineering ranging from CFD to computational physics and from chemistry to computer science with a special emphasis on industrially relevant applications. Presenting findings of one of Europe’s leading systems, this volume covers a wide variety of applications that deliver a high level of sustained performance. The book covers the main methods in high-performance computing. Its outstanding results in achieving the best performance for production codes are of particular interest for both scientists and engineers. The book comes with a wealth of color illustrations and tables of results.

  19. High Performance Computing in Science and Engineering '17 : Transactions of the High Performance Computing Center

    CERN Document Server

    Kröner, Dietmar; Resch, Michael; HLRS 2017

    2018-01-01

    This book presents the state-of-the-art in supercomputer simulation. It includes the latest findings from leading researchers using systems from the High Performance Computing Center Stuttgart (HLRS) in 2017. The reports cover all fields of computational science and engineering ranging from CFD to computational physics and from chemistry to computer science with a special emphasis on industrially relevant applications. Presenting findings of one of Europe’s leading systems, this volume covers a wide variety of applications that deliver a high level of sustained performance.The book covers the main methods in high-performance computing. Its outstanding results in achieving the best performance for production codes are of particular interest for both scientists and engineers. The book comes with a wealth of color illustrations and tables of results.

  20. People at risk - nexus critical infrastructure and society

    Science.gov (United States)

    Heiser, Micha; Thaler, Thomas; Fuchs, Sven

    2016-04-01

    Strategic infrastructure networks include the highly complex and interconnected systems that are so vital to a city or state that any sudden disruption can result in debilitating impacts on human life, the economy and the society as a whole. Recently, various studies have applied complex network-based models to study the performance and vulnerability of infrastructure systems under various types of attacks and hazards - a major part of them is, particularly after the 9/11 incident, related to terrorism attacks. Here, vulnerability is generally defined as the performance drop of an infrastructure system under a given disruptive event. The performance can be measured by different metrics, which correspond to various levels of resilience. In this paper, we will address vulnerability and exposure of critical infrastructure in the Eastern Alps. The Federal State Tyrol is an international transport route and an essential component of the north-south transport connectivity in Europe. Any interruption of the transport flow leads to incommensurable consequences in terms of indirect losses, since the system does not feature redundant elements at comparable economic efficiency. Natural hazard processes such as floods, debris flows, rock falls and avalanches, endanger this infrastructure line, such as large flood events in 2005 or 2012, rock falls 2014, which had strong impacts to the critical infrastructure, such as disruption of the railway lines (in 2005 and 2012), highways and motorways (in 2014). The aim of this paper is to present how critical infrastructures as well as communities and societies are vulnerable and can be resilient against natural hazard risks and the relative cascading effects to different compartments (industrial, infrastructural, societal, institutional, cultural, etc.), which is the dominant by the type of hazard (avalanches, torrential flooding, debris flow, rock falls). Specific themes will be addressed in various case studies to allow cross

  1. Service software engineering for innovative infrastructure for global financial services

    OpenAIRE

    MAAD , Soha; MCCARTHY , James B.; GARBAYA , Samir; Beynon , Meurig; Nagarajan , Rajagopal

    2010-01-01

    International audience; The recent financial crisis motivates our re-thinking of the engineering principles for service software and infrastructures intended to create business value in vital sectors. Existing monolithic, inwarddirected, cost insensitive and highly regulated technical and organizational infrastructures for financial services make it difficult for the domain to benefit from opportunities offered by new computing models such as cloud computing, software as a service, hardware a...

  2. ATLAS Distributed Computing Automation

    CERN Document Server

    Schovancova, J; The ATLAS collaboration; Borrego, C; Campana, S; Di Girolamo, A; Elmsheuser, J; Hejbal, J; Kouba, T; Legger, F; Magradze, E; Medrano Llamas, R; Negri, G; Rinaldi, L; Sciacca, G; Serfon, C; Van Der Ster, D C

    2012-01-01

    The ATLAS Experiment benefits from computing resources distributed worldwide at more than 100 WLCG sites. The ATLAS Grid sites provide over 100k CPU job slots, over 100 PB of storage space on disk or tape. Monitoring of status of such a complex infrastructure is essential. The ATLAS Grid infrastructure is monitored 24/7 by two teams of shifters distributed world-wide, by the ATLAS Distributed Computing experts, and by site administrators. In this paper we summarize automation efforts performed within the ATLAS Distributed Computing team in order to reduce manpower costs and improve the reliability of the system. Different aspects of the automation process are described: from the ATLAS Grid site topology provided by the ATLAS Grid Information System, via automatic site testing by the HammerCloud, to automatic exclusion from production or analysis activities.

  3. Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure.

    Science.gov (United States)

    Wang, Henry; Ma, Yunzhi; Pratx, Guillem; Xing, Lei

    2011-09-07

    Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed.

  4. Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure

    International Nuclear Information System (INIS)

    Wang, Henry; Ma Yunzhi; Pratx, Guillem; Xing Lei

    2011-01-01

    Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47x speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed. (note)

  5. Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Henry [Department of Electrical Engineering, Stanford University, Stanford, CA 94305 (United States); Ma Yunzhi; Pratx, Guillem; Xing Lei, E-mail: hwang41@stanford.edu [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305-5847 (United States)

    2011-09-07

    Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47x speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed. (note)

  6. Cloud computing applications for biomedical science: A perspective.

    Science.gov (United States)

    Navale, Vivek; Bourne, Philip E

    2018-06-01

    Biomedical research has become a digital data-intensive endeavor, relying on secure and scalable computing, storage, and network infrastructure, which has traditionally been purchased, supported, and maintained locally. For certain types of biomedical applications, cloud computing has emerged as an alternative to locally maintained traditional computing approaches. Cloud computing offers users pay-as-you-go access to services such as hardware infrastructure, platforms, and software for solving common biomedical computational problems. Cloud computing services offer secure on-demand storage and analysis and are differentiated from traditional high-performance computing by their rapid availability and scalability of services. As such, cloud services are engineered to address big data problems and enhance the likelihood of data and analytics sharing, reproducibility, and reuse. Here, we provide an introductory perspective on cloud computing to help the reader determine its value to their own research.

  7. Radiotherapy infrastructure and human resources in Switzerland. Present status and projected computations for 2020

    International Nuclear Information System (INIS)

    Datta, Niloy Ranjan; Khan, Shaka; Marder, Dietmar; Zwahlen, Daniel; Bodis, Stephan

    2016-01-01

    The purpose of this study was to evaluate the present status of radiotherapy infrastructure and human resources in Switzerland and compute projections for 2020. The European Society of Therapeutic Radiation Oncology ''Quantification of Radiation Therapy Infrastructure and Staffing'' guidelines (ESTRO-QUARTS) and those of the International Atomic Energy Agency (IAEA) were applied to estimate the requirements for teleradiotherapy (TRT) units, radiation oncologists (RO), medical physicists (MP) and radiotherapy technologists (RTT). The databases used for computation of the present gap and additional requirements are (a) Global Cancer Incidence, Mortality and Prevalence (GLOBOCAN) for cancer incidence (b) the Directory of Radiotherapy Centres (DIRAC) of the IAEA for existing TRT units (c) human resources from the recent ESTRO ''Health Economics in Radiation Oncology'' (HERO) survey and (d) radiotherapy utilization (RTU) rates for each tumour site, published by the Ingham Institute for Applied Medical Research (IIAMR). In 2015, 30,999 of 45,903 cancer patients would have required radiotherapy. By 2020, this will have increased to 34,041 of 50,427 cancer patients. Switzerland presently has an adequate number of TRTs, but a deficit of 57 ROs, 14 MPs and 36 RTTs. By 2020, an additional 7 TRTs, 72 ROs, 22 MPs and 66 RTTs will be required. In addition, a realistic dynamic model for calculation of staff requirements due to anticipated changes in future radiotherapy practices has been proposed. This model could be tailor-made and individualized for any radiotherapy centre. A 9.8 % increase in radiotherapy requirements is expected for cancer patients over the next 5 years. The present study should assist the stakeholders and health planners in designing an appropriate strategy for meeting future radiotherapy needs for Switzerland. (orig.) [de

  8. Decision-making as performative struggle: Strategic political-executive practices influencing the actualization of an infrastructural development

    NARCIS (Netherlands)

    Merkus, S.; de Heer, J.M.; Veenswijk, M.B.

    2014-01-01

    Purpose – The purpose of this paper is to introduce the concept of performative struggle through the use of an interpretative case story focussed on a strategic decision-making process concerning infrastructural development. Performativity is about “world-making” (Carter et al., 2010), based on the

  9. Designing a High Performance Parallel Personal Cluster

    OpenAIRE

    Kapanova, K. G.; Sellier, J. M.

    2016-01-01

    Today, many scientific and engineering areas require high performance computing to perform computationally intensive experiments. For example, many advances in transport phenomena, thermodynamics, material properties, computational chemistry and physics are possible only because of the availability of such large scale computing infrastructures. Yet many challenges are still open. The cost of energy consumption, cooling, competition for resources have been some of the reasons why the scientifi...

  10. Accessible high performance computing solutions for near real-time image processing for time critical applications

    Science.gov (United States)

    Bielski, Conrad; Lemoine, Guido; Syryczynski, Jacek

    2009-09-01

    High Performance Computing (HPC) hardware solutions such as grid computing and General Processing on a Graphics Processing Unit (GPGPU) are now accessible to users with general computing needs. Grid computing infrastructures in the form of computing clusters or blades are becoming common place and GPGPU solutions that leverage the processing power of the video card are quickly being integrated into personal workstations. Our interest in these HPC technologies stems from the need to produce near real-time maps from a combination of pre- and post-event satellite imagery in support of post-disaster management. Faster processing provides a twofold gain in this situation: 1. critical information can be provided faster and 2. more elaborate automated processing can be performed prior to providing the critical information. In our particular case, we test the use of the PANTEX index which is based on analysis of image textural measures extracted using anisotropic, rotation-invariant GLCM statistics. The use of this index, applied in a moving window, has been shown to successfully identify built-up areas in remotely sensed imagery. Built-up index image masks are important input to the structuring of damage assessment interpretation because they help optimise the workload. The performance of computing the PANTEX workflow is compared on two different HPC hardware architectures: (1) a blade server with 4 blades, each having dual quad-core CPUs and (2) a CUDA enabled GPU workstation. The reference platform is a dual CPU-quad core workstation and the PANTEX workflow total computing time is measured. Furthermore, as part of a qualitative evaluation, the differences in setting up and configuring various hardware solutions and the related software coding effort is presented.

  11. CERN Infrastructure Evolution

    CERN Document Server

    Bell, Tim

    2012-01-01

    The CERN Computer Centre is reviewing strategies for optimizing the use of the existing infrastructure in the future, and in the likely scenario that any extension will be remote from CERN, and in the light of the way other large facilities are today being operated. Over the past six months, CERN has been investigating modern and widely-used tools and procedures used for virtualisation, clouds and fabric management in order to reduce operational effort, increase agility and support unattended remote computer centres. This presentation will give the details on the project’s motivations, current status and areas for future investigation.

  12. COMPSs-Mobile: parallel programming for mobile-cloud computing

    OpenAIRE

    Lordan Gomis, Francesc-Josep; Badia Sala, Rosa Maria

    2016-01-01

    The advent of Cloud and the popularization of mobile devices have led us to a shift in computing access. Computing users will have an interaction display while the real computation will be performed remotely, in the Cloud. COMPSs-Mobile is a framework that aims to ease the development of energy-efficient and high-performing applications for this environment. The framework provides an infrastructure-unaware programming model that allows developers to code regular Android applications that, ...

  13. Climate simulations and services on HPC, Cloud and Grid infrastructures

    Science.gov (United States)

    Cofino, Antonio S.; Blanco, Carlos; Minondo Tshuma, Antonio

    2017-04-01

    Cloud, Grid and High Performance Computing have changed the accessibility and availability of computing resources for Earth Science research communities, specially for Climate community. These paradigms are modifying the way how climate applications are being executed. By using these technologies the number, variety and complexity of experiments and resources are increasing substantially. But, although computational capacity is increasing, traditional applications and tools used by the community are not good enough to manage this large volume and variety of experiments and computing resources. In this contribution, we evaluate the challenges to run climate simulations and services on Grid, Cloud and HPC infrestructures and how to tackle them. The Grid and Cloud infrastructures provided by EGI's VOs ( esr , earth.vo.ibergrid and fedcloud.egi.eu) will be evaluated, as well as HPC resources from PRACE infrastructure and institutional clusters. To solve those challenges, solutions using DRM4G framework will be shown. DRM4G provides a good framework to manage big volume and variety of computing resources for climate experiments. This work has been supported by the Spanish National R&D Plan under projects WRF4G (CGL2011-28864), INSIGNIA (CGL2016-79210-R) and MULTI-SDM (CGL2015-66583-R) ; the IS-ENES2 project from the 7FP of the European Commission (grant agreement no. 312979); the European Regional Development Fund—ERDF and the Programa de Personal Investigador en Formación Predoctoral from Universidad de Cantabria and Government of Cantabria.

  14. INFRASTRUCTURE

    CERN Document Server

    A.Gaddi

    2011-01-01

    Between the end of March to June 2011, there has been no detector downtime during proton fills due to CMS Infrastructures failures. This exceptional performance is a clear sign of the high quality work done by the CMS Infrastructures unit and its supporting teams. Powering infrastructure At the end of March, the EN/EL group observed a problem with the CMS 48 V system. The problem was a lack of isolation between the negative (return) terminal and earth. Although at that moment we were not seeing any loss of functionality, in the long term it would have led to severe disruption to the CMS power system. The 48 V system is critical to the operation of CMS: in addition to feeding the anti-panic lights, essential for the safety of the underground areas, it powers all the PLCs (Twidos) that control AC power to the racks and front-end electronics of CMS. A failure of the 48 V system would bring down the whole detector and lead to evacuation of the cavern. EN/EL technicians have made an accurate search of the fault, ...

  15. INFRASTRUCTURE

    CERN Multimedia

    A. Gaddi and P. Tropea

    2011-01-01

    Most of the work relating to Infrastructure has been concentrated in the new CSC and RPC manufactory at building 904, on the Prevessin site. Brand new gas distribution, powering and HVAC infrastructures are being deployed and the production of the first CSC chambers has started. Other activities at the CMS site concern the installation of a new small crane bridge in the Cooling technical room in USC55, in order to facilitate the intervention of the maintenance team in case of major failures of the chilled water pumping units. The laser barrack in USC55 has been also the object of a study, requested by the ECAL community, for the new laser system that shall be delivered in few months. In addition, ordinary maintenance works have been performed during the short machine stops on all the main infrastructures at Point 5 and in preparation to the Year-End Technical Stop (YETS), when most of the systems will be carefully inspected in order to ensure a smooth running through the crucial year 2012. After the incide...

  16. Computing networks from cluster to cloud computing

    CERN Document Server

    Vicat-Blanc, Pascale; Guillier, Romaric; Soudan, Sebastien

    2013-01-01

    "Computing Networks" explores the core of the new distributed computing infrastructures we are using today:  the networking systems of clusters, grids and clouds. It helps network designers and distributed-application developers and users to better understand the technologies, specificities, constraints and benefits of these different infrastructures' communication systems. Cloud Computing will give the possibility for millions of users to process data anytime, anywhere, while being eco-friendly. In order to deliver this emerging traffic in a timely, cost-efficient, energy-efficient, and

  17. On the Development of a Computing Infrastructure that Facilitates IPPD from a Decision-Based Design Perspective

    Science.gov (United States)

    Hale, Mark A.; Craig, James I.; Mistree, Farrokh; Schrage, Daniel P.

    1995-01-01

    Integrated Product and Process Development (IPPD) embodies the simultaneous application of both system and quality engineering methods throughout an iterative design process. The use of IPPD results in the time-conscious, cost-saving development of engineering systems. Georgia Tech has proposed the development of an Integrated Design Engineering Simulator that will merge Integrated Product and Process Development with interdisciplinary analysis techniques and state-of-the-art computational technologies. To implement IPPD, a Decision-Based Design perspective is encapsulated in an approach that focuses on the role of the human designer in product development. The approach has two parts and is outlined in this paper. First, an architecture, called DREAMS, is being developed that facilitates design from a decision-based perspective. Second, a supporting computing infrastructure, called IMAGE, is being designed. The current status of development is given and future directions are outlined.

  18. Challenges and opportunities of cloud computing for atmospheric sciences

    Science.gov (United States)

    Pérez Montes, Diego A.; Añel, Juan A.; Pena, Tomás F.; Wallom, David C. H.

    2016-04-01

    Cloud computing is an emerging technological solution widely used in many fields. Initially developed as a flexible way of managing peak demand it has began to make its way in scientific research. One of the greatest advantages of cloud computing for scientific research is independence of having access to a large cyberinfrastructure to fund or perform a research project. Cloud computing can avoid maintenance expenses for large supercomputers and has the potential to 'democratize' the access to high-performance computing, giving flexibility to funding bodies for allocating budgets for the computational costs associated with a project. Two of the most challenging problems in atmospheric sciences are computational cost and uncertainty in meteorological forecasting and climate projections. Both problems are closely related. Usually uncertainty can be reduced with the availability of computational resources to better reproduce a phenomenon or to perform a larger number of experiments. Here we expose results of the application of cloud computing resources for climate modeling using cloud computing infrastructures of three major vendors and two climate models. We show how the cloud infrastructure compares in performance to traditional supercomputers and how it provides the capability to complete experiments in shorter periods of time. The monetary cost associated is also analyzed. Finally we discuss the future potential of this technology for meteorological and climatological applications, both from the point of view of operational use and research.

  19. Cloud Computing Security Latest Issues amp Countermeasures

    OpenAIRE

    Shelveen Pandey; Mohammed Farik

    2015-01-01

    Abstract Cloud computing describes effective computing services provided by a third-party organization known as cloud service provider for organizations to perform different tasks over the internet for a fee. Cloud service providers computing resources are dynamically reallocated per demand and their infrastructure platform and software and other resources are shared by multiple corporate and private clients. With the steady increase in the number of cloud computing subscribers of these shar...

  20. Research and development of grid computing technology in center for computational science and e-systems of Japan Atomic Energy Agency

    International Nuclear Information System (INIS)

    Suzuki, Yoshio

    2007-01-01

    Center for Computational Science and E-systems of the Japan Atomic Energy Agency (CCSE/JAEA) has carried out R and D of grid computing technology. Since 1995, R and D to realize computational assistance for researchers called Seamless Thinking Aid (STA) and then to share intellectual resources called Information Technology Based Laboratory (ITBL) have been conducted, leading to construct an intelligent infrastructure for the atomic energy research called Atomic Energy Grid InfraStructure (AEGIS) under the Japanese national project 'Development and Applications of Advanced High-Performance Supercomputer'. It aims to enable synchronization of three themes: 1) Computer-Aided Research and Development (CARD) to realize and environment for STA, 2) Computer-Aided Engineering (CAEN) to establish Multi Experimental Tools (MEXT), and 3) Computer Aided Science (CASC) to promote the Atomic Energy Research and Investigation (AERI). This article reviewed achievements in R and D of grid computing technology so far obtained. (T. Tanaka)

  1. Towards Process Support for Migrating Applications to Cloud Computing

    DEFF Research Database (Denmark)

    Chauhan, Muhammad Aufeef; Babar, Muhammad Ali

    2012-01-01

    Cloud computing is an active area of research for industry and academia. There are a large number of organizations providing cloud computing infrastructure and services. In order to utilize these infrastructure resources and services, existing applications need to be migrated to clouds. However...... for supporting migration to cloud computing based on our experiences from migrating an Open Source System (OSS), Hackystat, to two different cloud computing platforms. We explained the process by performing a comparative analysis of our efforts to migrate Hackystate to Amazon Web Services and Google App Engine....... We also report the potential challenges, suitable solutions, and lesson learned to support the presented process framework. We expect that the reported experiences can serve guidelines for those who intend to migrate software applications to cloud computing....

  2. Tool-based Risk Assessment of Cloud Infrastructures as Socio-Technical Systems

    DEFF Research Database (Denmark)

    Nidd, Michael; Ivanova, Marieta Georgieva; Probst, Christian W.

    2015-01-01

    Assessing risk in cloud infrastructures is difficult. Typical cloud infrastructures contain potentially thousands of nodes that are highly interconnected and dynamic. Another important component is the set of human actors who get access to data and computing infrastructure. The cloud infrastructure...... exercise for cloud infrastructures using the socio-technical model developed in the TRESPASS project; after showing how to model typical components of a cloud infrastructure, we show how attacks are identified on this model and discuss their connection to risk assessment. The technical part of the model...... is extracted automatically from the configuration of the cloud infrastructure, which is especially important for systems so dynamic and complex....

  3. European Bioinformatics Institute: Research Infrastructure needed for Life Science

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    The life science community is an ever increasing source of data from increasing diverse range of instruments and sources. EMBL-EBI has a remit to store and exploit this data, collected and made available openly across the world, for the benefit of the whole research community. The research infrastructure needed to support the big data analysis around this mission encompasses high performance networks, high-throughput computing, and a range of cloud and storage solutions - and will be described in the presentation.

  4. Quantifying the digital divide: a scientific overview of network connectivity and grid infrastructure in South Asian countries

    International Nuclear Information System (INIS)

    Khan, S M; Cottrell, R L; Kalim, U; Ali, A

    2008-01-01

    The future of Computing in High Energy Physics (HEP) applications depends on both the Network and Grid infrastructure. South Asian countries such as India and Pakistan are making significant progress by building clusters as well as improving their network infrastructure However to facilitate the use of these resources, they need to manage the issues of network connectivity to be among the leading participants in Computing for HEP experiments. In this paper we classify the connectivity for academic and research institutions of South Asia. The quantitative measurements are carried out using the PingER methodology; an approach that induces minimal ICMP traffic to gather active end-to-end network statistics. The PingER project has been measuring the Internet performance for the last decade. Currently the measurement infrastructure comprises of over 700 hosts in more than 130 countries which collectively represents approximately 99% of the world's Internet-connected population. Thus, we are well positioned to characterize the world's connectivity. Here we present the current state of the National Research and Educational Networks (NRENs) and Grid Infrastructure in the South Asian countries and identify the areas of concern. We also present comparisons between South Asia and other developing as well as developed regions. We show that there is a strong correlation between the Network performance and several Human Development indices

  5. Quantifying the Digital Divide: A Scientific Overview of Network Connectivity and Grid Infrastructure in South Asian Countries

    International Nuclear Information System (INIS)

    Khan, Shahryar Muhammad; Cottrell, R. Les; Kalim, Umar; Ali, Arshad

    2007-01-01

    The future of Computing in High Energy Physics (HEP) applications depends on both the Network and Grid infrastructure. South Asian countries such as India and Pakistan are making significant progress by building clusters as well as improving their network infrastructure However to facilitate the use of these resources, they need to manage the issues of network connectivity to be among the leading participants in Computing for HEP experiments. In this paper we classify the connectivity for academic and research institutions of South Asia. The quantitative measurements are carried out using the PingER methodology; an approach that induces minimal ICMP traffic to gather active end-to-end network statistics. The PingER project has been measuring the Internet performance for the last decade. Currently the measurement infrastructure comprises of over 700 hosts in more than 130 countries which collectively represents approximately 99% of the world's Internet-connected population. Thus, we are well positioned to characterize the world's connectivity. Here we present the current state of the National Research and Educational Networks (NRENs) and Grid Infrastructure in the South Asian countries and identify the areas of concern. We also present comparisons between South Asia and other developing as well as developed regions. We show that there is a strong correlation between the Network performance and several Human Development indices

  6. Thumbnail Images:Uncertainties, Infrastructures and Search Engines

    OpenAIRE

    Thylstrup, Nanna; Teilmann, Stina

    2017-01-01

    This article argues that thumbnail images are infrastructural images that raise issues of uncertainty in two distinct, but interrelated, areas: a legal question of how to define, understand and govern visual information infrastructures, in particular image search systems in epistemological and strategic terms; and a cultural question of how human-computer interaction design works with navigational uncertainty, both as an experience to be managed and a resource to be exploited. This paper cons...

  7. Research on Methods for Discovering and Selecting Cloud Infrastructure Services Based on Feature Modeling

    Directory of Open Access Journals (Sweden)

    Huamin Zhu

    2016-01-01

    Full Text Available Nowadays more and more cloud infrastructure service providers are providing large numbers of service instances which are a combination of diversified resources, such as computing, storage, and network. However, for cloud infrastructure services, the lack of a description standard and the inadequate research of systematic discovery and selection methods have exposed difficulties in discovering and choosing services for users. First, considering the highly configurable properties of a cloud infrastructure service, the feature model method is used to describe such a service. Second, based on the description of the cloud infrastructure service, a systematic discovery and selection method for cloud infrastructure services are proposed. The automatic analysis techniques of the feature model are introduced to verify the model’s validity and to perform the matching of the service and demand models. Finally, we determine the critical decision metrics and their corresponding measurement methods for cloud infrastructure services, where the subjective and objective weighting results are combined to determine the weights of the decision metrics. The best matching instances from various providers are then ranked by their comprehensive evaluations. Experimental results show that the proposed methods can effectively improve the accuracy and efficiency of cloud infrastructure service discovery and selection.

  8. Parallel, distributed and GPU computing technologies in single-particle electron microscopy.

    Science.gov (United States)

    Schmeisser, Martin; Heisen, Burkhard C; Luettich, Mario; Busche, Boris; Hauer, Florian; Koske, Tobias; Knauber, Karl-Heinz; Stark, Holger

    2009-07-01

    Most known methods for the determination of the structure of macromolecular complexes are limited or at least restricted at some point by their computational demands. Recent developments in information technology such as multicore, parallel and GPU processing can be used to overcome these limitations. In particular, graphics processing units (GPUs), which were originally developed for rendering real-time effects in computer games, are now ubiquitous and provide unprecedented computational power for scientific applications. Each parallel-processing paradigm alone can improve overall performance; the increased computational performance obtained by combining all paradigms, unleashing the full power of today's technology, makes certain applications feasible that were previously virtually impossible. In this article, state-of-the-art paradigms are introduced, the tools and infrastructure needed to apply these paradigms are presented and a state-of-the-art infrastructure and solution strategy for moving scientific applications to the next generation of computer hardware is outlined.

  9. Radiotherapy infrastructure and human resources in Switzerland : Present status and projected computations for 2020.

    Science.gov (United States)

    Datta, Niloy Ranjan; Khan, Shaka; Marder, Dietmar; Zwahlen, Daniel; Bodis, Stephan

    2016-09-01

    The purpose of this study was to evaluate the present status of radiotherapy infrastructure and human resources in Switzerland and compute projections for 2020. The European Society of Therapeutic Radiation Oncology "Quantification of Radiation Therapy Infrastructure and Staffing" guidelines (ESTRO-QUARTS) and those of the International Atomic Energy Agency (IAEA) were applied to estimate the requirements for teleradiotherapy (TRT) units, radiation oncologists (RO), medical physicists (MP) and radiotherapy technologists (RTT). The databases used for computation of the present gap and additional requirements are (a) Global Cancer Incidence, Mortality and Prevalence (GLOBOCAN) for cancer incidence (b) the Directory of Radiotherapy Centres (DIRAC) of the IAEA for existing TRT units (c) human resources from the recent ESTRO "Health Economics in Radiation Oncology" (HERO) survey and (d) radiotherapy utilization (RTU) rates for each tumour site, published by the Ingham Institute for Applied Medical Research (IIAMR). In 2015, 30,999 of 45,903 cancer patients would have required radiotherapy. By 2020, this will have increased to 34,041 of 50,427 cancer patients. Switzerland presently has an adequate number of TRTs, but a deficit of 57 ROs, 14 MPs and 36 RTTs. By 2020, an additional 7 TRTs, 72 ROs, 22 MPs and 66 RTTs will be required. In addition, a realistic dynamic model for calculation of staff requirements due to anticipated changes in future radiotherapy practices has been proposed. This model could be tailor-made and individualized for any radiotherapy centre. A 9.8 % increase in radiotherapy requirements is expected for cancer patients over the next 5 years. The present study should assist the stakeholders and health planners in designing an appropriate strategy for meeting future radiotherapy needs for Switzerland.

  10. Computing infrastructure for ATLAS data analysis in the Italian Grid cloud

    International Nuclear Information System (INIS)

    Andreazza, A; Annovi, A; Martini, A; Barberis, D; Brunengo, A; Corosu, M; Campana, S; Girolamo, A Di; Carlino, G; Doria, A; Merola, L; Musto, E; Ciocca, C; Jha, M K; Cobal, M; Pascolo, F; Salvo, A De; Luminari, L; Sanctis, U De; Galeazzi, F

    2011-01-01

    ATLAS data are distributed centrally to Tier-1 and Tier-2 sites. The first stages of data selection and analysis take place mainly at Tier-2 centres, with the final, iterative and interactive, stages taking place mostly at Tier-3 clusters. The Italian ATLAS cloud consists of a Tier-1, four Tier-2s, and Tier-3 sites at each institute. Tier-3s that are grid-enabled are used to test code that will then be run on a larger scale at Tier-2s. All Tier-3s offer interactive data access to their users and the possibility to run PROOF. This paper describes the hardware and software infrastructure choices taken, the operational experience after 10 months of LHC data, and discusses site performances.

  11. Designing Cloud Infrastructure for Big Data in E-government

    Directory of Open Access Journals (Sweden)

    Jelena Šuh

    2015-03-01

    Full Text Available The development of new information services and technologies, especially in domains of mobile communications, Internet of things, and social media, has led to appearance of the large quantities of unstructured data. The pervasive computing also affects the e-government systems, where big data emerges and cannot be processed and analyzed in a traditional manner due to its complexity, heterogeneity and size. The subject of this paper is the design of the cloud infrastructure for big data storage and processing in e-government. The goal is to analyze the potential of cloud computing for big data infrastructure, and propose a model for effective storing, processing and analyzing big data in e-government. The paper provides an overview of current relevant concepts related to cloud infrastructure design that should provide support for big data. The second part of the paper gives a model of the cloud infrastructure based on the concepts of software defined networks and multi-tenancy. The final goal is to support projects in the field of big data in e-government

  12. Performative Environments

    DEFF Research Database (Denmark)

    Thomsen, Bo Stjerne

    2008-01-01

    The paper explores how performative architecture can act as a collective environment localizing urban flows and establishing public domains through the integration of pervasive computing and animation techniques. The NoRA project introduces the concept of ‘performative environments,' focusing on ...... of local interactions and network behaviour, building becomes social infrastructure and prompts an understanding of architectural structures as quasiobjects, which can retain both variation and recognisability in changing social constellations.......The paper explores how performative architecture can act as a collective environment localizing urban flows and establishing public domains through the integration of pervasive computing and animation techniques. The NoRA project introduces the concept of ‘performative environments,' focusing...

  13. 2003 Conference for Computing in High Energy and Nuclear Physics

    International Nuclear Information System (INIS)

    Schalk, T.

    2003-01-01

    The conference was subdivided into the follow separate tracks. Electronic presentations and/or videos are provided on the main website link. Sessions: Plenary Talks and Panel Discussion; Grid Architecture, Infrastructure, and Grid Security; HENP Grid Applications, Testbeds, and Demonstrations; HENP Computing Systems and Infrastructure; Monitoring; High Performance Networking; Data Acquisition, Triggers and Controls; First Level Triggers and Trigger Hardware; Lattice Gauge Computing; HENP Software Architecture and Software Engineering; Data Management and Persistency; Data Analysis Environment and Visualization; Simulation and Modeling; and Collaboration Tools and Information Systems

  14. Large-scale parallel genome assembler over cloud computing environment.

    Science.gov (United States)

    Das, Arghya Kusum; Koppa, Praveen Kumar; Goswami, Sayan; Platania, Richard; Park, Seung-Jong

    2017-06-01

    The size of high throughput DNA sequencing data has already reached the terabyte scale. To manage this huge volume of data, many downstream sequencing applications started using locality-based computing over different cloud infrastructures to take advantage of elastic (pay as you go) resources at a lower cost. However, the locality-based programming model (e.g. MapReduce) is relatively new. Consequently, developing scalable data-intensive bioinformatics applications using this model and understanding the hardware environment that these applications require for good performance, both require further research. In this paper, we present a de Bruijn graph oriented Parallel Giraph-based Genome Assembler (GiGA), as well as the hardware platform required for its optimal performance. GiGA uses the power of Hadoop (MapReduce) and Giraph (large-scale graph analysis) to achieve high scalability over hundreds of compute nodes by collocating the computation and data. GiGA achieves significantly higher scalability with competitive assembly quality compared to contemporary parallel assemblers (e.g. ABySS and Contrail) over traditional HPC cluster. Moreover, we show that the performance of GiGA is significantly improved by using an SSD-based private cloud infrastructure over traditional HPC cluster. We observe that the performance of GiGA on 256 cores of this SSD-based cloud infrastructure closely matches that of 512 cores of traditional HPC cluster.

  15. Evolution of the Virtualized HPC Infrastructure of Novosibirsk Scientific Center

    International Nuclear Information System (INIS)

    Adakin, A; Chubarov, D; Nikultsev, V; Anisenkov, A; Belov, S; Kaplin, V; Korol, A; Skovpen, K; Sukharev, A; Zaytsev, A; Kalyuzhny, V; Kuchin, N; Lomakin, S

    2012-01-01

    Novosibirsk Scientific Center (NSC), also known worldwide as Akademgorodok, is one of the largest Russian scientific centers hosting Novosibirsk State University (NSU) and more than 35 research organizations of the Siberian Branch of Russian Academy of Sciences including Budker Institute of Nuclear Physics (BINP), Institute of Computational Technologies, and Institute of Computational Mathematics and Mathematical Geophysics (ICM and MG). Since each institute has specific requirements on the architecture of computing farms involved in its research field, currently we've got several computing facilities hosted by NSC institutes, each optimized for a particular set of tasks, of which the largest are the NSU Supercomputer Center, Siberian Supercomputer Center (ICM and MG), and a Grid Computing Facility of BINP. A dedicated optical network with the initial bandwidth of 10 Gb/s connecting these three facilities was built in order to make it possible to share the computing resources among the research communities, thus increasing the efficiency of operating the existing computing facilities and offering a common platform for building the computing infrastructure for future scientific projects. Unification of the computing infrastructure is achieved by extensive use of virtualization technology based on XEN and KVM platforms. This contribution gives a thorough review of the present status and future development prospects for the NSC virtualized computing infrastructure and the experience gained while using it for running production data analysis jobs related to HEP experiments being carried out at BINP, especially the KEDR detector experiment at the VEPP-4M electron-positron collider.

  16. Cluman: Advanced cluster management for the large-scale infrastructures

    International Nuclear Information System (INIS)

    Babik, Marian; Fedorko, Ivan; Rodrigues, David

    2011-01-01

    The recent uptake of multi-core computing has produced a rapid growth of virtualisation and cloud computing services. With the increased use of the many-core processors this trend will likely accelerate and computing centres will be faced with the management of the tens of thousands of the virtual machines. Furthermore, these machines will likely be geographically distributed and need to be allocated on demand. In order to cope with such complexity we have designed and developed an advanced cluster management system that can execute administrative tasks targeting thousands of machines as well as provide an interactive high-density visualisation of the fabrics. The job management subsystem can perform complex tasks while following their progress and output and report aggregated information back to the system administrators. The visualisation subsystem can display tree maps of the infrastructure elements with data and monitoring information, thus providing a very detailed overview of the large clusters at a glance. The initial experience with development and testing of the system will be presented as well as an evaluation of its performance.

  17. Big data computing: Building a vision for ARS information management

    Science.gov (United States)

    Improvements are needed within the ARS to increase scientific capacity and keep pace with new developments in computer technologies that support data acquisition and analysis. Enhancements in computing power and IT infrastructure are needed to provide scientists better access to high performance com...

  18. SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology.

    Science.gov (United States)

    Adams, Richard; Clark, Allan; Yamaguchi, Azusa; Hanlon, Neil; Tsorman, Nikos; Ali, Shakir; Lebedeva, Galina; Goltsov, Alexey; Sorokin, Anatoly; Akman, Ozgur E; Troein, Carl; Millar, Andrew J; Goryanin, Igor; Gilmore, Stephen

    2013-03-01

    Complex computational experiments in Systems Biology, such as fitting model parameters to experimental data, can be challenging to perform. Not only do they frequently require a high level of computational power, but the software needed to run the experiment needs to be usable by scientists with varying levels of computational expertise, and modellers need to be able to obtain up-to-date experimental data resources easily. We have developed a software suite, the Systems Biology Software Infrastructure (SBSI), to facilitate the parameter-fitting process. SBSI is a modular software suite composed of three major components: SBSINumerics, a high-performance library containing parallelized algorithms for performing parameter fitting; SBSIDispatcher, a middleware application to track experiments and submit jobs to back-end servers; and SBSIVisual, an extensible client application used to configure optimization experiments and view results. Furthermore, we have created a plugin infrastructure to enable project-specific modules to be easily installed. Plugin developers can take advantage of the existing user-interface and application framework to customize SBSI for their own uses, facilitated by SBSI's use of standard data formats. All SBSI binaries and source-code are freely available from http://sourceforge.net/projects/sbsi under an Apache 2 open-source license. The server-side SBSINumerics runs on any Unix-based operating system; both SBSIVisual and SBSIDispatcher are written in Java and are platform independent, allowing use on Windows, Linux and Mac OS X. The SBSI project website at http://www.sbsi.ed.ac.uk provides documentation and tutorials.

  19. BUILDING A COMPLETE FREE AND OPEN SOURCE GIS INFRASTRUCTURE FOR HYDROLOGICAL COMPUTING AND DATA PUBLICATION USING GIS.LAB AND GISQUICK PLATFORMS

    Directory of Open Access Journals (Sweden)

    M. Landa

    2017-07-01

    Full Text Available Building a complete free and open source GIS computing and data publication platform can be a relatively easy task. This paper describes an automated deployment of such platform using two open source software projects – GIS.lab and Gisquick. GIS.lab (http: //web.gislab.io is a project for rapid deployment of a complete, centrally managed and horizontally scalable GIS infrastructure in the local area network, data center or cloud. It provides a comprehensive set of free geospatial software seamlessly integrated into one, easy-to-use system. A platform for GIS computing (in our case demonstrated on hydrological data processing requires core components as a geoprocessing server, map server, and a computation engine as eg. GRASS GIS, SAGA, or other similar GIS software. All these components can be rapidly, and automatically deployed by GIS.lab platform. In our demonstrated solution PyWPS is used for serving WPS processes built on the top of GRASS GIS computation platform. GIS.lab can be easily extended by other components running in Docker containers. This approach is shown on Gisquick seamless integration. Gisquick (http://gisquick.org is an open source platform for publishing geospatial data in the sense of rapid sharing of QGIS projects on the web. The platform consists of QGIS plugin, Django-based server application, QGIS server, and web/mobile clients. In this paper is shown how to easily deploy complete open source GIS infrastructure allowing all required operations as data preparation on desktop, data sharing, and geospatial computation as the service. It also includes data publication in the sense of OGC Web Services and importantly also as interactive web mapping applications.

  20. Cloud Infrastructure Security

    OpenAIRE

    Velev , Dimiter; Zlateva , Plamena

    2010-01-01

    Part 4: Security for Clouds; International audience; Cloud computing can help companies accomplish more by eliminating the physical bonds between an IT infrastructure and its users. Users can purchase services from a cloud environment that could allow them to save money and focus on their core business. At the same time certain concerns have emerged as potential barriers to rapid adoption of cloud services such as security, privacy and reliability. Usually the information security professiona...

  1. ELASTIC CLOUD COMPUTING ARCHITECTURE AND SYSTEM FOR HETEROGENEOUS SPATIOTEMPORAL COMPUTING

    Directory of Open Access Journals (Sweden)

    X. Shi

    2017-10-01

    Full Text Available Spatiotemporal computation implements a variety of different algorithms. When big data are involved, desktop computer or standalone application may not be able to complete the computation task due to limited memory and computing power. Now that a variety of hardware accelerators and computing platforms are available to improve the performance of geocomputation, different algorithms may have different behavior on different computing infrastructure and platforms. Some are perfect for implementation on a cluster of graphics processing units (GPUs, while GPUs may not be useful on certain kind of spatiotemporal computation. This is the same situation in utilizing a cluster of Intel's many-integrated-core (MIC or Xeon Phi, as well as Hadoop or Spark platforms, to handle big spatiotemporal data. Furthermore, considering the energy efficiency requirement in general computation, Field Programmable Gate Array (FPGA may be a better solution for better energy efficiency when the performance of computation could be similar or better than GPUs and MICs. It is expected that an elastic cloud computing architecture and system that integrates all of GPUs, MICs, and FPGAs could be developed and deployed to support spatiotemporal computing over heterogeneous data types and computational problems.

  2. Elastic Cloud Computing Architecture and System for Heterogeneous Spatiotemporal Computing

    Science.gov (United States)

    Shi, X.

    2017-10-01

    Spatiotemporal computation implements a variety of different algorithms. When big data are involved, desktop computer or standalone application may not be able to complete the computation task due to limited memory and computing power. Now that a variety of hardware accelerators and computing platforms are available to improve the performance of geocomputation, different algorithms may have different behavior on different computing infrastructure and platforms. Some are perfect for implementation on a cluster of graphics processing units (GPUs), while GPUs may not be useful on certain kind of spatiotemporal computation. This is the same situation in utilizing a cluster of Intel's many-integrated-core (MIC) or Xeon Phi, as well as Hadoop or Spark platforms, to handle big spatiotemporal data. Furthermore, considering the energy efficiency requirement in general computation, Field Programmable Gate Array (FPGA) may be a better solution for better energy efficiency when the performance of computation could be similar or better than GPUs and MICs. It is expected that an elastic cloud computing architecture and system that integrates all of GPUs, MICs, and FPGAs could be developed and deployed to support spatiotemporal computing over heterogeneous data types and computational problems.

  3. VM-based infrastructure for simulating different cluster and storage solutions in ATLAS

    CERN Document Server

    KUTOUSKI, M; The ATLAS collaboration; PETROSYAN, A; KADOCHNIKOV, I; BELOV, S; KORENKOV, V

    2012-01-01

    The current ATLAS Tier3 infrastructure consists of a variety of sites of different sizes and with a mix of local resource management systems (LRMS) and mass storage system (MSS) implementations. The Tier3 monitoring suite, having been developed in order to satisfy the needs of Tier3 site administrators and to aggregate Tier3 monitoring information on the global VO level, needs to be validated for various combinations of LRMS and MSS solutions along with the corresponding Ganglia and/or Nagios plugins. For this purpose the Testbed infrastructure, which allows simulation of various computational cluster and storage solutions, had been set up at JINR (Dubna). This infrastructure provides the ability to run testbeds with various LRMS and MSS implementations, and with the capability to quickly redeploy particular testbeds or their components. Performance of specific components is not a critical issue for development and validation, whereas easy management and deployment are crucial. Therefore virtual machines were...

  4. Computer performance evaluation of FACOM 230-75 computer system, (2)

    International Nuclear Information System (INIS)

    Fujii, Minoru; Asai, Kiyoshi

    1980-08-01

    In this report are described computer performance evaluations for FACOM230-75 computers in JAERI. The evaluations are performed on following items: (1) Cost/benefit analysis of timesharing terminals, (2) Analysis of the response time of timesharing terminals, (3) Analysis of throughout time for batch job processing, (4) Estimation of current potential demands for computer time, (5) Determination of appropriate number of card readers and line printers. These evaluations are done mainly from the standpoint of cost reduction of computing facilities. The techniques adapted are very practical ones. This report will be useful for those people who are concerned with the management of computing installation. (author)

  5. A Cyber Infrastructure for the SKA Telescope Manager

    OpenAIRE

    Barbosa, Domingos; Barracaa, Joao Paulo; Carvalho, Bruno; Maia, Dalmiro; Gupta, Yashwant; Natarajan, Swaminathan; Roux, Gerhard Le; Swart, Paul

    2016-01-01

    The Square Kilometre Array Telescope Manager (SKA TM) will be responsible for assisting the SKA Operations and Observation Management, carrying out System diagnosis and collecting Monitoring & Control data from the SKA sub-systems and components. To provide adequate compute resources, scalability, operation continuity and high availability, as well as strict Quality of Service, the TM cyber-infrastructure (embodied in the Local Infrastructure - LINFRA) consists of COTS hardware and infrastruc...

  6. Chromium Renderserver: Scalable and Open Source Remote RenderingInfrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Paul, Brian; Ahern, Sean; Bethel, E. Wes; Brugger, Eric; Cook,Rich; Daniel, Jamison; Lewis, Ken; Owen, Jens; Southard, Dale

    2007-12-01

    Chromium Renderserver (CRRS) is software infrastructure thatprovides the ability for one or more users to run and view image outputfrom unmodified, interactive OpenGL and X11 applications on a remote,parallel computational platform equipped with graphics hardwareaccelerators via industry-standard Layer 7 network protocolsand clientviewers. The new contributions of this work include a solution to theproblem of synchronizing X11 and OpenGL command streams, remote deliveryof parallel hardware-accelerated rendering, and a performance analysis ofseveral different optimizations that are generally applicable to avariety of rendering architectures. CRRSis fully operational, Open Sourcesoftware.

  7. VM-based infrastructure for simulating different cluster and storage solutions used on ATLAS Tier-3 sites

    International Nuclear Information System (INIS)

    Belov, S; Kadochnikov, I; Korenkov, V; Kutouski, M; Oleynik, D; Petrosyan, A

    2012-01-01

    The current ATLAS Tier-3 infrastructure consists of a variety of sites of different sizes and with a mix of local resource management systems (LRMS) and mass storage system (MSS) implementations. The Tier-3 monitoring suite, having been developed in order to satisfy the needs of Tier-3 site administrators and to aggregate Tier-3 monitoring information on the global VO level, needs to be validated for various combinations of LRMS and MSS solutions along with the corresponding Ganglia plugins. For this purpose the testbed infrastructure, which allows simulation of various computational cluster and storage solutions, had been set up at JINR (Dubna, Russia). This infrastructure provides the ability to run testbeds with various LRMS and MSS implementations, and with the capability to quickly redeploy particular testbeds or their components. Performance of specific components is not a critical issue for development and validation, whereas easy management and deployment are crucial. Therefore virtual machines were chosen for implementation of the validation infrastructure which, though initially developed for Tier-3 monitoring project, can be exploited for other purposes. Load generators for simulation of the computing activities at the farm were developed as a part of this task. The paper will cover concrete implementation, including deployment scenarios, hypervisor details and load simulators.

  8. Resilient workflows for computational mechanics platforms

    International Nuclear Information System (INIS)

    Nguyen, Toan; Trifan, Laurentiu; Desideri, Jean-Antoine

    2010-01-01

    Workflow management systems have recently been the focus of much interest and many research and deployment for scientific applications worldwide. Their ability to abstract the applications by wrapping application codes have also stressed the usefulness of such systems for multidiscipline applications. When complex applications need to provide seamless interfaces hiding the technicalities of the computing infrastructures, their high-level modeling, monitoring and execution functionalities help giving production teams seamless and effective facilities. Software integration infrastructures based on programming paradigms such as Python, Mathlab and Scilab have also provided evidence of the usefulness of such approaches for the tight coupling of multidisciplne application codes. Also high-performance computing based on multi-core multi-cluster infrastructures open new opportunities for more accurate, more extensive and effective robust multi-discipline simulations for the decades to come. This supports the goal of full flight dynamics simulation for 3D aircraft models within the next decade, opening the way to virtual flight-tests and certification of aircraft in the future.

  9. COMPUTING

    CERN Multimedia

    M. Kasemann

    Introduction During the past six months, Computing participated in the STEP09 exercise, had a major involvement in the October exercise and has been working with CMS sites on improving open issues relevant for data taking. At the same time operations for MC production, real data reconstruction and re-reconstructions and data transfers at large scales were performed. STEP09 was successfully conducted in June as a joint exercise with ATLAS and the other experiments. It gave good indication about the readiness of the WLCG infrastructure with the two major LHC experiments stressing the reading, writing and processing of physics data. The October Exercise, in contrast, was conducted as an all-CMS exercise, where Physics, Computing and Offline worked on a common plan to exercise all steps to efficiently access and analyze data. As one of the major results, the CMS Tier-2s demonstrated to be fully capable for performing data analysis. In recent weeks, efforts were devoted to CMS Computing readiness. All th...

  10. Computing on the grid and in the cloud

    CERN Multimedia

    CERN. Geneva

    2014-01-01

    "The results today are only possible because of the extraordinary performance of the accelerators, including the infrastructure, the experiments, and the Grid computing." These were the words of the CERN Director General Rolf Heuer when the observation of a new particle consistent with a Higgs Boson was revealed to the world on the 4th July 2012. The end result of the all investments made to build and operate the LHC is the data that are recorded and the knowledge that can be extracted. It is the role of the global computing infrastructure to unlock the value that is encapsulated in the data. This lecture provides a detailed overview of the Worldwide LHC Computing Grid, an international collaboration to distribute and analyse the LHC data.

  11. Computing on the grid and in the cloud

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    "The results today are only possible because of the extraordinary performance of the accelerators, including the infrastructure, the experiments, and the Grid computing." These were the words of the CERN Director General Rolf Heuer when the observation of a new particle consistent with a Higgs Boson was revealed to the world on the 4th July 2012. The end result of the all investments made to build and operate the LHC is the data that are recorded and the knowledge that can be extracted. It is the role of the global computing infrastructure to unlock the value that is encapsulated in the data. This lecture provides a detailed overview of the Worldwide LHC Computing Grid, an international collaboration to distribute and analyse the LHC data.

  12. ATLAS Computing on the Swiss Cloud SWITCHengines

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00215485; The ATLAS collaboration; Sciacca, Gianfranco

    2016-01-01

    Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performance used and achieved running ATLAS production on SWITCHengines. SWITCHengines is the new cloud infrastructure offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, which we also report on, are country specific.

  13. Parallel, distributed and GPU computing technologies in single-particle electron microscopy

    International Nuclear Information System (INIS)

    Schmeisser, Martin; Heisen, Burkhard C.; Luettich, Mario; Busche, Boris; Hauer, Florian; Koske, Tobias; Knauber, Karl-Heinz; Stark, Holger

    2009-01-01

    An introduction to the current paradigm shift towards concurrency in software. Most known methods for the determination of the structure of macromolecular complexes are limited or at least restricted at some point by their computational demands. Recent developments in information technology such as multicore, parallel and GPU processing can be used to overcome these limitations. In particular, graphics processing units (GPUs), which were originally developed for rendering real-time effects in computer games, are now ubiquitous and provide unprecedented computational power for scientific applications. Each parallel-processing paradigm alone can improve overall performance; the increased computational performance obtained by combining all paradigms, unleashing the full power of today’s technology, makes certain applications feasible that were previously virtually impossible. In this article, state-of-the-art paradigms are introduced, the tools and infrastructure needed to apply these paradigms are presented and a state-of-the-art infrastructure and solution strategy for moving scientific applications to the next generation of computer hardware is outlined

  14. ATLAS computing on Swiss Cloud SWITCHengines

    Science.gov (United States)

    Haug, S.; Sciacca, F. G.; ATLAS Collaboration

    2017-10-01

    Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider at CERN in Geneva. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performances used and achieved running simulation tasks for the ATLAS experiment on SWITCHengines. SWITCHengines is a new infrastructure as a service offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, on which we also report, are country specific.

  15. ATLAS computing on Swiss Cloud SWITCHengines

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00215485; The ATLAS collaboration; Sciacca, Gianfranco

    2017-01-01

    Consolidation towards more computing at flat budgets beyond what pure chip technology can offer, is a requirement for the full scientific exploitation of the future data from the Large Hadron Collider at CERN in Geneva. One consolidation measure is to exploit cloud infrastructures whenever they are financially competitive. We report on the technical solutions and the performances used and achieved running simulation tasks for the ATLAS experiment on SWITCHengines. SWITCHengines is a new infrastructure as a service offered to Swiss academia by the National Research and Education Network SWITCH. While solutions and performances are general, financial considerations and policies, on which we also report, are country specific.

  16. Security framework for virtualised infrastructure services provisioned on-demand

    NARCIS (Netherlands)

    Ngo, C.; Membrey, P.; Demchenko, Y.; de Laat, C.

    2011-01-01

    Cloud computing is developing as a new wave of ICT technologies, offering a common approach to on-demand provisioning computation, storage and network resources which are generally referred to as infrastructure services. Most of currently available commercial Cloud services are built and organized

  17. Towards Shibboleth-based security in the e-infrastructure for social sciences

    OpenAIRE

    Jie, Wei; Daw, Michael; Procter, Rob; Voss, Alex

    2007-01-01

    The e-Infrastructure for e-Social Sciences project leverages Grid computing technology to provide an integrated platform which enables social science researchers to securely access a variety of e-Science resources. Security underpins the e-Infrastructure and a security framework with authentication and authorization functionality is a core component of the e-Infrastructure for social sciences. To build the security framework, we adopt Shibboleth as the basic authentication and authorization i...

  18. Software network analyzer for computer network performance measurement planning over heterogeneous services in higher educational institutes

    OpenAIRE

    Ismail, Mohd Nazri

    2009-01-01

    In 21st century, convergences of technologies and services in heterogeneous environment have contributed multi-traffic. This scenario will affect computer network on learning system in higher educational Institutes. Implementation of various services can produce different types of content and quality. Higher educational institutes should have a good computer network infrastructure to support usage of various services. The ability of computer network should consist of i) higher bandwidth; ii) ...

  19. Social web applications in the city: a lightweight infrastructure for urban computing

    DEFF Research Database (Denmark)

    Hansen, Frank Allan; Grønbæk, Kaj

    2008-01-01

    In this paper, we describe an infrastructure for browsing and multimedia blogging of Web-based information anchored with physical places in an urban environment. The infrastructure is generic in the sense that it may use any means such as GPS, RFID or 2D-barcodes as ubiquitous links anchors...... to anchor Web-based information, blogs, and services in the physical environment. The infrastructure is inspired from earlier work on open hypermedia, in the sense that the anchoring and blogging functionality can be integrated to augment arbitrary Web sites providing information that is relevant to places...... or objects in the physical world. The blog and anchor functionality is implemented as a set of Web services running on a server external to the content server. Experiences and design issues from three cases are discussed, which use Semacode-based physical anchoring to support lightweight urban Web...

  20. High Performance Computing in Science and Engineering '16 : Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2016

    CERN Document Server

    Kröner, Dietmar; Resch, Michael

    2016-01-01

    This book presents the state-of-the-art in supercomputer simulation. It includes the latest findings from leading researchers using systems from the High Performance Computing Center Stuttgart (HLRS) in 2016. The reports cover all fields of computational science and engineering ranging from CFD to computational physics and from chemistry to computer science with a special emphasis on industrially relevant applications. Presenting findings of one of Europe’s leading systems, this volume covers a wide variety of applications that deliver a high level of sustained performance. The book covers the main methods in high-performance computing. Its outstanding results in achieving the best performance for production codes are of particular interest for both scientists and engineers. The book comes with a wealth of color illustrations and tables of results.

  1. VASA: Interactive Computational Steering of Large Asynchronous Simulation Pipelines for Societal Infrastructure.

    Science.gov (United States)

    Ko, Sungahn; Zhao, Jieqiong; Xia, Jing; Afzal, Shehzad; Wang, Xiaoyu; Abram, Greg; Elmqvist, Niklas; Kne, Len; Van Riper, David; Gaither, Kelly; Kennedy, Shaun; Tolone, William; Ribarsky, William; Ebert, David S

    2014-12-01

    We present VASA, a visual analytics platform consisting of a desktop application, a component model, and a suite of distributed simulation components for modeling the impact of societal threats such as weather, food contamination, and traffic on critical infrastructure such as supply chains, road networks, and power grids. Each component encapsulates a high-fidelity simulation model that together form an asynchronous simulation pipeline: a system of systems of individual simulations with a common data and parameter exchange format. At the heart of VASA is the Workbench, a visual analytics application providing three distinct features: (1) low-fidelity approximations of the distributed simulation components using local simulation proxies to enable analysts to interactively configure a simulation run; (2) computational steering mechanisms to manage the execution of individual simulation components; and (3) spatiotemporal and interactive methods to explore the combined results of a simulation run. We showcase the utility of the platform using examples involving supply chains during a hurricane as well as food contamination in a fast food restaurant chain.

  2. Partnership in Computational Science

    Energy Technology Data Exchange (ETDEWEB)

    Huray, Paul G.

    1999-02-24

    This is the final report for the "Partnership in Computational Science" (PICS) award in an amount of $500,000 for the period January 1, 1993 through December 31, 1993. A copy of the proposal with its budget is attached as Appendix A. This report first describes the consequent significance of the DOE award in building infrastructure of high performance computing in the Southeast and then describes the work accomplished under this grant and a list of publications resulting from it.

  3. Critical infrastructure protection research results of the first critical infrastructure protection research project in Hungary

    CERN Document Server

    Padányi, József

    2016-01-01

    This book presents recent research in the recognition of vulnerabilities of national systems and assets which gained special attention for the Critical Infrastructures in the last two decades. The book concentrates on R&D activities in the relation of Critical Infrastructures focusing on enhancing the performance of services as well as the level of security. The objectives of the book are based on a project entitled "Critical Infrastructure Protection Researches" (TÁMOP-4.2.1.B-11/2/KMR-2011-0001) which concentrated on innovative UAV solutions, robotics, cybersecurity, surface engineering, and mechatrinics and technologies providing safe operations of essential assets. This report is summarizing the methodologies and efforts taken to fulfill the goals defined. The project has been performed by the consortium of the Óbuda University and the National University of Public Service.

  4. Critical Infrastructure: Control Systems and the Terrorist Threat

    National Research Council Canada - National Science Library

    Shea, Dana A

    2003-01-01

    .... Industrial control computer systems involved in this infrastructure are specific points of vulnerability, as cyber-security for these systems has not been previously perceived as a high priority...

  5. Critical Infrastructure: Control Systems and the Terrorist Threat

    National Research Council Canada - National Science Library

    Shea, Dana A

    2004-01-01

    .... Industrial control computer systems involved in this infrastructure are specific points of vulnerability, as cyber-security for these systems has not been previously perceived as a high priority...

  6. SEE-GRID eInfrastructure for Regional eScience

    Science.gov (United States)

    Prnjat, Ognjen; Balaz, Antun; Vudragovic, Dusan; Liabotis, Ioannis; Sener, Cevat; Marovic, Branko; Kozlovszky, Miklos; Neagu, Gabriel

    In the past 6 years, a number of targeted initiatives, funded by the European Commission via its information society and RTD programmes and Greek infrastructure development actions, have articulated a successful regional development actions in South East Europe that can be used as a role model for other international developments. The SEEREN (South-East European Research and Education Networking initiative) project, through its two phases, established the SEE segment of the pan-European G ´EANT network and successfully connected the research and scientific communities in the region. Currently, the SEE-LIGHT project is working towards establishing a dark-fiber backbone that will interconnect most national Research and Education networks in the region. On the distributed computing and storage provisioning i.e. Grid plane, the SEE-GRID (South-East European GRID e-Infrastructure Development) project, similarly through its two phases, has established a strong human network in the area of scientific computing and has set up a powerful regional Grid infrastructure, and attracted a number of applications from different fields from countries throughout the South-East Europe. The current SEEGRID-SCI project, ending in April 2010, empowers the regional user communities from fields of meteorology, seismology and environmental protection in common use and sharing of the regional e-Infrastructure. Current technical initiatives in formulation are focusing on a set of coordinated actions in the area of HPC and application fields making use of HPC initiatives. Finally, the current SEERA-EI project brings together policy makers - programme managers from 10 countries in the region. The project aims to establish a communication platform between programme managers, pave the way towards common e-Infrastructure strategy and vision, and implement concrete actions for common funding of electronic infrastructures on the regional level. The regional vision on establishing an e-Infrastructure

  7. Use of several Cloud Computing approaches for climate modelling: performance, costs and opportunities

    Science.gov (United States)

    Perez Montes, Diego A.; Añel Cabanelas, Juan A.; Wallom, David C. H.; Arribas, Alberto; Uhe, Peter; Caderno, Pablo V.; Pena, Tomas F.

    2017-04-01

    Cloud Computing is a technological option that offers great possibilities for modelling in geosciences. We have studied how two different climate models, HadAM3P-HadRM3P and CESM-WACCM, can be adapted in two different ways to run on Cloud Computing Environments from three different vendors: Amazon, Google and Microsoft. Also, we have evaluated qualitatively how the use of Cloud Computing can affect the allocation of resources by funding bodies and issues related to computing security, including scientific reproducibility. Our first experiments were developed using the well known ClimatePrediction.net (CPDN), that uses BOINC, over the infrastructure from two cloud providers, namely Microsoft Azure and Amazon Web Services (hereafter AWS). For this comparison we ran a set of thirteen month climate simulations for CPDN in Azure and AWS using a range of different virtual machines (VMs) for HadRM3P (50 km resolution over South America CORDEX region) nested in the global atmosphere-only model HadAM3P. These simulations were run on a single processor and took between 3 and 5 days to compute depending on the VM type. The last part of our simulation experiments was running WACCM over different VMS on the Google Compute Engine (GCE) and make a comparison with the supercomputer (SC) Finisterrae1 from the Centro de Supercomputacion de Galicia. It was shown that GCE gives better performance than the SC for smaller number of cores/MPI tasks but the model throughput shows clearly how the SC performance is better after approximately 100 cores (related with network speed and latency differences). From a cost point of view, Cloud Computing moves researchers from a traditional approach where experiments were limited by the available hardware resources to monetary resources (how many resources can be afforded). As there is an increasing movement and recommendation for budgeting HPC projects on this technology (budgets can be calculated in a more realistic way) we could see a shift on

  8. Understanding the infrastructure of European Research Infrastructures

    DEFF Research Database (Denmark)

    Lindstrøm, Maria Duclos; Kropp, Kristoffer

    2017-01-01

    European Research Infrastructure Consortia (ERIC) are a new form of legal and financial framework for the establishment and operation of research infrastructures in Europe. Despite their scope, ambition, and novelty, the topic has received limited scholarly attention. This article analyses one ER....... It is also a promising theoretical framework for addressing the relationship between the ERIC construct and the large diversity of European Research Infrastructures.......European Research Infrastructure Consortia (ERIC) are a new form of legal and financial framework for the establishment and operation of research infrastructures in Europe. Despite their scope, ambition, and novelty, the topic has received limited scholarly attention. This article analyses one ERIC...... became an ERIC using the Bowker and Star’s sociology of infrastructures. We conclude that focusing on ERICs as a European standard for organising and funding research collaboration gives new insights into the problems of membership, durability, and standardisation faced by research infrastructures...

  9. Infrastructuring for Quality

    DEFF Research Database (Denmark)

    Bossen, Claus; Danholt, Peter; Ubbesen, Morten Bonde

    2015-01-01

    Reimbursement and budgeting constitutes a central infrastructural element in most secondary healthcare sectors. In Denmark, Diagnose-Related Groups (DRG) function as the core element for budgeting and encouraging increase in activity and effectivity. However, DRG is known to potentially have...... indicators for quality in treatment to guide and govern their performance, in order to investigate whether this may generate a new performance measurement infrastructure that will improve quality of healthcare. The project is entitled: “New governance in the patient’s perspective”....... adverse effects by encouraging hospitals to maximize reimbursement at the expense of patients. To counter this, one Danish region has initiated an experiment involving nine hospital departments whose normal budgeting and reimbursement based on DRG is put on hold. Instead, they have been asked to develop...

  10. Towards Constraint-based High Performance Cloud System in the Process of Cloud Computing Adoption in an Organization

    OpenAIRE

    Simalango, Mikael Fernandus; Kang, Mun-Young; Oh, Sangyoon

    2010-01-01

    Cloud computing is penetrating into various domains and environments, from theoretical computer science to economy, from marketing hype to educational curriculum and from R&D lab to enterprise IT infrastructure. Yet, the currently developing state of cloud computing leaves several issues to address and also affects cloud computing adoption by organizations. In this paper, we explain how the transition into the cloud can occur in an organization and describe the mechanism for transforming lega...

  11. DOE research in utilization of high-performance computers

    International Nuclear Information System (INIS)

    Buzbee, B.L.; Worlton, W.J.; Michael, G.; Rodrigue, G.

    1980-12-01

    Department of Energy (DOE) and other Government research laboratories depend on high-performance computer systems to accomplish their programatic goals. As the most powerful computer systems become available, they are acquired by these laboratories so that advances can be made in their disciplines. These advances are often the result of added sophistication to numerical models whose execution is made possible by high-performance computer systems. However, high-performance computer systems have become increasingly complex; consequently, it has become increasingly difficult to realize their potential performance. The result is a need for research on issues related to the utilization of these systems. This report gives a brief description of high-performance computers, and then addresses the use of and future needs for high-performance computers within DOE, the growing complexity of applications within DOE, and areas of high-performance computer systems warranting research. 1 figure

  12. Grid computing infrastructure, service, and applications

    CERN Document Server

    Jie, Wei; Chen, Jinjun

    2009-01-01

    Offering a comprehensive discussion of advances in grid computing, this book summarizes the concepts, methods, technologies, and applications. It covers topics such as philosophy, middleware, architecture, services, and applications. It also includes technical details to demonstrate how grid computing works in the real world

  13. Monitoring the US ATLAS Network Infrastructure with perfSONAR-PS

    International Nuclear Information System (INIS)

    McKee, Shawn; Lake, Andrew; Laurens, Philippe; Severini, Horst; Wlodek, Tomasz; Wolff, Stephen; Zurawski, Jason

    2012-01-01

    Global scientific collaborations, such as ATLAS, continue to push the network requirements envelope. Data movement in this collaboration is routinely including the regular exchange of petabytes of datasets between the collection and analysis facilities in the coming years. These requirements place a high emphasis on networks functioning at peak efficiency and availability; the lack thereof could mean critical delays in the overall scientific progress of distributed data-intensive experiments like ATLAS. Network operations staff routinely must deal with problems deep in the infrastructure; this may be as benign as replacing a failing piece of equipment, or as complex as dealing with a multi-domain path that is experiencing data loss. In either case, it is crucial that effective monitoring and performance analysis tools are available to ease the burden of management. We will report on our experiences deploying and using the perfSONAR-PS Performance Toolkit at ATLAS sites in the United States. This software creates a dedicated monitoring server, capable of collecting and performing a wide range of passive and active network measurements. Each independent instance is managed locally, but able to federate on a global scale; enabling a full view of the network infrastructure that spans domain boundaries. This information, available through web service interfaces, can easily be retrieved to create customized applications. The US ATLAS collaboration has developed a centralized “dashboard” offering network administrators, users, and decision makers the ability to see the performance of the network at a glance. The dashboard framework includes the ability to notify users (alarm) when problems are found, thus allowing rapid response to potential problems and making perfSONAR-PS crucial to the operation of our distributed computing infrastructure.

  14. High-performance computing — an overview

    Science.gov (United States)

    Marksteiner, Peter

    1996-08-01

    An overview of high-performance computing (HPC) is given. Different types of computer architectures used in HPC are discussed: vector supercomputers, high-performance RISC processors, various parallel computers like symmetric multiprocessors, workstation clusters, massively parallel processors. Software tools and programming techniques used in HPC are reviewed: vectorizing compilers, optimization and vector tuning, optimization for RISC processors; parallel programming techniques like shared-memory parallelism, message passing and data parallelism; and numerical libraries.

  15. Cyber Attack on Critical Infrastructure and Its Influence on International Security

    OpenAIRE

    出口 雅史

    2017-01-01

     Since the internet appeared, with increasing cyber threats, the vulnerability of critical infrastructure has become a vital issue for international security. Although cyber attack was not lethal in the past, new type of cyber assaults such as stuxnet are able to damage not only computer system digitally, but also critical infrastructure physically. This article will investigate how the recent cyber attacks have threatened critical infrastructure and their influence on international security....

  16. High performance computing in Windows Azure cloud

    OpenAIRE

    Ambruš, Dejan

    2013-01-01

    High performance, security, availability, scalability, flexibility and lower costs of maintenance have essentially contributed to the growing popularity of cloud computing in all spheres of life, especially in business. In fact cloud computing offers even more than this. With usage of virtual computing clusters a runtime environment for high performance computing can be efficiently implemented also in a cloud. There are many advantages but also some disadvantages of cloud computing, some ...

  17. An adaptive process-based cloud infrastructure for space situational awareness applications

    Science.gov (United States)

    Liu, Bingwei; Chen, Yu; Shen, Dan; Chen, Genshe; Pham, Khanh; Blasch, Erik; Rubin, Bruce

    2014-06-01

    Space situational awareness (SSA) and defense space control capabilities are top priorities for groups that own or operate man-made spacecraft. Also, with the growing amount of space debris, there is an increase in demand for contextual understanding that necessitates the capability of collecting and processing a vast amount sensor data. Cloud computing, which features scalable and flexible storage and computing services, has been recognized as an ideal candidate that can meet the large data contextual challenges as needed by SSA. Cloud computing consists of physical service providers and middleware virtual machines together with infrastructure, platform, and software as service (IaaS, PaaS, SaaS) models. However, the typical Virtual Machine (VM) abstraction is on a per operating systems basis, which is at too low-level and limits the flexibility of a mission application architecture. In responding to this technical challenge, a novel adaptive process based cloud infrastructure for SSA applications is proposed in this paper. In addition, the details for the design rationale and a prototype is further examined. The SSA Cloud (SSAC) conceptual capability will potentially support space situation monitoring and tracking, object identification, and threat assessment. Lastly, the benefits of a more granular and flexible cloud computing resources allocation are illustrated for data processing and implementation considerations within a representative SSA system environment. We show that the container-based virtualization performs better than hypervisor-based virtualization technology in an SSA scenario.

  18. Information technology developments within the national biological information infrastructure

    Science.gov (United States)

    Cotter, G.; Frame, M.T.

    2000-01-01

    Looking out an office window or exploring a community park, one can easily see the tremendous challenges that biological information presents the computer science community. Biological information varies in format and content depending whether or not it is information pertaining to a particular species (i.e. Brown Tree Snake), or a specific ecosystem, which often includes multiple species, land use characteristics, and geospatially referenced information. The complexity and uniqueness of each individual species or ecosystem do not easily lend themselves to today's computer science tools and applications. To address the challenges that the biological enterprise presents the National Biological Information Infrastructure (NBII) (http://www.nbii.gov) was established in 1993. The NBII is designed to address these issues on a National scale within the United States, and through international partnerships abroad. This paper discusses current computer science efforts within the National Biological Information Infrastructure Program and future computer science research endeavors that are needed to address the ever-growing issues related to our Nation's biological concerns.

  19. Structures and infrastructures series

    National Research Council Canada - National Science Library

    2008-01-01

    "Research, developments, and applications...on the most advanced techonologies for analyzing, predicting, and optimizing the performance of structures and infrastructures such as buildings, bridges, dams...

  20. FY 1994 Blue Book: High Performance Computing and Communications: Toward a National Information Infrastructure

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — government and industry that advanced computer and telecommunications technologies could provide huge benefits throughout the research community and the entire U.S....

  1. Business Benefits from the Virtualization of an ICT Infrastructure

    Directory of Open Access Journals (Sweden)

    Ivan Pogarcic

    2012-11-01

    Full Text Available Virtualization is a technique that may be encountered in all parts of an ICT infrastructure. The benefits of virtualization for an infrastructure are recognized by a growing number of companies. In this way, virtualization creates prerequisites for the further improvement of the entire information system. Another reason is the growing awareness of environmental issues at the global level, which has become a large external sponsor of this technology. While virtualization technology has been known about for several decades, its hay day is yet to come. In the following years many jobs will be create because of it, from the user desktop and notebook computers, to the server in all businesses. This article examines the impact of virtualization in business enterprises, with emphasis on infrastructure costs and improved business functions. It points to the large savings that can occur even in medium‐sized enterprises. Claims are verifiable quantitative indicators, particularly in the procurement of equipment. It also demonstrates the benefits of virtualization while performing everyday tasks that take place within the IT department. We discuss the correlation of increased flexibility and convenience, and agile response to market demands, while reducing capital and operating costs, and increasing the competitiveness of companies in the market.

  2. COMPUTING

    CERN Multimedia

    M. Kasemann

    Overview In autumn the main focus was to process and handle CRAFT data and to perform the Summer08 MC production. The operational aspects were well covered by regular Computing Shifts, experts on duty and Computing Run Coordination. At the Computing Resource Board (CRB) in October a model to account for service work at Tier 2s was approved. The computing resources for 2009 were reviewed for presentation at the C-RRB. The quarterly resource monitoring is continuing. Facilities/Infrastructure operations Operations during CRAFT data taking ran fine. This proved to be a very valuable experience for T0 workflows and operations. The transfers of custodial data to most T1s went smoothly. A first round of reprocessing started at the Tier-1 centers end of November; it will take about two weeks. The Computing Shifts procedure was tested full scale during this period and proved to be very efficient: 30 Computing Shifts Persons (CSP) and 10 Computing Resources Coordinators (CRC). The shift program for the shut down w...

  3. High Performance Computing Facility Operational Assessment 2015: Oak Ridge Leadership Computing Facility

    Energy Technology Data Exchange (ETDEWEB)

    Barker, Ashley D. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Bernholdt, David E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Bland, Arthur S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Gary, Jeff D. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Hack, James J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; McNally, Stephen T. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Rogers, James H. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Smith, Brian E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Straatsma, T. P. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Sukumar, Sreenivas Rangan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Thach, Kevin G. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Tichenor, Suzy [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Vazhkudai, Sudharshan S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility; Wells, Jack C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility

    2016-03-01

    Oak Ridge National Laboratory’s (ORNL’s) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable systems; creating innovative solutions for high-performance computing (HPC) needs; and managing risks, safety, and security aspects associated with operating one of the most powerful computers in the world. The results can be seen in the cutting-edge science delivered by users and the praise from the research community. Calendar year (CY) 2015 was filled with outstanding operational results and accomplishments: a very high rating from users on overall satisfaction that ties the highest-ever mark set in CY 2014; the greatest number of core-hours delivered to research projects; the largest percentage of capability usage since the OLCF began tracking the metric in 2009; and success in delivering on the allocation of 60, 30, and 10% of core hours offered for the INCITE (Innovative and Novel Computational Impact on Theory and Experiment), ALCC (Advanced Scientific Computing Research Leadership Computing Challenge), and Director’s Discretionary programs, respectively. These accomplishments, coupled with the extremely high utilization rate, represent the fulfillment of the promise of Titan: maximum use by maximum-size simulations. The impact of all of these successes and more is reflected in the accomplishments of OLCF users, with publications this year in notable journals Nature, Nature Materials, Nature Chemistry, Nature Physics, Nature Climate Change, ACS Nano, Journal of the American Chemical Society, and Physical Review Letters, as well as many others. The achievements included in the 2015 OLCF Operational Assessment Report reflect first-ever or largest simulations in their communities; for example Titan enabled engineers in Los Angeles and the surrounding region to design and begin building improved critical infrastructure by enabling the highest-resolution Cybershake map for Southern

  4. Computer technique for evaluating collimator performance

    International Nuclear Information System (INIS)

    Rollo, F.D.

    1975-01-01

    A computer program has been developed to theoretically evaluate the overall performance of collimators used with radioisotope scanners and γ cameras. The first step of the program involves the determination of the line spread function (LSF) and geometrical efficiency from the fundamental parameters of the collimator being evaluated. The working equations can be applied to any plane of interest. The resulting LSF is applied to subroutine computer programs which compute corresponding modulation transfer function and contrast efficiency functions. The latter function is then combined with appropriate geometrical efficiency data to determine the performance index function. The overall computer program allows one to predict from the physical parameters of the collimator alone how well the collimator will reproduce various sized spherical voids of activity in the image plane. The collimator performance program can be used to compare the performance of various collimator types, to study the effects of source depth on collimator performance, and to assist in the design of collimators. The theory of the collimator performance equation is discussed, a comparison between the experimental and theoretical LSF values is made, and examples of the application of the technique are presented

  5. Framework for Computation Offloading in Mobile Cloud Computing

    Directory of Open Access Journals (Sweden)

    Dejan Kovachev

    2012-12-01

    Full Text Available The inherently limited processing power and battery lifetime of mobile phones hinder the possible execution of computationally intensive applications like content-based video analysis or 3D modeling. Offloading of computationally intensive application parts from the mobile platform into a remote cloud infrastructure or nearby idle computers addresses this problem. This paper presents our Mobile Augmentation Cloud Services (MACS middleware which enables adaptive extension of Android application execution from a mobile client into the cloud. Applications are developed by using the standard Android development pattern. The middleware does the heavy lifting of adaptive application partitioning, resource monitoring and computation offloading. These elastic mobile applications can run as usual mobile application, but they can also use remote computing resources transparently. Two prototype applications using the MACS middleware demonstrate the benefits of the approach. The evaluation shows that applications, which involve costly computations, can benefit from offloading with around 95% energy savings and significant performance gains compared to local execution only.

  6. Handling Worldwide LHC Computing Grid Critical Service Incidents : The infrastructure and experience behind nearly 5 years of GGUS ALARMs

    CERN Multimedia

    Dimou, M; Dulov, O; Grein, G

    2013-01-01

    In the Wordwide LHC Computing Grid (WLCG) project the Tier centres are of paramount importance for storing and accessing experiment data and for running the batch jobs necessary for experiment production activities. Although Tier2 sites provide a significant fraction of the resources a non-availability of resources at the Tier0 or the Tier1s can seriously harm not only WLCG Operations but also the experiments' workflow and the storage of LHC data which are very expensive to reproduce. This is why availability requirements for these sites are high and committed in the WLCG Memorandum of Understanding (MoU). In this talk we describe the workflow of GGUS ALARMs, the only 24/7 mechanism available to LHC experiment experts for reporting to the Tier0 or the Tier1s problems with their Critical Services. Conclusions and experience gained from the detailed drills performed in each such ALARM for the last 4 years are explained and the shift with time of Type of Problems met. The physical infrastructure put in place to ...

  7. Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

    Science.gov (United States)

    Johnston, William E.; Gannon, Dennis; Nitzberg, Bill

    2000-01-01

    We use the term "Grid" to refer to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. This infrastructure includes: (1) Tools for constructing collaborative, application oriented Problem Solving Environments / Frameworks (the primary user interfaces for Grids); (2) Programming environments, tools, and services providing various approaches for building applications that use aggregated computing and storage resources, and federated data sources; (3) Comprehensive and consistent set of location independent tools and services for accessing and managing dynamic collections of widely distributed resources: heterogeneous computing systems, storage systems, real-time data sources and instruments, human collaborators, and communications systems; (4) Operational infrastructure including management tools for distributed systems and distributed resources, user services, accounting and auditing, strong and location independent user authentication and authorization, and overall system security services The vision for NASA's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks. Such Grids will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. Examples of these problems include: (1) Coupled, multidisciplinary simulations too large for single systems (e.g., multi-component NPSS turbomachine simulation); (2) Use of widely distributed, federated data archives (e.g., simultaneous access to metrological, topological, aircraft performance, and flight path scheduling databases supporting a National Air Space Simulation systems}; (3

  8. Simulation of cloud data security processes and performance

    OpenAIRE

    Chand, K; Ramachandran, M; Kor, AL

    2015-01-01

    In the world of cloud computing, millions of people are using cloud computing for the purpose of business, education and socialization. Examples of cloud applications are: Google Drive for storage, Facebook for social networks, etc. Cloud users use the cloud computing infrastructure thinking that these services are easy and safe to use. However, there are security and performance issues to be addressed. This paper discusses how cloud users and cloud providers address performance and security ...

  9. Critical infrastructure system security and resiliency

    CERN Document Server

    Biringer, Betty; Warren, Drake

    2013-01-01

    Security protections for critical infrastructure nodes are intended to minimize the risks resulting from an initiating event, whether it is an intentional malevolent act or a natural hazard. With an emphasis on protecting an infrastructure's ability to perform its mission or function, Critical Infrastructure System Security and Resiliency presents a practical methodology for developing an effective protection system that can either prevent undesired events or mitigate the consequences of such events.Developed at Sandia National Labs, the authors' analytical approach and

  10. Progress with the national infrastructure maintenance strategy

    CSIR Research Space (South Africa)

    Wall, K

    2008-07-01

    Full Text Available infrastructure investment and maintenance that will result from this strategy will not only improve infrastructure performance and underpin services sustainability, but will also contribute significantly towards national and local economic growth and will add...

  11. Research and development of fusion grid infrastructure based on atomic energy grid infrastructure (AEGIS)

    International Nuclear Information System (INIS)

    Suzuki, Y.; Nakajima, K.; Kushida, N.; Kino, C.; Aoyagi, T.; Nakajima, N.; Iba, K.; Hayashi, N.; Ozeki, T.; Totsuka, T.; Nakanishi, H.; Nagayama, Y.

    2008-01-01

    In collaboration with the Naka Fusion Institute of Japan Atomic Energy Agency (NFI/JAEA) and the National Institute for Fusion Science of National Institute of Natural Science (NIFS/NINS), Center for Computational Science and E-systems of Japan Atomic Energy Agency (CCSE/JAEA) aims at establishing an integrated framework for experiments and analyses in nuclear fusion research based on the atomic energy grid infrastructure (AEGIS). AEGIS has been being developed by CCSE/JAEA aiming at providing the infrastructure that enables atomic energy researchers in remote locations to carry out R and D efficiently and collaboratively through the Internet. Toward establishing the integrated framework, we have been applying AEGIS to pre-existing three systems: experiment system, remote data acquisition system, and integrated analysis system. For the experiment system, the secure remote experiment system with JT-60 has been successfully accomplished. For the remote data acquisition system, it will be possible to equivalently operate experimental data obtained from LHD data acquisition and management system (LABCOM system) and JT-60 Data System. The integrated analysis system has been extended to the system executable in heterogeneous computers among institutes

  12. Technologies and tools for high-performance distributed computing. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Karonis, Nicholas T.

    2000-05-01

    In this project we studied the practical use of the MPI message-passing interface in advanced distributed computing environments. We built on the existing software infrastructure provided by the Globus Toolkit{trademark}, the MPICH portable implementation of MPI, and the MPICH-G integration of MPICH with Globus. As a result of this project we have replaced MPICH-G with its successor MPICH-G2, which is also an integration of MPICH with Globus. MPICH-G2 delivers significant improvements in message passing performance when compared to its predecessor MPICH-G and was based on superior software design principles resulting in a software base that was much easier to make the functional extensions and improvements we did. Using Globus services we replaced the default implementation of MPI's collective operations in MPICH-G2 with more efficient multilevel topology-aware collective operations which, in turn, led to the development of a new timing methodology for broadcasts [8]. MPICH-G2 was extended to include client/server functionality from the MPI-2 standard [23] to facilitate remote visualization applications and, through the use of MPI idioms, MPICH-G2 provided application-level control of quality-of-service parameters as well as application-level discovery of underlying Grid-topology information. Finally, MPICH-G2 was successfully used in a number of applications including an award-winning record-setting computation in numerical relativity. In the sections that follow we describe in detail the accomplishments of this project, we present experimental results quantifying the performance improvements, and conclude with a discussion of our applications experiences. This project resulted in a significant increase in the utility of MPICH-G2.

  13. High performance computing in power and energy systems

    Energy Technology Data Exchange (ETDEWEB)

    Khaitan, Siddhartha Kumar [Iowa State Univ., Ames, IA (United States); Gupta, Anshul (eds.) [IBM Watson Research Center, Yorktown Heights, NY (United States)

    2013-07-01

    The twin challenge of meeting global energy demands in the face of growing economies and populations and restricting greenhouse gas emissions is one of the most daunting ones that humanity has ever faced. Smart electrical generation and distribution infrastructure will play a crucial role in meeting these challenges. We would need to develop capabilities to handle large volumes of data generated by the power system components like PMUs, DFRs and other data acquisition devices as well as by the capacity to process these data at high resolution via multi-scale and multi-period simulations, cascading and security analysis, interaction between hybrid systems (electric, transport, gas, oil, coal, etc.) and so on, to get meaningful information in real time to ensure a secure, reliable and stable power system grid. Advanced research on development and implementation of market-ready leading-edge high-speed enabling technologies and algorithms for solving real-time, dynamic, resource-critical problems will be required for dynamic security analysis targeted towards successful implementation of Smart Grid initiatives. This books aims to bring together some of the latest research developments as well as thoughts on the future research directions of the high performance computing applications in electric power systems planning, operations, security, markets, and grid integration of alternate sources of energy, etc.

  14. LCA as a Tool to Evaluate Green Infrastructure's Environmental Performance

    Science.gov (United States)

    Catalano De Sousa, M.; Erispaha, A.; Spatari, S.; Montalto, F.

    2011-12-01

    Decentralized approaches to managing urban stormwater through use of green infrastructure (GI) often lead to system-wide efficiency gains within the urban watershed's energy supply system. These efficiencies lead to direct greenhouse gas (GHG) emissions savings, and also restore some ecosystem functions within the urban landscape. We developed a consequential life cycle assessment (LCA) model to estimate the life cycle energy, global warming potential (GWP), and payback times for each if GI were applied within a select neighborhood in New York City. We applied the SIMAPRO LCA software and the economic input-output LCA (EIO-LCA) tool developed by Carnegie Mellon University. The results showed that for a new intersection installation highlighted in this study a conventional infrastructure construction would emit and use approximately 3 times more for both CO2 and energy than a design using GI. Two GI benefits were analyzed with regards to retrofitting the existing intersection. The first was related to the savings in energy and CO2 at the Waste Water Treatment Plant via runoff reduction accrued from GI use. The second benefit was related to the avoided environmental costs associated with an additional new grey infrastructure installation needed to prevent CSO in case of no GI implementation. The first benefit indicated a high payback time for a GI installation in terms of CO2 and energy demand (80 and 90 years respectively) and suggest a slow energy and carbon recovery time. However, concerning to the second benefit, GI proved to be a sustainable alternative considering the high CO2 releases (429 MTE) and energy demand (5.5 TJ) associated with a grey infrastructure construction.

  15. The NCI High Performance Computing (HPC) and High Performance Data (HPD) Platform to Support the Analysis of Petascale Environmental Data Collections

    Science.gov (United States)

    Evans, B. J. K.; Pugh, T.; Wyborn, L. A.; Porter, D.; Allen, C.; Smillie, J.; Antony, J.; Trenham, C.; Evans, B. J.; Beckett, D.; Erwin, T.; King, E.; Hodge, J.; Woodcock, R.; Fraser, R.; Lescinsky, D. T.

    2014-12-01

    The National Computational Infrastructure (NCI) has co-located a priority set of national data assets within a HPC research platform. This powerful in-situ computational platform has been created to help serve and analyse the massive amounts of data across the spectrum of environmental collections - in particular the climate, observational data and geoscientific domains. This paper examines the infrastructure, innovation and opportunity for this significant research platform. NCI currently manages nationally significant data collections (10+ PB) categorised as 1) earth system sciences, climate and weather model data assets and products, 2) earth and marine observations and products, 3) geosciences, 4) terrestrial ecosystem, 5) water management and hydrology, and 6) astronomy, social science and biosciences. The data is largely sourced from the NCI partners (who include the custodians of many of the national scientific records), major research communities, and collaborating overseas organisations. By co-locating these large valuable data assets, new opportunities have arisen by harmonising the data collections, making a powerful transdisciplinary research platformThe data is accessible within an integrated HPC-HPD environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large scale and high-bandwidth Lustre filesystems. New scientific software, cloud-scale techniques, server-side visualisation and data services have been harnessed and integrated into the platform, so that analysis is performed seamlessly across the traditional boundaries of the underlying data domains. Characterisation of the techniques along with performance profiling ensures scalability of each software component, all of which can either be enhanced or replaced through future improvements. A Development-to-Operations (DevOps) framework has also been implemented to manage the scale of the software complexity alone. This ensures that

  16. Configuration Management and Infrastructure Monitoring Using CFEngine and Icinga for Real-time Heterogeneous Data Taking Environment

    Science.gov (United States)

    Poat, M. D.; Lauret, J.; Betts, W.

    2015-12-01

    The STAR online computing environment is an intensive ever-growing system used for real-time data collection and analysis. Composed of heterogeneous and sometimes groups of custom-tuned machines, the computing infrastructure was previously managed by manual configurations and inconsistently monitored by a combination of tools. This situation led to configuration inconsistency and an overload of repetitive tasks along with lackluster communication between personnel and machines. Globally securing this heterogeneous cyberinfrastructure was tedious at best and an agile, policy-driven system ensuring consistency, was pursued. Three configuration management tools, Chef, Puppet, and CFEngine have been compared in reliability, versatility and performance along with a comparison of infrastructure monitoring tools Nagios and Icinga. STAR has selected the CFEngine configuration management tool and the Icinga infrastructure monitoring system leading to a versatile and sustainable solution. By leveraging these two tools STAR can now swiftly upgrade and modify the environment to its needs with ease as well as promptly react to cyber-security requests. By creating a sustainable long term monitoring solution, the detection of failures was reduced from days to minutes, allowing rapid actions before the issues become dire problems, potentially causing loss of precious experimental data or uptime.

  17. Event heap: a coordination infrastructure for dynamic heterogeneous application interactions in ubiquitous computing environments

    Science.gov (United States)

    Johanson, Bradley E.; Fox, Armando; Winograd, Terry A.; Hanrahan, Patrick M.

    2010-04-20

    An efficient and adaptive middleware infrastructure called the Event Heap system dynamically coordinates application interactions and communications in a ubiquitous computing environment, e.g., an interactive workspace, having heterogeneous software applications running on various machines and devices across different platforms. Applications exchange events via the Event Heap. Each event is characterized by a set of unordered, named fields. Events are routed by matching certain attributes in the fields. The source and target versions of each field are automatically set when an event is posted or used as a template. The Event Heap system implements a unique combination of features, both intrinsic to tuplespaces and specific to the Event Heap, including content based addressing, support for routing patterns, standard routing fields, limited data persistence, query persistence/registration, transparent communication, self-description, flexible typing, logical/physical centralization, portable client API, at most once per source first-in-first-out ordering, and modular restartability.

  18. Development of multi-functional streetscape green infrastructure using a performance index approach.

    Science.gov (United States)

    Tiwary, A; Williams, I D; Heidrich, O; Namdeo, A; Bandaru, V; Calfapietra, C

    2016-01-01

    This paper presents a performance evaluation framework for streetscape vegetation. A performance index (PI) is conceived using the following seven traits, specific to the street environments - Pollution Flux Potential (PFP), Carbon Sequestration Potential (CSP), Thermal Comfort Potential (TCP), Noise Attenuation Potential (NAP), Biomass Energy Potential (BEP), Environmental Stress Tolerance (EST) and Crown Projection Factor (CPF). Its application is demonstrated through a case study using fifteen street vegetation species from the UK, utilising a combination of direct field measurements and inventoried literature data. Our results indicate greater preference to small-to-medium size trees and evergreen shrubs over larger trees for streetscaping. The proposed PI approach can be potentially applied two-fold: one, for evaluation of the performance of the existing street vegetation, facilitating the prospects for further improving them through management strategies and better species selection; two, for planning new streetscapes and multi-functional biomass as part of extending the green urban infrastructure. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. METHODS FOR IMPROVING AVAILABILITY AND EFFICIENCY OF COMPUTER INFRASTRUCTURE IN SMART CITIES

    Directory of Open Access Journals (Sweden)

    Jerzy Balicki

    2017-09-01

    Full Text Available This paper discusses methods for increasing the availability and efficiency of information infrastructure in smart cities. Two criteria have been formulated to assign some key resources in smart city system. The process of finding some compromise solutions from Pareto-optimal solutions has been illustrated. Metaheuristics of collective intelligence, including particle swarm optimization PSO, ant colony optimization ACO, algorithm of bee colony ABC, and differential evolution DE have been described due to smart city infrastructure improving. Other application of above metaheuristics in smart city have been also presented.

  20. High Performance Computing in Science and Engineering '02 : Transactions of the High Performance Computing Center

    CERN Document Server

    Jäger, Willi

    2003-01-01

    This book presents the state-of-the-art in modeling and simulation on supercomputers. Leading German research groups present their results achieved on high-end systems of the High Performance Computing Center Stuttgart (HLRS) for the year 2002. Reports cover all fields of supercomputing simulation ranging from computational fluid dynamics to computer science. Special emphasis is given to industrially relevant applications. Moreover, by presenting results for both vector sytems and micro-processor based systems the book allows to compare performance levels and usability of a variety of supercomputer architectures. It therefore becomes an indispensable guidebook to assess the impact of the Japanese Earth Simulator project on supercomputing in the years to come.

  1. Resilient workflows for computational mechanics platforms

    Science.gov (United States)

    Nguyên, Toàn; Trifan, Laurentiu; Désidéri, Jean-Antoine

    2010-06-01

    Workflow management systems have recently been the focus of much interest and many research and deployment for scientific applications worldwide [26, 27]. Their ability to abstract the applications by wrapping application codes have also stressed the usefulness of such systems for multidiscipline applications [23, 24]. When complex applications need to provide seamless interfaces hiding the technicalities of the computing infrastructures, their high-level modeling, monitoring and execution functionalities help giving production teams seamless and effective facilities [25, 31, 33]. Software integration infrastructures based on programming paradigms such as Python, Mathlab and Scilab have also provided evidence of the usefulness of such approaches for the tight coupling of multidisciplne application codes [22, 24]. Also high-performance computing based on multi-core multi-cluster infrastructures open new opportunities for more accurate, more extensive and effective robust multi-discipline simulations for the decades to come [28]. This supports the goal of full flight dynamics simulation for 3D aircraft models within the next decade, opening the way to virtual flight-tests and certification of aircraft in the future [23, 24, 29].

  2. CLIMB (the Cloud Infrastructure for Microbial Bioinformatics): an online resource for the medical microbiology community.

    Science.gov (United States)

    Connor, Thomas R; Loman, Nicholas J; Thompson, Simon; Smith, Andy; Southgate, Joel; Poplawski, Radoslaw; Bull, Matthew J; Richardson, Emily; Ismail, Matthew; Thompson, Simon Elwood-; Kitchen, Christine; Guest, Martyn; Bakke, Marius; Sheppard, Samuel K; Pallen, Mark J

    2016-09-01

    The increasing availability and decreasing cost of high-throughput sequencing has transformed academic medical microbiology, delivering an explosion in available genomes while also driving advances in bioinformatics. However, many microbiologists are unable to exploit the resulting large genomics datasets because they do not have access to relevant computational resources and to an appropriate bioinformatics infrastructure. Here, we present the Cloud Infrastructure for Microbial Bioinformatics (CLIMB) facility, a shared computing infrastructure that has been designed from the ground up to provide an environment where microbiologists can share and reuse methods and data.

  3. Performing an allreduce operation on a plurality of compute nodes of a parallel computer

    Science.gov (United States)

    Faraj, Ahmad [Rochester, MN

    2012-04-17

    Methods, apparatus, and products are disclosed for performing an allreduce operation on a plurality of compute nodes of a parallel computer. Each compute node includes at least two processing cores. Each processing core has contribution data for the allreduce operation. Performing an allreduce operation on a plurality of compute nodes of a parallel computer includes: establishing one or more logical rings among the compute nodes, each logical ring including at least one processing core from each compute node; performing, for each logical ring, a global allreduce operation using the contribution data for the processing cores included in that logical ring, yielding a global allreduce result for each processing core included in that logical ring; and performing, for each compute node, a local allreduce operation using the global allreduce results for each processing core on that compute node.

  4. Secure Enclaves: An Isolation-centric Approach for Creating Secure High Performance Computing Environments

    Energy Technology Data Exchange (ETDEWEB)

    Aderholdt, Ferrol [Tennessee Technological Univ., Cookeville, TN (United States); Caldwell, Blake A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hicks, Susan Elaine [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Koch, Scott M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Naughton, III, Thomas J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Pelfrey, Daniel S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Pogge, James R [Tennessee Technological Univ., Cookeville, TN (United States); Scott, Stephen L [Tennessee Technological Univ., Cookeville, TN (United States); Shipman, Galen M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Sorrillo, Lawrence [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-01-01

    High performance computing environments are often used for a wide variety of workloads ranging from simulation, data transformation and analysis, and complex workflows to name just a few. These systems may process data at various security levels but in so doing are often enclaved at the highest security posture. This approach places significant restrictions on the users of the system even when processing data at a lower security level and exposes data at higher levels of confidentiality to a much broader population than otherwise necessary. The traditional approach of isolation, while effective in establishing security enclaves poses significant challenges for the use of shared infrastructure in HPC environments. This report details current state-of-the-art in virtualization, reconfigurable network enclaving via Software Defined Networking (SDN), and storage architectures and bridging techniques for creating secure enclaves in HPC environments.

  5. N2R vs. DR Network Infrastructure Evaluation

    DEFF Research Database (Denmark)

    Pedersen, Jens Myrup; Roost, Lars Jessen; Toft, Per Nesager

    2007-01-01

    Recent development of Internet-based services has set higher requirements to network infrastructures in terms of more bandwidth, lower delays and more reliability. Theoretical research within the area of Structural Quality of Service (SQoS) has introduced a new type of infrastructure which meet...... these requirements: N2R infrastructures. This paper contributes to the ongoing research with a case study from North Jutland. An evaluation of three N2R infrastructures compared to a Double Ring (DR) infrastructure will provide valuable information of the practical applicability of N2R infrastructures. In order...... to study if N2R infrastructures perform better than the DR infrastructure, a distribution network was established based on geographical information system (GIS) data. Nodes were placed with respect to demographic and geographical factors. The established distribution network was investigated with respect...

  6. Infrastructure and Economic Development in Sub-Saharan Africa

    OpenAIRE

    Calderón, César; Servén, Luis

    2008-01-01

    An adequate supply of infrastructure services has long been viewed by both academics and policy makers as a key ingredient for economic development. Sub-Saharan Africa ranks consistently at the bottom of all developing regions in terms of infrastructure performance, and an increasing number of observers point to deficient infrastructure as a major obstacle for growth and poverty reduction ...

  7. Contemporary high performance computing from petascale toward exascale

    CERN Document Server

    Vetter, Jeffrey S

    2013-01-01

    Contemporary High Performance Computing: From Petascale toward Exascale focuses on the ecosystems surrounding the world's leading centers for high performance computing (HPC). It covers many of the important factors involved in each ecosystem: computer architectures, software, applications, facilities, and sponsors. The first part of the book examines significant trends in HPC systems, including computer architectures, applications, performance, and software. It discusses the growth from terascale to petascale computing and the influence of the TOP500 and Green500 lists. The second part of the

  8. Agile infrastructure monitoring

    International Nuclear Information System (INIS)

    Andrade, P; Ascenso, J; Fedorko, I; Fiorini, B; Paladin, M; Pigueiras, L; Santos, M

    2014-01-01

    At the present time, data centres are facing a massive rise in virtualisation and cloud computing. The Agile Infrastructure (AI) project is working to deliver new solutions to ease the management of CERN data centres. Part of the solution consists in a new 'shared monitoring architecture' which collects and manages monitoring data from all data centre resources. In this article, we present the building blocks of this new monitoring architecture, the different open source technologies selected for each architecture layer, and how we are building a community around this common effort.

  9. Commissioning the CERN IT Agile Infrastructure with experiment workloads

    CERN Document Server

    Medrano Llamas, Ramón; Kucharczyk, Katarzyna; Denis, Marek Kamil; Cinquilli, Mattia

    2014-01-01

    In order to ease the management of their infrastructure, most of the WLCG sites are adopting cloud based strategies. In the case of CERN, the Tier 0 of the WLCG, is completely restructuring the resource and configuration management of their computing center under the codename Agile Infrastructure. Its goal is to manage 15,000 Virtual Machines by means of an OpenStack middleware in order to unify all the resources in CERN's two datacenters: the one placed in Meyrin and the new on in Wigner, Hungary. During the commissioning of this infrastructure, CERN IT is offering an attractive amount of computing resources to the experiments (800 cores for ATLAS and CMS) through a private cloud interface. ATLAS and CMS have joined forces to exploit them by running stress tests and simulation workloads since November 2012. This work will describe the experience of the first deployments of the current experiment workloads on the CERN private cloud testbed. The paper is organized as follows: the first section will explain th...

  10. MOBBED: a computational data infrastructure for handling large collections of event-rich time series datasets in MATLAB.

    Science.gov (United States)

    Cockfield, Jeremy; Su, Kyungmin; Robbins, Kay A

    2013-01-01

    Experiments to monitor human brain activity during active behavior record a variety of modalities (e.g., EEG, eye tracking, motion capture, respiration monitoring) and capture a complex environmental context leading to large, event-rich time series datasets. The considerable variability of responses within and among subjects in more realistic behavioral scenarios requires experiments to assess many more subjects over longer periods of time. This explosion of data requires better computational infrastructure to more systematically explore and process these collections. MOBBED is a lightweight, easy-to-use, extensible toolkit that allows users to incorporate a computational database into their normal MATLAB workflow. Although capable of storing quite general types of annotated data, MOBBED is particularly oriented to multichannel time series such as EEG that have event streams overlaid with sensor data. MOBBED directly supports access to individual events, data frames, and time-stamped feature vectors, allowing users to ask questions such as what types of events or features co-occur under various experimental conditions. A database provides several advantages not available to users who process one dataset at a time from the local file system. In addition to archiving primary data in a central place to save space and avoid inconsistencies, such a database allows users to manage, search, and retrieve events across multiple datasets without reading the entire dataset. The database also provides infrastructure for handling more complex event patterns that include environmental and contextual conditions. The database can also be used as a cache for expensive intermediate results that are reused in such activities as cross-validation of machine learning algorithms. MOBBED is implemented over PostgreSQL, a widely used open source database, and is freely available under the GNU general public license at http://visual.cs.utsa.edu/mobbed. Source and issue reports for MOBBED

  11. Analytical Hierarchy Process for the selection of strategic alternatives for introduction of infrastructure virtual desktop infrastructure in the university

    Directory of Open Access Journals (Sweden)

    Katerina A. Makoviy

    2017-12-01

    Full Text Available The task of choosing a strategy for implementing the virtual desktop infrastructure into the IT infrastructure of the university is considered. The infrastructure of virtual desktops is a technology that provides centralization of management of client workplaces, increase the service life of computers in classrooms. The analysis of strengths and weaknesses, threats and opportunities for introducing virtualization in the university. Alternatives to implementation based on the results of the pilot project have been developed. To obtain quantitative estimates in the SWOT - analysis of the pilot project, the analytical hierarchy process is used. The analysis of implementation of the pilot project by experts is carried out and the integral value of quantitative estimates of various alternatives is generated. The combination of the analytical hierarchy process and SWOT - analysis allows you to choose the optimal strategy for implementing desktop virtualization.

  12. Management of virtualized infrastructure for physics databases

    International Nuclear Information System (INIS)

    Topurov, Anton; Gallerani, Luigi; Chatal, Francois; Piorkowski, Mariusz

    2012-01-01

    Demands for information storage of physics metadata are rapidly increasing together with the requirements for its high availability. Most of the HEP laboratories are struggling to squeeze more from their computer centers, thus focus on virtualizing available resources. CERN started investigating database virtualization in early 2006, first by testing database performance and stability on native Xen. Since then we have been closely evaluating the constantly evolving functionality of virtualisation solutions for database and middle tier together with the associated management applications – Oracle's Enterprise Manager and VM Manager. This session will detail our long experience in dealing with virtualized environments, focusing on newest Oracle OVM 3.0 for x86 and Oracle Enterprise Manager functionality for efficiently managing your virtualized database infrastructure.

  13. Security infrastructure for dynamically provisioned cloud infrastructure services

    NARCIS (Netherlands)

    Demchenko, Y.; Ngo, C.; de Laat, C.; Lopez, D.R.; Morales, A.; García-Espín, J.A.; Pearson, S.; Yee, G.

    2013-01-01

    This chapter discusses conceptual issues, basic requirements and practical suggestions for designing dynamically configured security infrastructure provisioned on demand as part of the cloud-based infrastructure. This chapter describes general use cases for provisioning cloud infrastructure services

  14. Lean computing for the cloud

    CERN Document Server

    Bauer, Eric

    2016-01-01

    Applies lean manufacturing principles across the cloud service delivery chain to enable application and infrastructure service providers to sustainably achieve the shortest lead time, best quality, and value This book focuses on lean in the context of cloud computing capacity management of applications and the physical and virtual cloud resources that support them. Lean Computing for the Cloud considers business, architectural and operational aspects of efficiently delivering valuable services to end users via cloud-based applications hosted on shared cloud infrastructure. The work also focuses on overall optimization of the service delivery chain to enable both application service and infrastructure service providers to adopt leaner, demand driven operations to serve end users more efficiently. The book’s early chapters analyze how capacity management morphs with cloud computing into interlocked physical infrastructure capacity management, virtual resou ce capacity management, and application capacity ma...

  15. Cloud Computing and Its Applications in GIS

    Science.gov (United States)

    Kang, Cao

    2011-12-01

    Cloud computing is a novel computing paradigm that offers highly scalable and highly available distributed computing services. The objectives of this research are to: 1. analyze and understand cloud computing and its potential for GIS; 2. discover the feasibilities of migrating truly spatial GIS algorithms to distributed computing infrastructures; 3. explore a solution to host and serve large volumes of raster GIS data efficiently and speedily. These objectives thus form the basis for three professional articles. The first article is entitled "Cloud Computing and Its Applications in GIS". This paper introduces the concept, structure, and features of cloud computing. Features of cloud computing such as scalability, parallelization, and high availability make it a very capable computing paradigm. Unlike High Performance Computing (HPC), cloud computing uses inexpensive commodity computers. The uniform administration systems in cloud computing make it easier to use than GRID computing. Potential advantages of cloud-based GIS systems such as lower barrier to entry are consequently presented. Three cloud-based GIS system architectures are proposed: public cloud- based GIS systems, private cloud-based GIS systems and hybrid cloud-based GIS systems. Public cloud-based GIS systems provide the lowest entry barriers for users among these three architectures, but their advantages are offset by data security and privacy related issues. Private cloud-based GIS systems provide the best data protection, though they have the highest entry barriers. Hybrid cloud-based GIS systems provide a compromise between these extremes. The second article is entitled "A cloud computing algorithm for the calculation of Euclidian distance for raster GIS". Euclidean distance is a truly spatial GIS algorithm. Classical algorithms such as the pushbroom and growth ring techniques require computational propagation through the entire raster image, which makes it incompatible with the distributed nature

  16. Research Activity in Computational Physics utilizing High Performance Computing: Co-authorship Network Analysis

    Science.gov (United States)

    Ahn, Sul-Ah; Jung, Youngim

    2016-10-01

    The research activities of the computational physicists utilizing high performance computing are analyzed by bibliometirc approaches. This study aims at providing the computational physicists utilizing high-performance computing and policy planners with useful bibliometric results for an assessment of research activities. In order to achieve this purpose, we carried out a co-authorship network analysis of journal articles to assess the research activities of researchers for high-performance computational physics as a case study. For this study, we used journal articles of the Scopus database from Elsevier covering the time period of 2004-2013. We extracted the author rank in the physics field utilizing high-performance computing by the number of papers published during ten years from 2004. Finally, we drew the co-authorship network for 45 top-authors and their coauthors, and described some features of the co-authorship network in relation to the author rank. Suggestions for further studies are discussed.

  17. Tackling some of the most intricate geophysical challenges via high-performance computing

    Science.gov (United States)

    Khosronejad, A.

    2016-12-01

    Recently, world has been witnessing significant enhancements in computing power of supercomputers. Computer clusters in conjunction with the advanced mathematical algorithms has set the stage for developing and applying powerful numerical tools to tackle some of the most intricate geophysical challenges that today`s engineers face. One such challenge is to understand how turbulent flows, in real-world settings, interact with (a) rigid and/or mobile complex bed bathymetry of waterways and sea-beds in the coastal areas; (b) objects with complex geometry that are fully or partially immersed; and (c) free-surface of waterways and water surface waves in the coastal area. This understanding is especially important because the turbulent flows in real-world environments are often bounded by geometrically complex boundaries, which dynamically deform and give rise to multi-scale and multi-physics transport phenomena, and characterized by multi-lateral interactions among various phases (e.g. air/water/sediment phases). Herein, I present some of the multi-scale and multi-physics geophysical fluid mechanics processes that I have attempted to study using an in-house high-performance computational model, the so-called VFS-Geophysics. More specifically, I will present the simulation results of turbulence/sediment/solute/turbine interactions in real-world settings. Parts of the simulations I present are performed to gain scientific insights into the processes such as sand wave formation (A. Khosronejad, and F. Sotiropoulos, (2014), Numerical simulation of sand waves in a turbulent open channel flow, Journal of Fluid Mechanics, 753:150-216), while others are carried out to predict the effects of climate change and large flood events on societal infrastructures ( A. Khosronejad, et al., (2016), Large eddy simulation of turbulence and solute transport in a forested headwater stream, Journal of Geophysical Research:, doi: 10.1002/2014JF003423).

  18. Computational performance of a smoothed particle hydrodynamics simulation for shared-memory parallel computing

    Science.gov (United States)

    Nishiura, Daisuke; Furuichi, Mikito; Sakaguchi, Hide

    2015-09-01

    The computational performance of a smoothed particle hydrodynamics (SPH) simulation is investigated for three types of current shared-memory parallel computer devices: many integrated core (MIC) processors, graphics processing units (GPUs), and multi-core CPUs. We are especially interested in efficient shared-memory allocation methods for each chipset, because the efficient data access patterns differ between compute unified device architecture (CUDA) programming for GPUs and OpenMP programming for MIC processors and multi-core CPUs. We first introduce several parallel implementation techniques for the SPH code, and then examine these on our target computer architectures to determine the most effective algorithms for each processor unit. In addition, we evaluate the effective computing performance and power efficiency of the SPH simulation on each architecture, as these are critical metrics for overall performance in a multi-device environment. In our benchmark test, the GPU is found to produce the best arithmetic performance as a standalone device unit, and gives the most efficient power consumption. The multi-core CPU obtains the most effective computing performance. The computational speed of the MIC processor on Xeon Phi approached that of two Xeon CPUs. This indicates that using MICs is an attractive choice for existing SPH codes on multi-core CPUs parallelized by OpenMP, as it gains computational acceleration without the need for significant changes to the source code.

  19. Towards higher reliability of CMS computing facilities

    International Nuclear Information System (INIS)

    Bagliesi, G; Bloom, K; Brew, C; Flix, J; Kreuzer, P; Sciabà, A

    2012-01-01

    The CMS experiment has adopted a computing system where resources are distributed worldwide in more than 50 sites. The operation of the system requires a stable and reliable behaviour of the underlying infrastructure. CMS has established procedures to extensively test all relevant aspects of a site and their capability to sustain the various CMS computing workflows at the required scale. The Site Readiness monitoring infrastructure has been instrumental in understanding how the system as a whole was improving towards LHC operations, measuring the reliability of sites when running CMS activities, and providing sites with the information they need to troubleshoot any problem. This contribution reviews the complete automation of the Site Readiness program, with the description of monitoring tools and their inclusion into the Site Status Board (SSB), the performance checks, the use of tools like HammerCloud, and the impact in improving the overall reliability of the Grid from the point of view of the CMS computing system. These results are used by CMS to select good sites to conduct workflows, in order to maximize workflows efficiencies. The performance against these tests seen at the sites during the first years of LHC running is as well reviewed.

  20. AUTOMATION OF CALCULATION ALGORITHMS FOR EFFICIENCY ESTIMATION OF TRANSPORT INFRASTRUCTURE DEVELOPMENT

    Directory of Open Access Journals (Sweden)

    Sergey Kharitonov

    2015-06-01

    Full Text Available Optimum transport infrastructure usage is an important aspect of the development of the national economy of the Russian Federation. Thus, development of instruments for assessing the efficiency of infrastructure is impossible without constant monitoring of a number of significant indicators. This work is devoted to the selection of indicators and the method of their calculation in relation to the transport subsystem as airport infrastructure. The work also reflects aspects of the evaluation of the possibilities of algorithmic computational mechanisms to improve the tools of public administration transport subsystems.

  1. A GRID solution for gravitational waves signal analysis from coalescing binaries: performances of test algorithms and further developments

    International Nuclear Information System (INIS)

    Acernese, A; Barone, F; Rosa, R De; Esposito, R; Frasca, S; Mastroserio, P; Milano, L; Palomba, C; Pardi, S; Qipiani, K; Ricci, F; Russo, G

    2004-01-01

    The analysis of data coming from interferometric antennas for gravitational wave detection requires a huge amount of computing power. The usual approach to the detection strategy is to set up computer farms able to perform several tasks in parallel, exchanging data through network links. In this paper a new computation strategy based on the GRID environment, is presented. The GRID environment allows several geographically distributed computing resources to exchange data and programs in a secure way, using standard infrastructures. The computing resources can be geographically distributed also on a large scale. Some preliminary tests were performed using a subnetwork of the GRID infrastructure, producing good results in terms of distribution efficiency and time duration

  2. High-performance computing for airborne applications

    International Nuclear Information System (INIS)

    Quinn, Heather M.; Manuzatto, Andrea; Fairbanks, Tom; Dallmann, Nicholas; Desgeorges, Rose

    2010-01-01

    Recently, there has been attempts to move common satellite tasks to unmanned aerial vehicles (UAVs). UAVs are significantly cheaper to buy than satellites and easier to deploy on an as-needed basis. The more benign radiation environment also allows for an aggressive adoption of state-of-the-art commercial computational devices, which increases the amount of data that can be collected. There are a number of commercial computing devices currently available that are well-suited to high-performance computing. These devices range from specialized computational devices, such as field-programmable gate arrays (FPGAs) and digital signal processors (DSPs), to traditional computing platforms, such as microprocessors. Even though the radiation environment is relatively benign, these devices could be susceptible to single-event effects. In this paper, we will present radiation data for high-performance computing devices in a accelerated neutron environment. These devices include a multi-core digital signal processor, two field-programmable gate arrays, and a microprocessor. From these results, we found that all of these devices are suitable for many airplane environments without reliability problems.

  3. INFRASTRUCTURE

    CERN Multimedia

    A. Gaddi

    2012-01-01

    The CMS Infrastructures teams are constantly ensuring the smooth operation of the different services during this critical period when the detector is taking data at full speed. A single failure would spoil hours of high luminosity beam and everything is put in place to avoid such an eventuality. In the meantime however, the fast approaching LS1 requires that we take a look at the various activities to take place from the end of the year onwards. The list of infrastructures consolidation and upgrade tasks is already long and will touch all the services (cooling, gas, inertion, powering, etc.). The definitive list will be available just before the LS1 start. One activity performed by the CMS cooling team that is worth mentioning is the maintenance of the cooling circuits at the CMS Electronics Integration Centre (EIC) at building 904. The old chiller has been replaced by a three-units cooling plant that also serves the HVAC system for the new CSC and RPC factories. The commissioning of this new plant has tak...

  4. SCinet Architecture: Featured at the International Conference for High Performance Computing,Networking, Storage and Analysis 2016

    Energy Technology Data Exchange (ETDEWEB)

    Lyonnais, Marc; Smith, Matt; Mace, Kate P.

    2017-02-06

    SCinet is the purpose-built network that operates during the International Conference for High Performance Computing,Networking, Storage and Analysis (Super Computing or SC). Created each year for the conference, SCinet brings to life a high-capacity network that supports applications and experiments that are a hallmark of the SC conference. The network links the convention center to research and commercial networks around the world. This resource serves as a platform for exhibitors to demonstrate the advanced computing resources of their home institutions and elsewhere by supporting a wide variety of applications. Volunteers from academia, government and industry work together to design and deliver the SCinet infrastructure. Industry vendors and carriers donate millions of dollars in equipment and services needed to build and support the local and wide area networks. Planning begins more than a year in advance of each SC conference and culminates in a high intensity installation in the days leading up to the conference. The SCinet architecture for SC16 illustrates a dramatic increase in participation from the vendor community, particularly those that focus on network equipment. Software-Defined Networking (SDN) and Data Center Networking (DCN) are present in nearly all aspects of the design.

  5. Executable research compendia in geoscience research infrastructures

    Science.gov (United States)

    Nüst, Daniel

    2017-04-01

    From generation through analysis and collaboration to communication, scientific research requires the right tools. Scientists create their own software using third party libraries and platforms. Cloud computing, Open Science, public data infrastructures, and Open Source enable scientists with unprecedented opportunites, nowadays often in a field "Computational X" (e.g. computational seismology) or X-informatics (e.g. geoinformatics) [0]. This increases complexity and generates more innovation, e.g. Environmental Research Infrastructures (environmental RIs [1]). Researchers in Computational X write their software relying on both source code (e.g. from https://github.com) and binary libraries (e.g. from package managers such as APT, https://wiki.debian.org/Apt, or CRAN, https://cran.r-project.org/). They download data from domain specific (cf. https://re3data.org) or generic (e.g. https://zenodo.org) data repositories, and deploy computations remotely (e.g. European Open Science Cloud). The results themselves are archived, given persistent identifiers, connected to other works (e.g. using https://orcid.org/), and listed in metadata catalogues. A single researcher, intentionally or not, interacts with all sub-systems of RIs: data acquisition, data access, data processing, data curation, and community support [3]. To preserve computational research [3] proposes the Executable Research Compendium (ERC), a container format closing the gap of dependency preservation by encapsulating the runtime environment. ERCs and RIs can be integrated for different uses: (i) Coherence: ERC services validate completeness, integrity and results (ii) Metadata: ERCs connect the different parts of a piece of research and faciliate discovery (iii) Exchange and Preservation: ERC as usable building blocks are the shared and archived entity (iv) Self-consistency: ERCs remove dependence on ephemeral sources (v) Execution: ERC services create and execute a packaged analysis but integrate with

  6. Evolution of the ATLAS data and computing model for a Tier2 in the EGI infrastructure

    CERN Document Server

    Fernández Casaní, A; The ATLAS collaboration; González de la Hoz, S; Salt Cairols, J; Fassi, F; Kaci, M; Lamas, A; Oliver, E; Sánchez, J; Sánchez, V

    2012-01-01

    Since the start of the LHC pp collisions in 2010, the ATLAS computing model has moved from a more strict design, where every Tier2 had a liaison and a network dependence from a Tier1, to a more meshed approach where every cloud could be connected. Evolution of ATLAS data models requires changes in ATLAS Tier2s policy for the data replication, dynamic data caching and remote data access. It also requires rethinking the network infrastructure to enable any Tier2 and associated Tier3 to easily connect to any Tier1 or Tier2. Tier2s are becoming more and more important in the ATLAS computing model as it allows more data to be readily accessible for analysis jobs to all users, independently of their geographical location. The Tier2s disk space has been reserved for real, simulated, calibration and alignment, group, and user data. A buffer disk space is needed for input and output data for simulations jobs. Tier2s are going to be used more efficiently. In this way Tier1s and Tier2s are becoming more equivalent for t...

  7. High Performance Computing in Science and Engineering '14

    CERN Document Server

    Kröner, Dietmar; Resch, Michael

    2015-01-01

    This book presents the state-of-the-art in supercomputer simulation. It includes the latest findings from leading researchers using systems from the High Performance Computing Center Stuttgart (HLRS). The reports cover all fields of computational science and engineering ranging from CFD to computational physics and from chemistry to computer science with a special emphasis on industrially relevant applications. Presenting findings of one of Europe’s leading systems, this volume covers a wide variety of applications that deliver a high level of sustained performance. The book covers the main methods in high-performance computing. Its outstanding results in achieving the best performance for production codes are of particular interest for both scientists and   engineers. The book comes with a wealth of color illustrations and tables of results.  

  8. Analysis of parallel computing performance of the code MCNP

    International Nuclear Information System (INIS)

    Wang Lei; Wang Kan; Yu Ganglin

    2006-01-01

    Parallel computing can reduce the running time of the code MCNP effectively. With the MPI message transmitting software, MCNP5 can achieve its parallel computing on PC cluster with Windows operating system. Parallel computing performance of MCNP is influenced by factors such as the type, the complexity level and the parameter configuration of the computing problem. This paper analyzes the parallel computing performance of MCNP regarding with these factors and gives measures to improve the MCNP parallel computing performance. (authors)

  9. The ATLAS High Level Trigger Infrastructure, Performance and Future Developments

    CERN Document Server

    The ATLAS collaboration

    2009-01-01

    The ATLAS High Level Trigger (HLT) is a distributed real-time software system that performs the final online selection of events produced during proton-proton collisions at the Large Hadron Collider (LHC). It is designed as a two-stage event filter running on a farm of commodity PC hardware. Currently the system consists of about 850 multi-core processing nodes that will be extended incrementally following the increasing luminosity of the LHC to about 2000 nodes depending on the evolution of the processor technology. Due to the complexity and similarity of the algorithms a large fraction of the software is shared between the online and offline event reconstruction. The HLT Infrastructure serves as the interface between the two domains and provides common services for the trigger algorithms. The consequences of this design choice will be discussed and experiences from the operation of the ATLAS HLT during cosmic ray data taking and first beam in 2008 will be presented. Since the event processing time at the HL...

  10. Earthquake disaster simulation of civil infrastructures from tall buildings to urban areas

    CERN Document Server

    Lu, Xinzheng

    2017-01-01

    Based on more than 12 years of systematic investigation on earthquake disaster simulation of civil infrastructures, this book covers the major research outcomes including a number of novel computational models, high performance computing methods and realistic visualization techniques for tall buildings and urban areas, with particular emphasize on collapse prevention and mitigation in extreme earthquakes, earthquake loss evaluation and seismic resilience. Typical engineering applications to several tallest buildings in the world (e.g., the 632 m tall Shanghai Tower and the 528 m tall Z15 Tower) and selected large cities in China (the Beijing Central Business District, Xi'an City, Taiyuan City and Tangshan City) are also introduced to demonstrate the advantages of the proposed computational models and techniques. The high-fidelity computational model developed in this book has proven to be the only feasible option to date for earthquake-induced collapse simulation of supertall buildings that are higher than 50...

  11. Smart and multifunctional concrete toward sustainable infrastructures

    CERN Document Server

    Han, Baoguo; Ou, Jinping

    2017-01-01

    This book presents the latest research advances and findings in the field of smart/multifunctional concretes, focusing on the principles, design and fabrication, test and characterization, performance and mechanism, and their applications in infrastructures. It also discusses future challenges in the development and application of smart/multifunctional concretes, providing useful theory, ideas and principles, as well as insights and practical guidance for developing sustainable infrastructures. It is a valuable resource for researchers, scientists and engineers in the field of civil-engineering materials and infrastructures.

  12. Implementing an Affordable High-Performance Computing for Teaching-Oriented Computer Science Curriculum

    Science.gov (United States)

    Abuzaghleh, Omar; Goldschmidt, Kathleen; Elleithy, Yasser; Lee, Jeongkyu

    2013-01-01

    With the advances in computing power, high-performance computing (HPC) platforms have had an impact on not only scientific research in advanced organizations but also computer science curriculum in the educational community. For example, multicore programming and parallel systems are highly desired courses in the computer science major. However,…

  13. Federated data storage and management infrastructure

    International Nuclear Information System (INIS)

    Zarochentsev, A; Kiryanov, A; Klimentov, A; Krasnopevtsev, D; Hristov, P

    2016-01-01

    The Large Hadron Collider (LHC)’ operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe. Computing models for the High Luminosity LHC era anticipate a growth of storage needs of at least orders of magnitude; it will require new approaches in data storage organization and data handling. In our project we address the fundamental problem of designing of architecture to integrate a distributed heterogeneous disk resources for LHC experiments and other data- intensive science applications and to provide access to data from heterogeneous computing facilities. We have prototyped a federated storage for Russian T1 and T2 centers located in Moscow, St.-Petersburg and Gatchina, as well as Russian / CERN federation. We have conducted extensive tests of underlying network infrastructure and storage endpoints with synthetic performance measurement tools as well as with HENP-specific workloads, including the ones running on supercomputing platform, cloud computing and Grid for ALICE and ATLAS experiments. We will present our current accomplishments with running LHC data analysis remotely and locally to demonstrate our ability to efficiently use federated data storage experiment wide within National Academic facilities for High Energy and Nuclear Physics as well as for other data-intensive science applications, such as bio-informatics. (paper)

  14. Pricing Digital Goods: Discontinuous Costs and Shared Infrastructure

    OpenAIRE

    Ke-Wei Huang; Arun Sundararajan

    2006-01-01

    We develop and analyze a model of pricing for digital products with discontinuous supply functions. This characterizes a number of information technology-based products and services for which variable increases in demand are fulfilled by the addition of "blocks" of computing or network infrastructure. Examples include internet service, telephony, online trading, on-demand software, digital music, streamed video-on-demand and grid computing. These goods are often modeled as information goods w...

  15. Lecture 4: Cloud Computing in Large Computer Centers

    CERN Multimedia

    CERN. Geneva

    2013-01-01

    This lecture will introduce Cloud Computing concepts identifying and analyzing its characteristics, models, and applications. Also, you will learn how CERN built its Cloud infrastructure and which tools are been used to deploy and manage it. About the speaker: Belmiro Moreira is an enthusiastic software engineer passionate about the challenges and complexities of architecting and deploying Cloud Infrastructures in ve...

  16. Trusted Virtual Infrastructure Bootstrapping for On Demand Services

    NARCIS (Netherlands)

    Membrey, P.; Chan, K.C.C.; Ngo, C.; Demchenko, Y.; de Laat, C.

    2012-01-01

    As cloud computing continues to gain traction, a great deal of effort is being expended in researching the most effective ways to build and manage secure and trustworthy clouds. Providing consistent security services in on-demand provisioned Cloud infrastructure services is of primary importance due

  17. Performing stencil computations

    Energy Technology Data Exchange (ETDEWEB)

    Donofrio, David

    2018-01-16

    A method and apparatus for performing stencil computations efficiently are disclosed. In one embodiment, a processor receives an offset, and in response, retrieves a value from a memory via a single instruction, where the retrieving comprises: identifying, based on the offset, one of a plurality of registers of the processor; loading an address stored in the identified register; and retrieving from the memory the value at the address.

  18. Tracking the NGS revolution: managing life science research on shared high-performance computing clusters.

    Science.gov (United States)

    Dahlö, Martin; Scofield, Douglas G; Schaal, Wesley; Spjuth, Ola

    2018-05-01

    Next-generation sequencing (NGS) has transformed the life sciences, and many research groups are newly dependent upon computer clusters to store and analyze large datasets. This creates challenges for e-infrastructures accustomed to hosting computationally mature research in other sciences. Using data gathered from our own clusters at UPPMAX computing center at Uppsala University, Sweden, where core hour usage of ∼800 NGS and ∼200 non-NGS projects is now similar, we compare and contrast the growth, administrative burden, and cluster usage of NGS projects with projects from other sciences. The number of NGS projects has grown rapidly since 2010, with growth driven by entry of new research groups. Storage used by NGS projects has grown more rapidly since 2013 and is now limited by disk capacity. NGS users submit nearly twice as many support tickets per user, and 11 more tools are installed each month for NGS projects than for non-NGS projects. We developed usage and efficiency metrics and show that computing jobs for NGS projects use more RAM than non-NGS projects, are more variable in core usage, and rarely span multiple nodes. NGS jobs use booked resources less efficiently for a variety of reasons. Active monitoring can improve this somewhat. Hosting NGS projects imposes a large administrative burden at UPPMAX due to large numbers of inexperienced users and diverse and rapidly evolving research areas. We provide a set of recommendations for e-infrastructures that host NGS research projects. We provide anonymized versions of our storage, job, and efficiency databases.

  19. Tracking the NGS revolution: managing life science research on shared high-performance computing clusters

    Science.gov (United States)

    2018-01-01

    Abstract Background Next-generation sequencing (NGS) has transformed the life sciences, and many research groups are newly dependent upon computer clusters to store and analyze large datasets. This creates challenges for e-infrastructures accustomed to hosting computationally mature research in other sciences. Using data gathered from our own clusters at UPPMAX computing center at Uppsala University, Sweden, where core hour usage of ∼800 NGS and ∼200 non-NGS projects is now similar, we compare and contrast the growth, administrative burden, and cluster usage of NGS projects with projects from other sciences. Results The number of NGS projects has grown rapidly since 2010, with growth driven by entry of new research groups. Storage used by NGS projects has grown more rapidly since 2013 and is now limited by disk capacity. NGS users submit nearly twice as many support tickets per user, and 11 more tools are installed each month for NGS projects than for non-NGS projects. We developed usage and efficiency metrics and show that computing jobs for NGS projects use more RAM than non-NGS projects, are more variable in core usage, and rarely span multiple nodes. NGS jobs use booked resources less efficiently for a variety of reasons. Active monitoring can improve this somewhat. Conclusions Hosting NGS projects imposes a large administrative burden at UPPMAX due to large numbers of inexperienced users and diverse and rapidly evolving research areas. We provide a set of recommendations for e-infrastructures that host NGS research projects. We provide anonymized versions of our storage, job, and efficiency databases. PMID:29659792

  20. High performance computing in linear control

    International Nuclear Information System (INIS)

    Datta, B.N.

    1993-01-01

    Remarkable progress has been made in both theory and applications of all important areas of control. The theory is rich and very sophisticated. Some beautiful applications of control theory are presently being made in aerospace, biomedical engineering, industrial engineering, robotics, economics, power systems, etc. Unfortunately, the same assessment of progress does not hold in general for computations in control theory. Control Theory is lagging behind other areas of science and engineering in this respect. Nowadays there is a revolution going on in the world of high performance scientific computing. Many powerful computers with vector and parallel processing have been built and have been available in recent years. These supercomputers offer very high speed in computations. Highly efficient software, based on powerful algorithms, has been developed to use on these advanced computers, and has also contributed to increased performance. While workers in many areas of science and engineering have taken great advantage of these hardware and software developments, control scientists and engineers, unfortunately, have not been able to take much advantage of these developments

  1. The virtual machine (VM) scaler: an infrastructure manager supporting environmental modeling on IaaS clouds

    Science.gov (United States)

    Infrastructure-as-a-service (IaaS) clouds provide a new medium for deployment of environmental modeling applications. Harnessing advancements in virtualization, IaaS clouds can provide dynamic scalable infrastructure to better support scientific modeling computational demands. Providing scientific m...

  2. Critical infrastructure protection

    Energy Technology Data Exchange (ETDEWEB)

    Bradley, F. [Canadian Electricity Association, Toronto, ON (Canada)

    2003-04-01

    The need to protect critical electrical infrastructure from terrorist attacks, or other physical damage, including weather related events, or the potential impact of computer viruses and other attacks on IT resources are discussed. Activities of the North American Electric Reliability Council (NERC) are highlighted which seek to safeguard the North American bulk electric power system principally through the Information Sharing and Analysis Sector (ES-ISAC). ES-ISAC serves the electricity sector by facilitating communication between electric sector participants, federal government and other critical infrastructure industries by disseminating threat indications, analyses and warnings, together with interpretations, to assist the industry in taking infrastructure protection actions. Attention is drawn to the numerous cyber incidents in recent years, which although resulted in no loss of service to electricity customers so far, in at least one instance (the January 25th SOL-Slammer worm incident) resulted in degradation of service in a number of sectors, including financial, transportation and telecommunication services. The increasing frequency of cyber-based attacks, coupled with the industry's growing dependence on e-commerce and electronic controls, are good reasons to believe that critical infrastructure protection (CIP) poses a serious challenge to the industry's risk management practices. The Canadian Electricity Association (CEA) is an active participant in ES-ISAC and works cooperatively with a range of partners, such as the Edison Electric Institute and the American Public Power Association to ensure coordination and effective protection program delivery for the electric power sector. The Early Warning System (EWS) developed by the CIP Working Group is one of the results of this cooperation. EWS uses the Internet, e-mail, web-enabled cell phones and Blackberry hand-held devices to deliver real-time threat information to members on a 24/7 basis. EWS

  3. IT Infrastructure Design and Implementation Considerations for the ATLAS TDAQ System

    CERN Document Server

    Dobson, M; The ATLAS collaboration; Caramarcu, C; Dumitru, I; Valsan, L; Darlea, G L; Bujor, F; Bogdanchikov, A G; Korol, A A; Zaytsev, A S; Ballestrero, S

    2013-01-01

    This paper gives a thorough overview of the ATLAS TDAQ SysAdmin group activities which deals with administration of the TDAQ computing environment supporting Front End detector hardware, Data Flow, Event Filter and other subsystems of the ATLAS detector operating on the LHC accelerator at CERN. The current installation consists of approximately 1500 netbooted nodes managed by more than 60 dedicated servers, a high performance centralized storage system, about 50 multi-screen user interface systems installed in the control rooms and various hardware and critical service monitoring machines. In the final configuration, the online computer farm will be capable of hosting tens of thousands applications running simultaneously. The ATLAS TDAQ computing environment is now serving more than 3000 users subdivided into approximately 300 categories in correspondence with their roles in the system. The access and role management system is custom built on top of an LDAP schema. The engineering infrastructure of the ATLAS ...

  4. Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

    Science.gov (United States)

    Clematis, Andrea; Quarati, Alfonso; Cesini, Daniele; Milanesi, Luciano; Merelli, Ivan

    2013-01-01

    Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements. PMID:24106693

  5. Cloud Infrastructures for In Silico Drug Discovery: Economic and Practical Aspects

    Directory of Open Access Journals (Sweden)

    Daniele D'Agostino

    2013-01-01

    Full Text Available Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements.

  6. ENES the European Network for Earth System modelling and its infrastructure projects IS-ENES

    Science.gov (United States)

    Guglielmo, Francesca; Joussaume, Sylvie; Parinet, Marie

    2016-04-01

    The scientific community working on climate modelling is organized within the European Network for Earth System modelling (ENES). In the past decade, several European university departments, research centres, meteorological services, computer centres, and industrial partners engaged in the creation of ENES with the purpose of working together and cooperating towards the further development of the network, by signing a Memorandum of Understanding. As of 2015, the consortium counts 47 partners. The climate modelling community, and thus ENES, faces challenges which are both science-driven, i.e. analysing of the full complexity of the Earth System to improve our understanding and prediction of climate changes, and have multi-faceted societal implications, as a better representation of climate change on regional scales leads to improved understanding and prediction of impacts and to the development and provision of climate services. ENES, promoting and endorsing projects and initiatives, helps in developing and evaluating of state-of-the-art climate and Earth system models, facilitates model inter-comparison studies, encourages exchanges of software and model results, and fosters the use of high performance computing facilities dedicated to high-resolution multi-model experiments. ENES brings together public and private partners, integrates countries underrepresented in climate modelling studies, and reaches out to different user communities, thus enhancing European expertise and competitiveness. In this need of sophisticated models, world-class, high-performance computers, and state-of-the-art software solutions to make efficient use of models, data and hardware, a key role is played by the constitution and maintenance of a solid infrastructure, developing and providing services to the different user communities. ENES has investigated the infrastructural needs and has received funding from the EU FP7 program for the IS-ENES (InfraStructure for ENES) phase I and II

  7. High Performance Computing Multicast

    Science.gov (United States)

    2012-02-01

    A History of the Virtual Synchrony Replication Model,” in Replication: Theory and Practice, Charron-Bost, B., Pedone, F., and Schiper, A. (Eds...Performance Computing IP / IPv4 Internet Protocol (version 4.0) IPMC Internet Protocol MultiCast LAN Local Area Network MCMD Dr. Multicast MPI

  8. Software for computing and annotating genomic ranges.

    Science.gov (United States)

    Lawrence, Michael; Huber, Wolfgang; Pagès, Hervé; Aboyoun, Patrick; Carlson, Marc; Gentleman, Robert; Morgan, Martin T; Carey, Vincent J

    2013-01-01

    We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.

  9. Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments

    Directory of Open Access Journals (Sweden)

    Jose M. Moya

    2012-08-01

    Full Text Available Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time.

  10. Ubiquitous green computing techniques for high demand applications in Smart environments.

    Science.gov (United States)

    Zapater, Marina; Sanchez, Cesar; Ayala, Jose L; Moya, Jose M; Risco-Martín, José L

    2012-01-01

    Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time.

  11. An Adaptive Middleware for Improved Computational Performance

    DEFF Research Database (Denmark)

    Bonnichsen, Lars Frydendal

    , we are improving computational performance by exploiting modern hardware features, such as dynamic voltage-frequency scaling and transactional memory. Adapting software is an iterative process, requiring that we continually revisit it to meet new requirements or realities; a time consuming process......The performance improvements in computer systems over the past 60 years have been fueled by an exponential increase in energy efficiency. In recent years, the phenomenon known as the end of Dennard’s scaling has slowed energy efficiency improvements — but improving computer energy efficiency...... is more important now than ever. Traditionally, most improvements in computer energy efficiency have come from improvements in lithography — the ability to produce smaller transistors — and computer architecture - the ability to apply those transistors efficiently. Since the end of scaling, we have seen...

  12. Security infrastructure for on-demand provisioned Cloud infrastructure services

    NARCIS (Netherlands)

    Demchenko, Y.; Ngo, C.; de Laat, C.; Wlodarczyk, T.W.; Rong, C.; Ziegler, W.

    2011-01-01

    Providing consistent security services in on-demand provisioned Cloud infrastructure services is of primary importance due to multi-tenant and potentially multi-provider nature of Clouds Infrastructure as a Service (IaaS) environment. Cloud security infrastructure should address two aspects of the

  13. High-performance scientific computing in the cloud

    Science.gov (United States)

    Jorissen, Kevin; Vila, Fernando; Rehr, John

    2011-03-01

    Cloud computing has the potential to open up high-performance computational science to a much broader class of researchers, owing to its ability to provide on-demand, virtualized computational resources. However, before such approaches can become commonplace, user-friendly tools must be developed that hide the unfamiliar cloud environment and streamline the management of cloud resources for many scientific applications. We have recently shown that high-performance cloud computing is feasible for parallelized x-ray spectroscopy calculations. We now present benchmark results for a wider selection of scientific applications focusing on electronic structure and spectroscopic simulation software in condensed matter physics. These applications are driven by an improved portable interface that can manage virtual clusters and run various applications in the cloud. We also describe a next generation of cluster tools, aimed at improved performance and a more robust cluster deployment. Supported by NSF grant OCI-1048052.

  14. History and future perspectives of the Monte Carlo shell model -from Alphleet to K computer-

    International Nuclear Information System (INIS)

    Shimizu, Noritaka; Otsuka, Takaharu; Utsuno, Yutaka; Mizusaki, Takahiro; Honma, Michio; Abe, Takashi

    2013-01-01

    We report a history of the developments of the Monte Carlo shell model (MCSM). The MCSM was proposed in order to perform large-scale shell-model calculations which direct diagonalization method cannot reach. Since 1999 PC clusters were introduced for parallel computation of the MCSM. Since 2011 we participated the High Performance Computing Infrastructure Strategic Program and developed a new MCSM code for current massively parallel computers such as K computer. We discuss future perspectives concerning a new framework and parallel computation of the MCSM by incorporating conjugate gradient method and energy-variance extrapolation

  15. A Security Monitoring Framework For Virtualization Based HEP Infrastructures

    Science.gov (United States)

    Gomez Ramirez, A.; Martinez Pedreira, M.; Grigoras, C.; Betev, L.; Lara, C.; Kebschull, U.; ALICE Collaboration

    2017-10-01

    High Energy Physics (HEP) distributed computing infrastructures require automatic tools to monitor, analyze and react to potential security incidents. These tools should collect and inspect data such as resource consumption, logs and sequence of system calls for detecting anomalies that indicate the presence of a malicious agent. They should also be able to perform automated reactions to attacks without administrator intervention. We describe a novel framework that accomplishes these requirements, with a proof of concept implementation for the ALICE experiment at CERN. We show how we achieve a fully virtualized environment that improves the security by isolating services and Jobs without a significant performance impact. We also describe a collected dataset for Machine Learning based Intrusion Prevention and Detection Systems on Grid computing. This dataset is composed of resource consumption measurements (such as CPU, RAM and network traffic), logfiles from operating system services, and system call data collected from production Jobs running in an ALICE Grid test site and a big set of malware samples. This malware set was collected from security research sites. Based on this dataset, we will proceed to develop Machine Learning algorithms able to detect malicious Jobs.

  16. Cloud Computing Security Latest Issues amp Countermeasures

    Directory of Open Access Journals (Sweden)

    Shelveen Pandey

    2015-08-01

    Full Text Available Abstract Cloud computing describes effective computing services provided by a third-party organization known as cloud service provider for organizations to perform different tasks over the internet for a fee. Cloud service providers computing resources are dynamically reallocated per demand and their infrastructure platform and software and other resources are shared by multiple corporate and private clients. With the steady increase in the number of cloud computing subscribers of these shared resources over the years security on the cloud is a growing concern. In this review paper the current cloud security issues and practices are described and a few innovative solutions are proposed that can help improve cloud computing security in the future.

  17. Department of Energy research in utilization of high-performance computers

    International Nuclear Information System (INIS)

    Buzbee, B.L.; Worlton, W.J.; Michael, G.; Rodrigue, G.

    1980-08-01

    Department of Energy (DOE) and other Government research laboratories depend on high-performance computer systems to accomplish their programmatic goals. As the most powerful computer systems become available, they are acquired by these laboratories so that advances can be made in their disciplines. These advances are often the result of added sophistication to numerical models, the execution of which is made possible by high-performance computer systems. However, high-performance computer systems have become increasingly complex, and consequently it has become increasingly difficult to realize their potential performance. The result is a need for research on issues related to the utilization of these systems. This report gives a brief description of high-performance computers, and then addresses the use of and future needs for high-performance computers within DOE, the growing complexity of applications within DOE, and areas of high-performance computer systems warranting research. 1 figure

  18. Performance of Project Alliancing in Australasia: a Digest of Infrastructure Development from 2008 to 2013

    Directory of Open Access Journals (Sweden)

    Derek Henry Thomas Walker

    2015-03-01

    Full Text Available Project and program alliances have been an accepted form of project procurement for public infrastructure engineering projects in Australia and New Zealand (Australasia. Alliancing often provides best value and superior value for money when compared to traditional approaches such as Design and Construct, however considerable debate continues about its success and applicability. This paper reports on three studies of completed construction project alliance performance in 2008, 2010 and 2012. Consolidated findings are presented on 61 project alliances, data is analysed and emerging trends discussed. Recent government policy changes in Australia at Federal and State level have led to a decline in the number of project alliances, however, while the volume of alliance activity is declining it still represents billions of dollars of infrastructure construction work being undertaken. Results also revealed that communication and trust between the executive leadership and operational management teams was a major factor contributing to the functioning of the alliance. Furthermore, the research identifies several key factors that were necessary preconditions for successful alliances. Paper Type: Research article

  19. Computing shifts to monitor ATLAS distributed computing infrastructure and operations

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00068610; The ATLAS collaboration; Barberis, Dario; Crepe-Renaudin, Sabine Chrystel; De, Kaushik; Fassi, Farida; Stradling, Alden; Svatos, Michal; Vartapetian, Armen; Wolters, Helmut

    2017-01-01

    The ATLAS Distributed Computing (ADC) group established a new Computing Run Coordinator (CRC) shift at the start of LHC Run 2 in 2015. The main goal was to rely on a person with a good overview of the ADC activities to ease the ADC experts’ workload. The CRC shifter keeps track of ADC tasks related to their fields of expertise and responsibility. At the same time, the shifter maintains a global view of the day-to-day operations of the ADC system. During Run 1, this task was accomplished by a person of the expert team called the ADC Manager on Duty (AMOD), a position that was removed during the shutdown period due to the reduced number and availability of ADC experts foreseen for Run 2. The CRC position was proposed to cover some of the AMODs former functions, while allowing more people involved in computing to participate. In this way, CRC shifters help with the training of future ADC experts. The CRC shifters coordinate daily ADC shift operations, including tracking open issues, reporting, and representing...

  20. Computing shifts to monitor ATLAS distributed computing infrastructure and operations

    CERN Document Server

    Adam Bourdarios, Claire; The ATLAS collaboration

    2016-01-01

    The ATLAS Distributed Computing (ADC) group established a new Computing Run Coordinator (CRC) shift at the start of LHC Run2 in 2015. The main goal was to rely on a person with a good overview of the ADC activities to ease the ADC experts' workload. The CRC shifter keeps track of ADC tasks related to their fields of expertise and responsibility. At the same time, the shifter maintains a global view of the day-to-day operations of the ADC system. During Run1, this task was accomplished by the ADC Manager on Duty (AMOD), a position that was removed during the shutdown period due to the reduced number and availability of ADC experts foreseen for Run2. The CRC position was proposed to cover some of the AMOD’s former functions, while allowing more people involved in computing to participate. In this way, CRC shifters help train future ADC experts. The CRC shifters coordinate daily ADC shift operations, including tracking open issues, reporting, and representing ADC in relevant meetings. The CRC also facilitates ...

  1. A modular (almost) automatic set-up for elastic multi-tenants cloud (micro)infrastructures

    Science.gov (United States)

    Amoroso, A.; Astorino, F.; Bagnasco, S.; Balashov, N. A.; Bianchi, F.; Destefanis, M.; Lusso, S.; Maggiora, M.; Pellegrino, J.; Yan, L.; Yan, T.; Zhang, X.; Zhao, X.

    2017-10-01

    An auto-installing tool on an usb drive can allow for a quick and easy automatic deployment of OpenNebula-based cloud infrastructures remotely managed by a central VMDIRAC instance. A single team, in the main site of an HEP Collaboration or elsewhere, can manage and run a relatively large network of federated (micro-)cloud infrastructures, making an highly dynamic and elastic use of computing resources. Exploiting such an approach can lead to modular systems of cloud-bursting infrastructures addressing complex real-life scenarios.

  2. Optical interconnection networks for high-performance computing systems

    International Nuclear Information System (INIS)

    Biberman, Aleksandr; Bergman, Keren

    2012-01-01

    Enabled by silicon photonic technology, optical interconnection networks have the potential to be a key disruptive technology in computing and communication industries. The enduring pursuit of performance gains in computing, combined with stringent power constraints, has fostered the ever-growing computational parallelism associated with chip multiprocessors, memory systems, high-performance computing systems and data centers. Sustaining these parallelism growths introduces unique challenges for on- and off-chip communications, shifting the focus toward novel and fundamentally different communication approaches. Chip-scale photonic interconnection networks, enabled by high-performance silicon photonic devices, offer unprecedented bandwidth scalability with reduced power consumption. We demonstrate that the silicon photonic platforms have already produced all the high-performance photonic devices required to realize these types of networks. Through extensive empirical characterization in much of our work, we demonstrate such feasibility of waveguides, modulators, switches and photodetectors. We also demonstrate systems that simultaneously combine many functionalities to achieve more complex building blocks. We propose novel silicon photonic devices, subsystems, network topologies and architectures to enable unprecedented performance of these photonic interconnection networks. Furthermore, the advantages of photonic interconnection networks extend far beyond the chip, offering advanced communication environments for memory systems, high-performance computing systems, and data centers. (review article)

  3. Heterogeneous access and processing of EO-Data on a Cloud based Infrastructure delivering operational Products

    Science.gov (United States)

    Niggemann, F.; Appel, F.; Bach, H.; de la Mar, J.; Schirpke, B.; Dutting, K.; Rucker, G.; Leimbach, D.

    2015-04-01

    To address the challenges of effective data handling faced by Small and Medium Sized Enterprises (SMEs) a cloud-based infrastructure for accessing and processing of Earth Observation(EO)-data has been developed within the project APPS4GMES(www.apps4gmes.de). To gain homogenous multi mission data access an Input Data Portal (IDP) been implemented on this infrastructure. The IDP consists of an Open Geospatial Consortium (OGC) conformant catalogue, a consolidation module for format conversion and an OGC-conformant ordering framework. Metadata of various EO-sources and with different standards is harvested and transferred to an OGC conformant Earth Observation Product standard and inserted into the catalogue by a Metadata Harvester. The IDP can be accessed for search and ordering of the harvested datasets by the services implemented on the cloud infrastructure. Different land-surface services have been realised by the project partners, using the implemented IDP and cloud infrastructure. Results of these are customer ready products, as well as pre-products (e.g. atmospheric corrected EO data), serving as a basis for other services. Within the IDP an automated access to ESA's Sentinel-1 Scientific Data Hub has been implemented. Searching and downloading of the SAR data can be performed in an automated way. With the implementation of the Sentinel-1 Toolbox and own software, for processing of the datasets for further use, for example for Vista's snow monitoring, delivering input for the flood forecast services, can also be performed in an automated way. For performance tests of the cloud environment a sophisticated model based atmospheric correction and pre-classification service has been implemented. Tests conducted an automated synchronised processing of one entire Landsat 8 (LS-8) coverage for Germany and performance comparisons to standard desktop systems. Results of these tests, showing a performance improvement by the factor of six, proved the high flexibility and

  4. Debugging a high performance computing program

    Science.gov (United States)

    Gooding, Thomas M.

    2013-08-20

    Methods, apparatus, and computer program products are disclosed for debugging a high performance computing program by gathering lists of addresses of calling instructions for a plurality of threads of execution of the program, assigning the threads to groups in dependence upon the addresses, and displaying the groups to identify defective threads.

  5. Development of Resource Sharing System Components for AliEn Grid Infrastructure

    CERN Document Server

    Harutyunyan, Artem

    2010-01-01

    The problem of the resource provision, sharing, accounting and use represents a principal issue in the contemporary scientific cyberinfrastructures. For example, collaborations in physics, astrophysics, Earth science, biology and medicine need to store huge amounts of data (of the order of several petabytes) as well as to conduct highly intensive computations. The appropriate computing and storage capacities cannot be ensured by one (even very large) research center. The modern approach to the solution of this problem suggests exploitation of computational and data storage facilities of the centers participating in collaborations. The most advanced implementation of this approach is based on Grid technologies, which enable effective work of the members of collaborations regardless of their geographical location. Currently there are several tens of Grid infrastructures deployed all over the world. The Grid infrastructures of CERN Large Hadron Collider experiments - ALICE, ATLAS, CMS, and LHCb which are exploi...

  6. On Decision Support for Sustainability and Resilience of Infrastructure

    DEFF Research Database (Denmark)

    Nielsen, Michael Havbro Faber; Qin, J.; Miragliaa, S.

    2017-01-01

    in Bayesian decision analysis and probabilistic systems performance modelling. A principal example for decision support at regulatory level is presented for a coupled system comprised of infrastructure, social, hazard and environmental subsystems. The infrastructure systems is modelled as multi...

  7. Probabilistic sensitivity analysis of optimised preventive maintenance strategies for deteriorating infrastructure assets

    International Nuclear Information System (INIS)

    Daneshkhah, A.; Stocks, N.G.; Jeffrey, P.

    2017-01-01

    Efficient life-cycle management of civil infrastructure systems under continuous deterioration can be improved by studying the sensitivity of optimised preventive maintenance decisions with respect to changes in model parameters. Sensitivity analysis in maintenance optimisation problems is important because if the calculation of the cost of preventive maintenance strategies is not sufficiently robust, the use of the maintenance model can generate optimised maintenances strategies that are not cost-effective. Probabilistic sensitivity analysis methods (particularly variance based ones), only partially respond to this issue and their use is limited to evaluating the extent to which uncertainty in each input contributes to the overall output's variance. These methods do not take account of the decision-making problem in a straightforward manner. To address this issue, we use the concept of the Expected Value of Perfect Information (EVPI) to perform decision-informed sensitivity analysis: to identify the key parameters of the problem and quantify the value of learning about certain aspects of the life-cycle management of civil infrastructure system. This approach allows us to quantify the benefits of the maintenance strategies in terms of expected costs and in the light of accumulated information about the model parameters and aspects of the system, such as the ageing process. We use a Gamma process model to represent the uncertainty associated with asset deterioration, illustrating the use of EVPI to perform sensitivity analysis on the optimisation problem for age-based and condition-based preventive maintenance strategies. The evaluation of EVPI indices is computationally demanding and Markov Chain Monte Carlo techniques would not be helpful. To overcome this computational difficulty, we approximate the EVPI indices using Gaussian process emulators. The implications of the worked numerical examples discussed in the context of analytical efficiency and organisational

  8. Bike Infrastructures

    DEFF Research Database (Denmark)

    Silva, Victor; Harder, Henrik; Jensen, Ole B.

    Bike Infrastructures aims to identify bicycle infrastructure typologies and design elements that can help promote cycling significantly. It is structured as a case study based research where three cycling infrastructures with distinct typologies were analyzed and compared. The three cases......, the findings of this research project can also support bike friendly design and planning, and cyclist advocacy....

  9. Innovative infrastructure of scientific-industrial cluster

    OpenAIRE

    SHEBEKO KONSTANTIN K

    2016-01-01

    Based on the analysis of problems of creation and functioning of innovation infrastructure in Belarus conclusions on the lack of its effectiveness are made. Main focus is given to the analysis of the practice of innovation infrastructure functioning, created on the basis of Polessky State University as a research university in order to perform technological modernization of the economy and the dissemination of effective business practices in Pripyat Polesye region in the form of scientific an...

  10. AQUAGRID: The subsurface hydrology Grid service of the Sardinian regional Grid infrastructure

    International Nuclear Information System (INIS)

    Lecca, G.; Murgia, F.; Maggi, P.; Perias, A.

    2007-01-01

    AQUAGRID is the subsurface hydrology service of the Sardinian regional Grid infrastructure, designed to deliver complex environmental applications via a user-friendly Web portal. The service is oriented towards the needs of water professionals providing them a flexible and powerful tool to solve water resources management problems and aid decision between different remediation options for contaminated soil and groundwater. In this paper, the AQUAGRID application concept and the enabling technologies are illustrated. The heart of the service is the CODESA-3D hydrogeological model to simulate complex and large groundwater flow and contaminant transport problems. The relevant experience gained from the porting of the CODESA-3D application on the EGEE infrastructure, via the GILDA test bed (https://gilda.ct.infn.it), has contributed to the service prototype. AQUAGRID is built on top of compute-Grid technologies by means of the EnginFrame Grid portal. The portal enables the interaction with the underlying Grid infrastructure and manages the computational requirements of the whole application system. Data management, distribution and visualization mechanisms are based on the tools provided by the DatacroSSing Decision Support System (http://datacrossing.crs4.it). The DSS, built on top of the SRB data-Grid middleware, is based on Web-GIS and relational database technologies. The resulting production environment allows the end-user to visualize and interact with the results of the performed analyses, using graphs, annotated maps and 3D objects. Such a set of graphical widgets increases enormously the number of AQUAGRID potential users because it does not require any specific expertise of the physical model and technological background to be understood. (Author)

  11. A model to forecast data centre infrastructure costs.

    Science.gov (United States)

    Vernet, R.

    2015-12-01

    The computing needs in the HEP community are increasing steadily, but the current funding situation in many countries is tight. As a consequence experiments, data centres, and funding agencies have to rationalize resource usage and expenditures. CC-IN2P3 (Lyon, France) provides computing resources to many experiments including LHC, and is a major partner for astroparticle projects like LSST, CTA or Euclid. The financial cost to accommodate all these experiments is substantial and has to be planned well in advance for funding and strategic reasons. In that perspective, leveraging infrastructure expenses, electric power cost and hardware performance observed in our site over the last years, we have built a model that integrates these data and provides estimates of the investments that would be required to cater to the experiments for the mid-term future. We present how our model is built and the expenditure forecast it produces, taking into account the experiment roadmaps. We also examine the resource growth predicted by our model over the next years assuming a flat-budget scenario.

  12. Software for computing and annotating genomic ranges.

    Directory of Open Access Journals (Sweden)

    Michael Lawrence

    Full Text Available We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.

  13. European view of the EGEE infrastructure

    CERN Multimedia

    2007-01-01

    This view is of the Enabling Grids for E-sciencE (EGEE) infrastructure zoomed in on Europe. The EGEE allows the processing power of many computers to be shared so that the huge amount of data produced at CERN's new collider, the Large Hadron Collider (LHC) can be processed. The sites used in the Grid can be downloaded in a zipped .kmz format, which can be imported into Google Earth.

  14. COMPUTING

    CERN Multimedia

    Matthias Kasemann

    Overview The main focus during the summer was to handle data coming from the detector and to perform Monte Carlo production. The lessons learned during the CCRC and CSA08 challenges in May were addressed by dedicated PADA campaigns lead by the Integration team. Big improvements were achieved in the stability and reliability of the CMS Tier1 and Tier2 centres by regular and systematic follow-up of faults and errors with the help of the Savannah bug tracking system. In preparation for data taking the roles of a Computing Run Coordinator and regular computing shifts monitoring the services and infrastructure as well as interfacing to the data operations tasks are being defined. The shift plan until the end of 2008 is being put together. User support worked on documentation and organized several training sessions. The ECoM task force delivered the report on “Use Cases for Start-up of pp Data-Taking” with recommendations and a set of tests to be performed for trigger rates much higher than the ...

  15. Workshop on Software Development Tools for Petascale Computing

    Energy Technology Data Exchange (ETDEWEB)

    Vetter, Jeffrey [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Georgia Inst. of Technology, Atlanta, GA (United States)

    2007-08-01

    Petascale computing systems will soon be available to the DOE science community. Recent studies in the productivity of HPC platforms point to better software environments as a key enabler to science on these systems. To prepare for the deployment and productive use of these petascale platforms, the DOE science and general HPC community must have the software development tools, such as performance analyzers and debuggers that meet application requirements for scalability, functionality, reliability, and ease of use. In this report, we identify and prioritize the research opportunities in the area of software development tools for high performance computing. To facilitate this effort, DOE hosted a group of 55 leading international experts in this area at the Software Development Tools for PetaScale Computing (SDTPC) Workshop, which was held in Washington, D.C. on August 1 and 2, 2007. Software development tools serve as an important interface between the application teams and the target HPC architectures. Broadly speaking, these roles can be decomposed into three categories: performance tools, correctness tools, and development environments. Accordingly, this SDTPC report has four technical thrusts: performance tools, correctness tools, development environment infrastructures, and scalable tool infrastructures. The last thrust primarily targets tool developers per se, rather than end users. Finally, this report identifies non-technical strategic challenges that impact most tool development. The organizing committee emphasizes that many critical areas are outside the scope of this charter; these important areas include system software, compilers, and I/O.

  16. Advanced Artificial Science. The development of an artificial science and engineering research infrastructure to facilitate innovative computational modeling, analysis, and application to interdisciplinary areas of scientific investigation.

    Energy Technology Data Exchange (ETDEWEB)

    Saffer, Shelley (Sam) I.

    2014-12-01

    This is a final report of the DOE award DE-SC0001132, Advanced Artificial Science. The development of an artificial science and engineering research infrastructure to facilitate innovative computational modeling, analysis, and application to interdisciplinary areas of scientific investigation. This document describes the achievements of the goals, and resulting research made possible by this award.

  17. Energy-Efficient Cooperative Techniques for Infrastructure-to-Vehicle Communications

    OpenAIRE

    Nguyen , Tuan-Duc; Berder , Olivier; Sentieys , Olivier

    2011-01-01

    International audience; In wireless distributed networks, cooperative relay and cooperative Multi-Input Multi-Output (MIMO) techniques can be used to exploit the spatial and temporal diversity gain in order to increase the performance or reduce the transmission energy consumption. The energy efficiency of cooperative MIMO and relay techniques is then very useful for the Infrastructure to Vehicle (I2V) and Infrastructure to Infrastructure (I2I) communications in Intelligent Transport Systems (I...

  18. Performance of Air Pollution Models on Massively Parallel Computers

    DEFF Research Database (Denmark)

    Brown, John; Hansen, Per Christian; Wasniewski, Jerzy

    1996-01-01

    To compare the performance and use of three massively parallel SIMD computers, we implemented a large air pollution model on the computers. Using a realistic large-scale model, we gain detailed insight about the performance of the three computers when used to solve large-scale scientific problems...

  19. Misleading Performance Claims in Parallel Computations

    Energy Technology Data Exchange (ETDEWEB)

    Bailey, David H.

    2009-05-29

    In a previous humorous note entitled 'Twelve Ways to Fool the Masses,' I outlined twelve common ways in which performance figures for technical computer systems can be distorted. In this paper and accompanying conference talk, I give a reprise of these twelve 'methods' and give some actual examples that have appeared in peer-reviewed literature in years past. I then propose guidelines for reporting performance, the adoption of which would raise the level of professionalism and reduce the level of confusion, not only in the world of device simulation but also in the larger arena of technical computing.

  20. Reliability in Warehouse-Scale Computing: Why Low Latency Matters

    DEFF Research Database (Denmark)

    Nannarelli, Alberto

    2015-01-01

    , the limiting factor of these warehouse-scale data centers is the power dissipation. Power is dissipated not only in the computation itself, but also in heat removal (fans, air conditioning, etc.) to keep the temperature of the devices within the operating ranges. The need to keep the temperature low within......Warehouse sized buildings are nowadays hosting several types of large computing systems: from supercomputers to large clusters of servers to provide the infrastructure to the cloud. Although the main target, especially for high-performance computing, is still to achieve high throughput...

  1. DIRAC distributed computing services

    International Nuclear Information System (INIS)

    Tsaregorodtsev, A

    2014-01-01

    DIRAC Project provides a general-purpose framework for building distributed computing systems. It is used now in several HEP and astrophysics experiments as well as for user communities in other scientific domains. There is a large interest from smaller user communities to have a simple tool like DIRAC for accessing grid and other types of distributed computing resources. However, small experiments cannot afford to install and maintain dedicated services. Therefore, several grid infrastructure projects are providing DIRAC services for their respective user communities. These services are used for user tutorials as well as to help porting the applications to the grid for a practical day-to-day work. The services are giving access typically to several grid infrastructures as well as to standalone computing clusters accessible by the target user communities. In the paper we will present the experience of running DIRAC services provided by the France-Grilles NGI and other national grid infrastructure projects.

  2. Sustainable support for WLCG through the EGI distributed infrastructure

    International Nuclear Information System (INIS)

    Antoni, Torsten; Bozic, Stefan; Reisser, Sabine

    2011-01-01

    Grid computing is now in a transition phase from development in research projects to routine usage in a sustainable infrastructure. This is mirrored in Europe by the transition from the series of EGEE projects to the European Grid Initiative (EGI). EGI aims at establishing a self-sustained grid infrastructure across Europe. The main building blocks of EGI are the national grid initiatives in the participating countries and a central coordinating institution (EGI.eu). The middleware used is provided by consortia outside of EGI. Also the user communities are organized separately from EGI. The transition to a self-sustained grid infrastructure is aided by the EGI-InSPIRE project, aiming at reducing the project-funding needed to run EGI over the course of its four year duration. Providing user support in this framework poses new technical and organisational challenges as it has to cross the boundaries of various projects and infrastructures. The EGI user support infrastructure is built around the Gobal Grid User Support system (GGUS) that was also the basis of user support in EGEE. Utmost care was taken that during the transition from EGEE to EGI support services which are already used in production were not perturbed. A year into the EGI-InSPIRE project, in this paper we would like to present the current status of the user support infrastructure provided by EGI for WLCG, new features that were needed to match the new infrastructure, issues and challenges that occurred during the transition and give an outlook on future plans and developments.

  3. Leveraging the Power of High Performance Computing for Next Generation Sequencing Data Analysis: Tricks and Twists from a High Throughput Exome Workflow

    Science.gov (United States)

    Wonczak, Stephan; Thiele, Holger; Nieroda, Lech; Jabbari, Kamel; Borowski, Stefan; Sinha, Vishal; Gunia, Wilfried; Lang, Ulrich; Achter, Viktor; Nürnberg, Peter

    2015-01-01

    Next generation sequencing (NGS) has been a great success and is now a standard method of research in the life sciences. With this technology, dozens of whole genomes or hundreds of exomes can be sequenced in rather short time, producing huge amounts of data. Complex bioinformatics analyses are required to turn these data into scientific findings. In order to run these analyses fast, automated workflows implemented on high performance computers are state of the art. While providing sufficient compute power and storage to meet the NGS data challenge, high performance computing (HPC) systems require special care when utilized for high throughput processing. This is especially true if the HPC system is shared by different users. Here, stability, robustness and maintainability are as important for automated workflows as speed and throughput. To achieve all of these aims, dedicated solutions have to be developed. In this paper, we present the tricks and twists that we utilized in the implementation of our exome data processing workflow. It may serve as a guideline for other high throughput data analysis projects using a similar infrastructure. The code implementing our solutions is provided in the supporting information files. PMID:25942438

  4. A high performance computing framework for physics-based modeling and simulation of military ground vehicles

    Science.gov (United States)

    Negrut, Dan; Lamb, David; Gorsich, David

    2011-06-01

    This paper describes a software infrastructure made up of tools and libraries designed to assist developers in implementing computational dynamics applications running on heterogeneous and distributed computing environments. Together, these tools and libraries compose a so called Heterogeneous Computing Template (HCT). The heterogeneous and distributed computing hardware infrastructure is assumed herein to be made up of a combination of CPUs and Graphics Processing Units (GPUs). The computational dynamics applications targeted to execute on such a hardware topology include many-body dynamics, smoothed-particle hydrodynamics (SPH) fluid simulation, and fluid-solid interaction analysis. The underlying theme of the solution approach embraced by HCT is that of partitioning the domain of interest into a number of subdomains that are each managed by a separate core/accelerator (CPU/GPU) pair. Five components at the core of HCT enable the envisioned distributed computing approach to large-scale dynamical system simulation: (a) the ability to partition the problem according to the one-to-one mapping; i.e., spatial subdivision, discussed above (pre-processing); (b) a protocol for passing data between any two co-processors; (c) algorithms for element proximity computation; and (d) the ability to carry out post-processing in a distributed fashion. In this contribution the components (a) and (b) of the HCT are demonstrated via the example of the Discrete Element Method (DEM) for rigid body dynamics with friction and contact. The collision detection task required in frictional-contact dynamics (task (c) above), is shown to benefit on the GPU of a two order of magnitude gain in efficiency when compared to traditional sequential implementations. Note: Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not imply its endorsement, recommendation, or favoring by the United States Army. The views and

  5. CSDMS2.0: Computational Infrastructure for Community Surface Dynamics Modeling

    Science.gov (United States)

    Syvitski, J. P.; Hutton, E.; Peckham, S. D.; Overeem, I.; Kettner, A.

    2012-12-01

    The Community Surface Dynamic Modeling System (CSDMS) is an NSF-supported, international and community-driven program that seeks to transform the science and practice of earth-surface dynamics modeling. CSDMS integrates a diverse community of more than 850 geoscientists representing 360 international institutions (academic, government, industry) from 60 countries and is supported by a CSDMS Interagency Committee (22 Federal agencies), and a CSDMS Industrial Consortia (18 companies). CSDMS presently distributes more 200 Open Source models and modeling tools, access to high performance computing clusters in support of developing and running models, and a suite of products for education and knowledge transfer. CSDMS software architecture employs frameworks and services that convert stand-alone models into flexible "plug-and-play" components to be assembled into larger applications. CSDMS2.0 will support model applications within a web browser, on a wider variety of computational platforms, and on other high performance computing clusters to ensure robustness and sustainability of the framework. Conversion of stand-alone models into "plug-and-play" components will employ automated wrapping tools. Methods for quantifying model uncertainty are being adapted as part of the modeling framework. Benchmarking data is being incorporated into the CSDMS modeling framework to support model inter-comparison. Finally, a robust mechanism for ingesting and utilizing semantic mediation databases is being developed within the Modeling Framework. Six new community initiatives are being pursued: 1) an earth - ecosystem modeling initiative to capture ecosystem dynamics and ensuing interactions with landscapes, 2) a geodynamics initiative to investigate the interplay among climate, geomorphology, and tectonic processes, 3) an Anthropocene modeling initiative, to incorporate mechanistic models of human influences, 4) a coastal vulnerability modeling initiative, with emphasis on deltas and

  6. Cloud Computing with iPlant Atmosphere.

    Science.gov (United States)

    McKay, Sheldon J; Skidmore, Edwin J; LaRose, Christopher J; Mercer, Andre W; Noutsos, Christos

    2013-10-15

    Cloud Computing refers to distributed computing platforms that use virtualization software to provide easy access to physical computing infrastructure and data storage, typically administered through a Web interface. Cloud-based computing provides access to powerful servers, with specific software and virtual hardware configurations, while eliminating the initial capital cost of expensive computers and reducing the ongoing operating costs of system administration, maintenance contracts, power consumption, and cooling. This eliminates a significant barrier to entry into bioinformatics and high-performance computing for many researchers. This is especially true of free or modestly priced cloud computing services. The iPlant Collaborative offers a free cloud computing service, Atmosphere, which allows users to easily create and use instances on virtual servers preconfigured for their analytical needs. Atmosphere is a self-service, on-demand platform for scientific computing. This unit demonstrates how to set up, access and use cloud computing in Atmosphere. Copyright © 2013 John Wiley & Sons, Inc.

  7. A Screen Space GPGPU Surface LIC Algorithm for Distributed Memory Data Parallel Sort Last Rendering Infrastructures

    Energy Technology Data Exchange (ETDEWEB)

    Loring, Burlen; Karimabadi, Homa; Rortershteyn, Vadim

    2014-07-01

    The surface line integral convolution(LIC) visualization technique produces dense visualization of vector fields on arbitrary surfaces. We present a screen space surface LIC algorithm for use in distributed memory data parallel sort last rendering infrastructures. The motivations for our work are to support analysis of datasets that are too large to fit in the main memory of a single computer and compatibility with prevalent parallel scientific visualization tools such as ParaView and VisIt. By working in screen space using OpenGL we can leverage the computational power of GPUs when they are available and run without them when they are not. We address efficiency and performance issues that arise from the transformation of data from physical to screen space by selecting an alternate screen space domain decomposition. We analyze the algorithm's scaling behavior with and without GPUs on two high performance computing systems using data from turbulent plasma simulations.

  8. Integrating operation design into infrastructure planning to foster robustness of planned water systems

    Science.gov (United States)

    Bertoni, Federica; Giuliani, Matteo; Castelletti, Andrea

    2017-04-01

    Over the past years, many studies have looked at the planning and management of water infrastructure systems as two separate problems, where the dynamic component (i.e., operations) is considered only after the static problem (i.e., planning) has been resolved. Most recent works have started to investigate planning and management as two strictly interconnected faces of the same problem, where the former is solved jointly with the latter in an integrated framework. This brings advantages to multi-purpose water reservoir systems, where several optimal operating strategies exist and similar system designs might perform differently on the long term depending on the considered short-term operating tradeoff. An operationally robust design will be therefore one performing well across multiple feasible tradeoff operating policies. This work aims at studying the interaction between short-term operating strategies and their impacts on long-term structural decisions, when long-lived infrastructures with complex ecological impacts and multi-sectoral demands to satisfy (i.e., reservoirs) are considered. A parametric reinforcement learning approach is adopted for nesting optimization and control yielding to both optimal reservoir design and optimal operational policies for water reservoir systems. The method is demonstrated on a synthetic reservoir that must be designed and operated for ensuring reliable water supply to downstream users. At first, the optimal design capacity derived is compared with the 'no-fail storage' computed through Rippl, a capacity design function that returns the minimum storage needed to satisfy specified water demands without allowing supply shortfall. Then, the optimal reservoir volume is used to simulate the simplified case study under other operating objectives than water supply, in order to assess whether and how the system performance changes. The more robust the infrastructural design, the smaller the difference between the performances of

  9. IP Infrastructure Geolocation

    Science.gov (United States)

    2015-03-01

    by non-commercial enti- ties. HostiP is a community-driven geolocation service. It provides an Application Pro- gramming Interface ( API ) for...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS IP INFRASTRUCTURE GEOLOCATION Thesis Advisor: Second Reader: by Guan Yan Cai March...FUNDING NUMBERS IP INFRASTRUCfURE GEOLOCATION N66001-2250-59231 6. AUTHOR(S) Guan Yan Cai 7. PERFORMING ORGANIZATION NAME(S) AND AOORESS(ES) 9

  10. The DIII-D Computing Environment: Characteristics and Recent Changes

    International Nuclear Information System (INIS)

    McHarg, B.B. Jr.

    1999-01-01

    The DIII-D tokamak national fusion research facility along with its predecessor Doublet III has been operating for over 21 years. The DIII-D computing environment consists of real-time systems controlling the tokamak, heating systems, and diagnostics, and systems acquiring experimental data from instrumentation; major data analysis server nodes performing short term and long term data access and data analysis; and systems providing mechanisms for remote collaboration and the dissemination of information over the world wide web. Computer systems for the facility have undergone incredible changes over the course of time as the computer industry has changed dramatically. Yet there are certain valuable characteristics of the DIII-D computing environment that have been developed over time and have been maintained to this day. Some of these characteristics include: continuous computer infrastructure improvements, distributed data and data access, computing platform integration, and remote collaborations. These characteristics are being carried forward as well as new characteristics resulting from recent changes which have included: a dedicated storage system and a hierarchical storage management system for raw shot data, various further infrastructure improvements including deployment of Fast Ethernet, the introduction of MDSplus, LSF and common IDL based tools, and improvements to remote collaboration capabilities. This paper will describe this computing environment, important characteristics that over the years have contributed to the success of DIII-D computing systems, and recent changes to computer systems

  11. Software Systems for High-performance Quantum Computing

    Energy Technology Data Exchange (ETDEWEB)

    Humble, Travis S [ORNL; Britt, Keith A [ORNL

    2016-01-01

    Quantum computing promises new opportunities for solving hard computational problems, but harnessing this novelty requires breakthrough concepts in the design, operation, and application of computing systems. We define some of the challenges facing the development of quantum computing systems as well as software-based approaches that can be used to overcome these challenges. Following a brief overview of the state of the art, we present models for the quantum programming and execution models, the development of architectures for hybrid high-performance computing systems, and the realization of software stacks for quantum networking. This leads to a discussion of the role that conventional computing plays in the quantum paradigm and how some of the current challenges for exascale computing overlap with those facing quantum computing.

  12. Effecting IT infrastructure culture change: management by processes and metrics

    Science.gov (United States)

    Miller, R. L.

    2001-01-01

    This talk describes the processes and metrics used by Jet Propulsion Laboratory to bring about the required IT infrastructure culture change to update and certify, as Y2K compliant, thousands of computers and millions of lines of code.

  13. GRID computing for experimental high energy physics

    International Nuclear Information System (INIS)

    Moloney, G.R.; Martin, L.; Seviour, E.; Taylor, G.N.; Moorhead, G.F.

    2002-01-01

    Full text: The Large Hadron Collider (LHC), to be completed at the CERN laboratory in 2006, will generate 11 petabytes of data per year. The processing of this large data stream requires a large, distributed computing infrastructure. A recent innovation in high performance distributed computing, the GRID, has been identified as an important tool in data analysis for the LHC. GRID computing has actual and potential application in many fields which require computationally intensive analysis of large, shared data sets. The Australian experimental High Energy Physics community has formed partnerships with the High Performance Computing community to establish a GRID node at the University of Melbourne. Through Australian membership of the ATLAS experiment at the LHC, Australian researchers have an opportunity to be involved in the European DataGRID project. This presentation will include an introduction to the GRID, and it's application to experimental High Energy Physics. We will present the results of our studies, including participation in the first LHC data challenge

  14. HPCToolkit: performance tools for scientific computing

    Energy Technology Data Exchange (ETDEWEB)

    Tallent, N; Mellor-Crummey, J; Adhianto, L; Fagan, M; Krentel, M [Department of Computer Science, Rice University, Houston, TX 77005 (United States)

    2008-07-15

    As part of the U.S. Department of Energy's Scientific Discovery through Advanced Computing (SciDAC) program, science teams are tackling problems that require simulation and modeling on petascale computers. As part of activities associated with the SciDAC Center for Scalable Application Development Software (CScADS) and the Performance Engineering Research Institute (PERI), Rice University is building software tools for performance analysis of scientific applications on the leadership-class platforms. In this poster abstract, we briefly describe the HPCToolkit performance tools and how they can be used to pinpoint bottlenecks in SPMD and multi-threaded parallel codes. We demonstrate HPCToolkit's utility by applying it to two SciDAC applications: the S3D code for simulation of turbulent combustion and the MFDn code for ab initio calculations of microscopic structure of nuclei.

  15. HPCToolkit: performance tools for scientific computing

    International Nuclear Information System (INIS)

    Tallent, N; Mellor-Crummey, J; Adhianto, L; Fagan, M; Krentel, M

    2008-01-01

    As part of the U.S. Department of Energy's Scientific Discovery through Advanced Computing (SciDAC) program, science teams are tackling problems that require simulation and modeling on petascale computers. As part of activities associated with the SciDAC Center for Scalable Application Development Software (CScADS) and the Performance Engineering Research Institute (PERI), Rice University is building software tools for performance analysis of scientific applications on the leadership-class platforms. In this poster abstract, we briefly describe the HPCToolkit performance tools and how they can be used to pinpoint bottlenecks in SPMD and multi-threaded parallel codes. We demonstrate HPCToolkit's utility by applying it to two SciDAC applications: the S3D code for simulation of turbulent combustion and the MFDn code for ab initio calculations of microscopic structure of nuclei

  16. Performance evaluation of cognitive radio in advanced metering infrastructure communication

    Science.gov (United States)

    Hiew, Yik-Kuan; Mohd Aripin, Norazizah; Din, Norashidah Md

    2016-03-01

    Smart grid is an intelligent electricity grid system. A reliable two-way communication system is required to transmit both critical and non-critical smart grid data. However, it is difficult to locate a huge chunk of dedicated spectrum for smart grid communications. Hence, cognitive radio based communication is applied. Cognitive radio allows smart grid users to access licensed spectrums opportunistically with the constraint of not causing harmful interference to licensed users. In this paper, a cognitive radio based smart grid communication framework is proposed. Smart grid framework consists of Home Area Network (HAN) and Advanced Metering Infrastructure (AMI), while AMI is made up of Neighborhood Area Network (NAN) and Wide Area Network (WAN). In this paper, the authors only report the findings for AMI communication. AMI is smart grid domain that comprises smart meters, data aggregator unit, and billing center. Meter data are collected by smart meters and transmitted to data aggregator unit by using cognitive 802.11 technique; data aggregator unit then relays the data to billing center using cognitive WiMAX and TV white space. The performance of cognitive radio in AMI communication is investigated using Network Simulator 2. Simulation results show that cognitive radio improves the latency and throughput performances of AMI. Besides, cognitive radio also improves spectrum utilization efficiency of WiMAX band from 5.92% to 9.24% and duty cycle of TV band from 6.6% to 10.77%.

  17. The Ex Hoc Infrastructure - Enhancing Traffic Safety through LIfe WArning Systems

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius; Kristensen, Lars Michael; Eskildsen, Toke

    2004-01-01

    New pervasive computing technologies for sensing and communication open up novel possibilities for enhancing traffic safety. We are currently designing and implementing the Ex Hoc infrastructure framework for communication among mobile and stationary units including vehicles. The infrastructure...... will connect sensing devices on vehicles with sensing devices on other vehicles and with stationary communication units placed alongside roads. The current application of Ex Hoc is to enable the collection and dissemination of information on road condition through LIfe Warning Systems (LIWAS) units....

  18. Computer task performance by subjects with Duchenne muscular dystrophy.

    Science.gov (United States)

    Malheiros, Silvia Regina Pinheiro; da Silva, Talita Dias; Favero, Francis Meire; de Abreu, Luiz Carlos; Fregni, Felipe; Ribeiro, Denise Cardoso; de Mello Monteiro, Carlos Bandeira

    2016-01-01

    Two specific objectives were established to quantify computer task performance among people with Duchenne muscular dystrophy (DMD). First, we compared simple computational task performance between subjects with DMD and age-matched typically developing (TD) subjects. Second, we examined correlations between the ability of subjects with DMD to learn the computational task and their motor functionality, age, and initial task performance. The study included 84 individuals (42 with DMD, mean age of 18±5.5 years, and 42 age-matched controls). They executed a computer maze task; all participants performed the acquisition (20 attempts) and retention (five attempts) phases, repeating the same maze. A different maze was used to verify transfer performance (five attempts). The Motor Function Measure Scale was applied, and the results were compared with maze task performance. In the acquisition phase, a significant decrease was found in movement time (MT) between the first and last acquisition block, but only for the DMD group. For the DMD group, MT during transfer was shorter than during the first acquisition block, indicating improvement from the first acquisition block to transfer. In addition, the TD group showed shorter MT than the DMD group across the study. DMD participants improved their performance after practicing a computational task; however, the difference in MT was present in all attempts among DMD and control subjects. Computational task improvement was positively influenced by the initial performance of individuals with DMD. In turn, the initial performance was influenced by their distal functionality but not their age or overall functionality.

  19. A prototype Infrastructure for Cloud-based distributed services in High Availability over WAN

    International Nuclear Information System (INIS)

    Bulfon, C.; De Salvo, A.; Graziosi, C.; Carlino, G.; Doria, A; Pardi, S; Sanchez, A.; Carboni, M; Bolletta, P; Puccio, L.; Capone, V; Merola, L

    2015-01-01

    In this work we present the architectural and performance studies concerning a prototype of a distributed Tier2 infrastructure for HEP, instantiated between the two Italian sites of INFN-Romal and INFN-Napoli. The network infrastructure is based on a Layer-2 geographical link, provided by the Italian NREN (GARR), directly connecting the two remote LANs of the named sites. By exploiting the possibilities offered by the new distributed file systems, a shared storage area with synchronous copy has been set up. The computing infrastructure, based on an OpenStack facility, is using a set of distributed Hypervisors installed in both sites. The main parameter to be taken into account when managing two remote sites with a single framework is the effect of the latency, due to the distance and the end-to-end service overhead. In order to understand the capabilities and limits of our setup, the impact of latency has been investigated by means of a set of stress tests, including data I/O throughput, metadata access performance evaluation and network occupancy, during the life cycle of a Virtual Machine. A set of resilience tests has also been performed, in order to verify the stability of the system on the event of hardware or software faults.The results of this work show that the reliability and robustness of the chosen architecture are effective enough to build a production system and to provide common services. This prototype can also be extended to multiple sites with small changes of the network topology, thus creating a National Network of Cloud-based distributed services, in HA over WAN. (paper)

  20. A prototype Infrastructure for Cloud-based distributed services in High Availability over WAN

    Science.gov (United States)

    Bulfon, C.; Carlino, G.; De Salvo, A.; Doria, A.; Graziosi, C.; Pardi, S.; Sanchez, A.; Carboni, M.; Bolletta, P.; Puccio, L.; Capone, V.; Merola, L.

    2015-12-01

    In this work we present the architectural and performance studies concerning a prototype of a distributed Tier2 infrastructure for HEP, instantiated between the two Italian sites of INFN-Romal and INFN-Napoli. The network infrastructure is based on a Layer-2 geographical link, provided by the Italian NREN (GARR), directly connecting the two remote LANs of the named sites. By exploiting the possibilities offered by the new distributed file systems, a shared storage area with synchronous copy has been set up. The computing infrastructure, based on an OpenStack facility, is using a set of distributed Hypervisors installed in both sites. The main parameter to be taken into account when managing two remote sites with a single framework is the effect of the latency, due to the distance and the end-to-end service overhead. In order to understand the capabilities and limits of our setup, the impact of latency has been investigated by means of a set of stress tests, including data I/O throughput, metadata access performance evaluation and network occupancy, during the life cycle of a Virtual Machine. A set of resilience tests has also been performed, in order to verify the stability of the system on the event of hardware or software faults. The results of this work show that the reliability and robustness of the chosen architecture are effective enough to build a production system and to provide common services. This prototype can also be extended to multiple sites with small changes of the network topology, thus creating a National Network of Cloud-based distributed services, in HA over WAN.

  1. Human performance models for computer-aided engineering

    Science.gov (United States)

    Elkind, Jerome I. (Editor); Card, Stuart K. (Editor); Hochberg, Julian (Editor); Huey, Beverly Messick (Editor)

    1989-01-01

    This report discusses a topic important to the field of computational human factors: models of human performance and their use in computer-based engineering facilities for the design of complex systems. It focuses on a particular human factors design problem -- the design of cockpit systems for advanced helicopters -- and on a particular aspect of human performance -- vision and related cognitive functions. By focusing in this way, the authors were able to address the selected topics in some depth and develop findings and recommendations that they believe have application to many other aspects of human performance and to other design domains.

  2. High Performance Computing in Science and Engineering '99 : Transactions of the High Performance Computing Center

    CERN Document Server

    Jäger, Willi

    2000-01-01

    The book contains reports about the most significant projects from science and engineering of the Federal High Performance Computing Center Stuttgart (HLRS). They were carefully selected in a peer-review process and are showcases of an innovative combination of state-of-the-art modeling, novel algorithms and the use of leading-edge parallel computer technology. The projects of HLRS are using supercomputer systems operated jointly by university and industry and therefore a special emphasis has been put on the industrial relevance of results and methods.

  3. Performative Computation-aided Design Optimization

    Directory of Open Access Journals (Sweden)

    Ming Tang

    2012-12-01

    Full Text Available This article discusses a collaborative research and teaching project between the University of Cincinnati, Perkins+Will’s Tech Lab, and the University of North Carolina Greensboro. The primary investigation focuses on the simulation, optimization, and generation of architectural designs using performance-based computational design approaches. The projects examine various design methods, including relationships between building form, performance and the use of proprietary software tools for parametric design.

  4. AGIS: Evolution of Distributed Computing Information system for ATLAS

    CERN Document Server

    Anisenkov, Alexey; The ATLAS collaboration; Alandes Pradillo, Maria; Karavakis, Edward

    2015-01-01

    The variety of the ATLAS Computing Infrastructure requires a central information system to define the topology of computing resources and to store the different parameters and configuration data which are needed by the various ATLAS software components. The ATLAS Grid Information System is the system designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by ATLAS Distributed Computing applications and services.

  5. COMPUTERS: Teraflops for Europe; EEC Working Group on High Performance Computing

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    1991-03-15

    In little more than a decade, simulation on high performance computers has become an essential tool for theoretical physics, capable of solving a vast range of crucial problems inaccessible to conventional analytic mathematics. In many ways, computer simulation has become the calculus for interacting many-body systems, a key to the study of transitions from isolated to collective behaviour.

  6. COMPUTERS: Teraflops for Europe; EEC Working Group on High Performance Computing

    International Nuclear Information System (INIS)

    Anon.

    1991-01-01

    In little more than a decade, simulation on high performance computers has become an essential tool for theoretical physics, capable of solving a vast range of crucial problems inaccessible to conventional analytic mathematics. In many ways, computer simulation has become the calculus for interacting many-body systems, a key to the study of transitions from isolated to collective behaviour

  7. High performance parallel computers for science

    International Nuclear Information System (INIS)

    Nash, T.; Areti, H.; Atac, R.; Biel, J.; Cook, A.; Deppe, J.; Edel, M.; Fischler, M.; Gaines, I.; Hance, R.

    1989-01-01

    This paper reports that Fermilab's Advanced Computer Program (ACP) has been developing cost effective, yet practical, parallel computers for high energy physics since 1984. The ACP's latest developments are proceeding in two directions. A Second Generation ACP Multiprocessor System for experiments will include $3500 RISC processors each with performance over 15 VAX MIPS. To support such high performance, the new system allows parallel I/O, parallel interprocess communication, and parallel host processes. The ACP Multi-Array Processor, has been developed for theoretical physics. Each $4000 node is a FORTRAN or C programmable pipelined 20 Mflops (peak), 10 MByte single board computer. These are plugged into a 16 port crossbar switch crate which handles both inter and intra crate communication. The crates are connected in a hypercube. Site oriented applications like lattice gauge theory are supported by system software called CANOPY, which makes the hardware virtually transparent to users. A 256 node, 5 GFlop, system is under construction

  8. Petascale Computational Systems

    OpenAIRE

    Bell, Gordon; Gray, Jim; Szalay, Alex

    2007-01-01

    Computational science is changing to be data intensive. Super-Computers must be balanced systems; not just CPU farms but also petascale IO and networking arrays. Anyone building CyberInfrastructure should allocate resources to support a balanced Tier-1 through Tier-3 design.

  9. Evolving ATLAS Computing For Today’s Networks

    CERN Document Server

    Campana, S; The ATLAS collaboration; Jezequel, S; Negri, G; Serfon, C; Ueda, I

    2012-01-01

    The ATLAS computing infrastructure was designed many years ago based on the assumption of rather limited network connectivity between computing centres. ATLAS sites have been organized in a hierarchical model, where only a static subset of all possible network links can be exploited and a static subset of well connected sites (CERN and the T1s) can cover important functional roles such as hosting master copies of the data. The pragmatic adoption of such simplified approach, in respect of a more relaxed scenario interconnecting all sites, was very beneficial during the commissioning of the ATLAS distributed computing system and essential in reducing the operational cost during the first two years of LHC data taking. In the mean time, networks evolved far beyond this initial scenario: while a few countries are still poorly connected with the rest of the WLCG infrastructure, most of the ATLAS computing centres are now efficiently interlinked. Our operational experience in running the computing infrastructure in ...

  10. Multicriteria Resource Brokering in Cloud Computing for Streaming Service

    Directory of Open Access Journals (Sweden)

    Chih-Lun Chou

    2015-01-01

    Full Text Available By leveraging cloud computing such as Infrastructure as a Service (IaaS, the outsourcing of computing resources used to support operations, including servers, storage, and networking components, is quite beneficial for various providers of Internet application. With this increasing trend, resource allocation that both assures QoS via Service Level Agreement (SLA and avoids overprovisioning in order to reduce cost becomes a crucial priority and challenge in the design and operation of complex service-based platforms such as streaming service. On the other hand, providers of IaaS also concern their profit performance and energy consumption while offering these virtualized resources. In this paper, considering both service-oriented and infrastructure-oriented criteria, we regard this resource allocation problem as Multicriteria Decision Making problem and propose an effective trade-off approach based on goal programming model. To validate its effectiveness, a cloud architecture for streaming application is addressed and extensive analysis is performed for related criteria. The results of numerical simulations show that the proposed approach strikes a balance between these conflicting criteria commendably and achieves high cost efficiency.

  11. Green(ing) infrastructure

    CSIR Research Space (South Africa)

    Van Wyk, Llewellyn V

    2014-03-01

    Full Text Available the generation of electricity from renewable sources such as wind, water and solar. Grey infrastructure – In the context of storm water management, grey infrastructure can be thought of as the hard, engineered systems to capture and convey runoff..., pumps, and treatment plants.  Green infrastructure reduces energy demand by reducing the need to collect and transport storm water to a suitable discharge location. In addition, green infrastructure such as green roofs, street trees and increased...

  12. Software Attribution for Geoscience Applications in the Computational Infrastructure for Geodynamics

    Science.gov (United States)

    Hwang, L.; Dumit, J.; Fish, A.; Soito, L.; Kellogg, L. H.; Smith, M.

    2015-12-01

    Scientific software is largely developed by individual scientists and represents a significant intellectual contribution to the field. As the scientific culture and funding agencies move towards an expectation that software be open-source, there is a corresponding need for mechanisms to cite software, both to provide credit and recognition to developers, and to aid in discoverability of software and scientific reproducibility. We assess the geodynamic modeling community's current citation practices by examining more than 300 predominantly self-reported publications utilizing scientific software in the past 5 years that is available through the Computational Infrastructure for Geodynamics (CIG). Preliminary results indicate that authors cite and attribute software either through citing (in rank order) peer-reviewed scientific publications, a user's manual, and/or a paper describing the software code. Attributions maybe found directly in the text, in acknowledgements, in figure captions, or in footnotes. What is considered citable varies widely. Citations predominantly lack software version numbers or persistent identifiers to find the software package. Versioning may be implied through reference to a versioned user manual. Authors sometimes report code features used and whether they have modified the code. As an open-source community, CIG requests that researchers contribute their modifications to the repository. However, such modifications may not be contributed back to a repository code branch, decreasing the chances of discoverability and reproducibility. Survey results through CIG's Software Attribution for Geoscience Applications (SAGA) project suggest that lack of knowledge, tools, and workflows to cite codes are barriers to effectively implement the emerging citation norms. Generated on-demand attributions on software landing pages and a prototype extensible plug-in to automatically generate attributions in codes are the first steps towards reproducibility.

  13. Software Requirements for a System to Compute Mean Failure Cost

    Energy Technology Data Exchange (ETDEWEB)

    Aissa, Anis Ben [University of Tunis, Belvedere, Tunisia; Abercrombie, Robert K [ORNL; Sheldon, Frederick T [ORNL; Mili, Ali [New Jersey Insitute of Technology

    2010-01-01

    In earlier works, we presented a computational infrastructure that allows an analyst to estimate the security of a system in terms of the loss that each stakeholder. We also demonstrated this infrastructure through the results of security breakdowns for the ecommerce case. In this paper, we illustrate this infrastructure by an application that supports the computation of the Mean Failure Cost (MFC) for each stakeholder.

  14. Towards sustainable infrastructure development in Africa : design principles and strategies for lifespan-based building performance

    NARCIS (Netherlands)

    Agyefi-Mensah, S.; Post, J.M.; Egmond - de Wilde De Ligny, van E.L.C.; Mohammadi, M.; Badu, E

    2012-01-01

    Societies and economies the world over develop on the wheels of infrastructure. In Africa, it accounts for about one-third to one-half of all public investment (Kessides, 1993). Significant about infrastructure in general, however is the fact that they have very long lives. Consequently, their

  15. Development of Best Practices for Large-scale Data Management Infrastructure

    NARCIS (Netherlands)

    S. Stadtmüller; H.F. Mühleisen (Hannes); C. Bizer; M.L. Kersten (Martin); J.A. de Rijke (Arjen); F.E. Groffen (Fabian); Y. Zhang (Ying); G. Ladwig; A. Harth; M Trampus

    2012-01-01

    htmlabstractThe amount of available data for processing is constantly increasing and becomes more diverse. We collect our experiences on deploying large-scale data management tools on local-area clusters or cloud infrastructures and provide guidance to use these computing and storage

  16. Cloud infrastructure for providing tools as a service: quality attributes and potential solutions

    DEFF Research Database (Denmark)

    Chauhan, Muhammad Aufeef; Ali Babar, Muhammad

    2012-01-01

    Cloud computing is being increasingly adopted in various domains for providing on-demand infrastructure and Software as a service (SaaS) by leveraging the utility computing model and virtualization technologies. One of the domains, where cloud computing is expected to gain huge traction is Global...... Software Development (GSD) that has emerged as a popular software development model. Despite several promised benefits, GSD is characterized by not only technical issues but also the complexities associated with its processes. One of the key challenges of GSD is to provide appropriate tools more...... efficiently and cost-effectively. Moreover, variations in tools available/used by different GSD team members can also pose challenges. We assert that providing Tools as a Service (TaaS) to GSD teams through a cloud-based infrastructure can be a promising solution to address the tools related challenges in GSD...

  17. Policy and context management in dynamically provisioned access control service for virtualized Cloud infrastructures

    NARCIS (Netherlands)

    Ngo, C.; Membrey, P.; Demchenko, Y.; de Laat, C.

    2012-01-01

    Cloud computing is developing as a new wave of ICT technologies, offering a common approach to on-demand provisioning of computation, storage and network resources which are generally referred to as infrastructure services. Most of currently available commercial Cloud services are built and

  18. Quantum Accelerators for High-Performance Computing Systems

    OpenAIRE

    Britt, Keith A.; Mohiyaddin, Fahd A.; Humble, Travis S.

    2017-01-01

    We define some of the programming and system-level challenges facing the application of quantum processing to high-performance computing. Alongside barriers to physical integration, prominent differences in the execution of quantum and conventional programs challenges the intersection of these computational models. Following a brief overview of the state of the art, we discuss recent advances in programming and execution models for hybrid quantum-classical computing. We discuss a novel quantu...

  19. A Provenance-Based Infrastructure to Support the Life Cycle of Executable Papers

    DEFF Research Database (Denmark)

    2011-01-01

    As publishers establish a greater online presence as well as infrastructure to support the distribution of more varied information, the idea of an executable paper that enables greater interaction has developed. An executable paper provides more information for computational experiments and results...... than the text, tables, and figures of standard papers. Executable papers can bundle computational content that allow readers and reviewers to interact, validate, and explore experiments. By including such content, authors facilitate future discoveries by lowering the barrier to reproducing...... and extending results. We present an infrastructure for creating, disseminating, and maintaining executable papers. Our approach is rooted in provenance, the documentation of exactly how data, experiments, and results were generated. We seek to improve the experience for everyone involved in the life cycle...

  20. Role of information systems in controlling costs: the electronic medical record (EMR) and the high-performance computing and communications (HPCC) efforts

    Science.gov (United States)

    Kun, Luis G.

    1994-12-01

    On October 18, 1991, the IEEE-USA produced an entity statement which endorsed the vital importance of the High Performance Computer and Communications Act of 1991 (HPCC) and called for the rapid implementation of all its elements. Efforts are now underway to develop a Computer Based Patient Record (CBPR), the National Information Infrastructure (NII) as part of the HPCC, and the so-called `Patient Card'. Multiple legislative initiatives which address these and related information technology issues are pending in Congress. Clearly, a national information system will greatly affect the way health care delivery is provided to the United States public. Timely and reliable information represents a critical element in any initiative to reform the health care system as well as to protect and improve the health of every person. Appropriately used, information technologies offer a vital means of improving the quality of patient care, increasing access to universal care and lowering overall costs within a national health care program. Health care reform legislation should reflect increased budgetary support and a legal mandate for the creation of a national health care information system by: (1) constructing a National Information Infrastructure; (2) building a Computer Based Patient Record System; (3) bringing the collective resources of our National Laboratories to bear in developing and implementing the NII and CBPR, as well as a security system with which to safeguard the privacy rights of patients and the physician-patient privilege; and (4) utilizing Government (e.g. DOD, DOE) capabilities (technology and human resources) to maximize resource utilization, create new jobs and accelerate technology transfer to address health care issues.

  1. GISpark: A Geospatial Distributed Computing Platform for Spatiotemporal Big Data

    Science.gov (United States)

    Wang, S.; Zhong, E.; Wang, E.; Zhong, Y.; Cai, W.; Li, S.; Gao, S.

    2016-12-01

    Geospatial data are growing exponentially because of the proliferation of cost effective and ubiquitous positioning technologies such as global remote-sensing satellites and location-based devices. Analyzing large amounts of geospatial data can provide great value for both industrial and scientific applications. Data- and compute- intensive characteristics inherent in geospatial big data increasingly pose great challenges to technologies of data storing, computing and analyzing. Such challenges require a scalable and efficient architecture that can store, query, analyze, and visualize large-scale spatiotemporal data. Therefore, we developed GISpark - a geospatial distributed computing platform for processing large-scale vector, raster and stream data. GISpark is constructed based on the latest virtualized computing infrastructures and distributed computing architecture. OpenStack and Docker are used to build multi-user hosting cloud computing infrastructure for GISpark. The virtual storage systems such as HDFS, Ceph, MongoDB are combined and adopted for spatiotemporal data storage management. Spark-based algorithm framework is developed for efficient parallel computing. Within this framework, SuperMap GIScript and various open-source GIS libraries can be integrated into GISpark. GISpark can also integrated with scientific computing environment (e.g., Anaconda), interactive computing web applications (e.g., Jupyter notebook), and machine learning tools (e.g., TensorFlow/Orange). The associated geospatial facilities of GISpark in conjunction with the scientific computing environment, exploratory spatial data analysis tools, temporal data management and analysis systems make up a powerful geospatial computing tool. GISpark not only provides spatiotemporal big data processing capacity in the geospatial field, but also provides spatiotemporal computational model and advanced geospatial visualization tools that deals with other domains related with spatial property. We

  2. A Lightweight, High-performance I/O Management Package for Data-intensive Computing

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jun

    2011-06-22

    Our group has been working with ANL collaborators on the topic bridging the gap between parallel file system and local file system during the course of this project period. We visited Argonne National Lab -- Dr. Robert Ross's group for one week in the past summer 2007. We looked over our current project progress and planned the activities for the incoming years 2008-09. The PI met Dr. Robert Ross several times such as HEC FSIO workshop 08, SC08 and SC10. We explored the opportunities to develop a production system by leveraging our current prototype to (SOGP+PVFS) a new PVFS version. We delivered SOGP+PVFS codes to ANL PVFS2 group in 2008.We also talked about exploring a potential project on developing new parallel programming models and runtime systems for data-intensive scalable computing (DISC). The methodology is to evolve MPI towards DISC by incorporating some functions of Google MapReduce parallel programming model. More recently, we are together exploring how to leverage existing works to perform (1) coordination/aggregation of local I/O operations prior to movement over the WAN, (2) efficient bulk data movement over the WAN, (3) latency hiding techniques for latency-intensive operations. Since 2009, we start applying Hadoop/MapReduce to some HEC applications with LANL scientists John Bent and Salman Habib. Another on-going work is to improve checkpoint performance at I/O forwarding Layer for the Road Runner super computer with James Nuetz and Gary Gridder at LANL. Two senior undergraduates from our research group did summer internships about high-performance file and storage system projects in LANL since 2008 for consecutive three years. Both of them are now pursuing Ph.D. degree in our group and will be 4th year in the PhD program in Fall 2011 and go to LANL to advance two above-mentioned works during this winter break. Since 2009, we have been collaborating with several computer scientists (Gary Grider, John bent, Parks Fields, James Nunez, Hsing

  3. A simulation study of the impact of the public-private partnership strategy on the performance of transport infrastructure.

    Science.gov (United States)

    Huang, Zhengfeng; Zheng, Pengjun; Ma, Yanqiang; Li, Xuan; Xu, Wenjun; Zhu, Wanlu

    2016-01-01

    The choice of investment strategy has a great impact on the performance of transport infrastructure. Positive projects such as the "Subway plus Property" model in Hong Kong have created sustainable financial profits for the public transport projects. Owing to a series of public debt and other constraints, public-private partnership (PPP) was introduced as an innovative investment model to address this issue and help develop transport infrastructure. Yet, few studies provide a deeper understanding of relationships between PPP strategy and the performance of such transport projects (particularly the whole transport system). This paper defines the research scope as a regional network of freeway. With a popular PPP model, travel demand prediction method, and relevant parameters as input, agents in a simulation framework can simulate the choice of PPP freeway over time. The simulation framework can be used to analyze the relationship between the PPP strategy and performance of the regional freeway network. This study uses the Freeway Network of Yangtze River Delta (FN-YRD) in China as the context. The results demonstrate the value of using simulation models of complex transportation systems to help decision makers choose the right PPP projects. Such a tool is viewed as particularly important given the ongoing transformation of functions of the Chinese transportation sector, including franchise rights of transport projects, and freeway charging mechanism.

  4. Explorations Around "Graceful Failure" in Transportation Infrastructure: Lessons Learned By the Infrastructure and Climate Network (ICNet)

    Science.gov (United States)

    Jacobs, J. M.; Thomas, N.; Mo, W.; Kirshen, P. H.; Douglas, E. M.; Daniel, J.; Bell, E.; Friess, L.; Mallick, R.; Kartez, J.; Hayhoe, K.; Croope, S.

    2014-12-01

    Recent events have demonstrated that the United States' transportation infrastructure is highly vulnerable to extreme weather events which will likely increase in the future. In light of the 60% shortfall of the $900 billion investment needed over the next five years to maintain this aging infrastructure, hardening of all infrastructures is unlikely. Alternative strategies are needed to ensure that critical aspects of the transportation network are maintained during climate extremes. Preliminary concepts around multi-tier service expectations of bridges and roads with reference to network capacity will be presented. Drawing from recent flooding events across the U.S., specific examples for roads/pavement will be used to illustrate impacts, disruptions, and trade-offs between performance during events and subsequent damage. This talk will also address policy and cultural norms within the civil engineering practice that will likely challenge the application of graceful failure pathways during extreme events.

  5. Tests of Cloud Computing and Storage System features for use in H1 Collaboration Data Preservation model

    International Nuclear Information System (INIS)

    Łobodziński, Bogdan

    2011-01-01

    Based on the currently developing strategy for data preservation and long-term analysis in HEP tests of possible future Cloud Computing based on the Eucalyptus Private Cloud platform and the petabyte scale storage open source system CEPH were performed for the H1 Collaboration. Improvements in computing power and strong development of storage systems suggests that a single Cloud Computing resource supported on a given site will be sufficient for analysis requirements beyond the end-date of experiments. This work describes our test-bed architecture which could be applied to fulfill the requirements of the physics program of H1 after the end date of the Collaboration. We discuss the reasons why we choose the Eucalyptus platform and CEPH storage infrastructure as well as our experience with installations and support of these infrastructures. Using our first test results we will examine performance characteristics, noticed failure states, deficiencies, bottlenecks and scaling boundaries.

  6. Development in design of test infrastructure for ITER prototype cryoline test

    International Nuclear Information System (INIS)

    Ketan, Choukekar; Ritendra, Bhattacharya; Nitin, Shah; Muralidhara, Srinivasa; Himanshu, Kapoor; Pratik, Patel; Uday, Kumar; Biswanath, Sarkar

    2015-01-01

    The prototype cryoline (PTCL) for ITER is a representative cryoline from the complex network of all cryolines for the project. PTCL consist of six process pipes (of which four are operating at 4 K temperature level while two are operating at 80 K temperature level), thermal shield and outer vacuum jacket. PTCL will be tested for its thermal performance, mechanical integrity, leak tightness and functioning of components at cryogenic temperatures. The test infrastructure requirements for testing of PTCL have been identified based on the optimized test methodology. The best suited infrastructure option to test PTCL involves 80K system with helium compressor, test boxes, liquid helium Dewar, liquid nitrogen Dewar and interconnecting cryolines. Process study and various analyses have been performed to finalize the specifications of test infrastructure. The present work describes study on global thermo-hydraulic analysis of PTCL test infrastructure. Preliminary process simulation using the ASPEN HYSYS® has been performed to study the dynamic behavior of 80K system. (author)

  7. Usage of Cloud Computing Simulators and Future Systems For Computational Research

    OpenAIRE

    Lakshminarayanan, Ramkumar; Ramalingam, Rajasekar

    2016-01-01

    Cloud Computing is an Internet based computing, whereby shared resources, software and information, are provided to computers and devices on demand, like the electricity grid. Currently, IaaS (Infrastructure as a Service), PaaS (Platform as a Service) and SaaS (Software as a Service) are used as a business model for Cloud Computing. Nowadays, the adoption and deployment of Cloud Computing is increasing in various domains, forcing researchers to conduct research in the area of Cloud Computing ...

  8. Multicore Challenges and Benefits for High Performance Scientific Computing

    Directory of Open Access Journals (Sweden)

    Ida M.B. Nielsen

    2008-01-01

    Full Text Available Until recently, performance gains in processors were achieved largely by improvements in clock speeds and instruction level parallelism. Thus, applications could obtain performance increases with relatively minor changes by upgrading to the latest generation of computing hardware. Currently, however, processor performance improvements are realized by using multicore technology and hardware support for multiple threads within each core, and taking full advantage of this technology to improve the performance of applications requires exposure of extreme levels of software parallelism. We will here discuss the architecture of parallel computers constructed from many multicore chips as well as techniques for managing the complexity of programming such computers, including the hybrid message-passing/multi-threading programming model. We will illustrate these ideas with a hybrid distributed memory matrix multiply and a quantum chemistry algorithm for energy computation using Møller–Plesset perturbation theory.

  9. Greening infrastructure

    CSIR Research Space (South Africa)

    Van Wyk, Llewellyn V

    2014-10-01

    Full Text Available The development and maintenance of infrastructure is crucial to improving economic growth and quality of life (WEF 2013). Urban infrastructure typically includes bulk services such as water, sanitation and energy (typically electricity and gas...

  10. Flowscapes : Infrastructure as landscape, landscape as infrastructure. Graduation Lab Landscape Architecture 2012/2013

    NARCIS (Netherlands)

    Nijhuis, S.; Jauslin, D.; De Vries, C.

    2012-01-01

    Flowscapes explores infrastructure as a type of landscape and landscape as a type of infrastructure, and is focused on landscape architectonic design of transportation-, green- and water infrastructures. These landscape infrastructures are considered armatures for urban and rural development. With

  11. A Vision for a European e‐Infrastructure for the 21st Century

    CERN Document Server

    Bird, Ian; Hemmer, Frédéric; Jones, Bob

    2013-01-01

    Over the past decade Europe has developed world‐leading expertise in building and operating very large scale federated and distributed e‐Infrastructures, supporting unprecedented scales of international collaboration in science, both within and across disciplines. We have the opportunity now to capitalize on that investment and experience, to build the next generation infrastructure to enable innovation and opportunities for European science and education, industry and entrepreneurs. We are now in a period of explosive data growth. The foundations for handling the “Data Tsunami” or “Big Data” have been laid in the last 20 years as we have moved from simple commodity computing (“Farms”), to commodity distributed computing (“Grid”) and then commodity computing services (“Cloud”). These have prepared the ground for handling the large amounts of data being produced today. The era of “Data Intensive Science” has begun. To address these challenges for the diverse, emerging “long tail o...

  12. Parameters that affect parallel processing for computational electromagnetic simulation codes on high performance computing clusters

    Science.gov (United States)

    Moon, Hongsik

    What is the impact of multicore and associated advanced technologies on computational software for science? Most researchers and students have multicore laptops or desktops for their research and they need computing power to run computational software packages. Computing power was initially derived from Central Processing Unit (CPU) clock speed. That changed when increases in clock speed became constrained by power requirements. Chip manufacturers turned to multicore CPU architectures and associated technological advancements to create the CPUs for the future. Most software applications benefited by the increased computing power the same way that increases in clock speed helped applications run faster. However, for Computational ElectroMagnetics (CEM) software developers, this change was not an obvious benefit - it appeared to be a detriment. Developers were challenged to find a way to correctly utilize the advancements in hardware so that their codes could benefit. The solution was parallelization and this dissertation details the investigation to address these challenges. Prior to multicore CPUs, advanced computer technologies were compared with the performance using benchmark software and the metric was FLoting-point Operations Per Seconds (FLOPS) which indicates system performance for scientific applications that make heavy use of floating-point calculations. Is FLOPS an effective metric for parallelized CEM simulation tools on new multicore system? Parallel CEM software needs to be benchmarked not only by FLOPS but also by the performance of other parameters related to type and utilization of the hardware, such as CPU, Random Access Memory (RAM), hard disk, network, etc. The codes need to be optimized for more than just FLOPs and new parameters must be included in benchmarking. In this dissertation, the parallel CEM software named High Order Basis Based Integral Equation Solver (HOBBIES) is introduced. This code was developed to address the needs of the

  13. Development of Bioinformatics Infrastructure for Genomics Research.

    Science.gov (United States)

    Mulder, Nicola J; Adebiyi, Ezekiel; Adebiyi, Marion; Adeyemi, Seun; Ahmed, Azza; Ahmed, Rehab; Akanle, Bola; Alibi, Mohamed; Armstrong, Don L; Aron, Shaun; Ashano, Efejiro; Baichoo, Shakuntala; Benkahla, Alia; Brown, David K; Chimusa, Emile R; Fadlelmola, Faisal M; Falola, Dare; Fatumo, Segun; Ghedira, Kais; Ghouila, Amel; Hazelhurst, Scott; Isewon, Itunuoluwa; Jung, Segun; Kassim, Samar Kamal; Kayondo, Jonathan K; Mbiyavanga, Mamana; Meintjes, Ayton; Mohammed, Somia; Mosaku, Abayomi; Moussa, Ahmed; Muhammd, Mustafa; Mungloo-Dilmohamud, Zahra; Nashiru, Oyekanmi; Odia, Trust; Okafor, Adaobi; Oladipo, Olaleye; Osamor, Victor; Oyelade, Jellili; Sadki, Khalid; Salifu, Samson Pandam; Soyemi, Jumoke; Panji, Sumir; Radouani, Fouzia; Souiai, Oussama; Tastan Bishop, Özlem

    2017-06-01

    Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community. H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for

  14. Cloud Environment Automation: from infrastructure deployment to application monitoring

    Science.gov (United States)

    Aiftimiei, C.; Costantini, A.; Bucchi, R.; Italiano, A.; Michelotto, D.; Panella, M.; Pergolesi, M.; Saletta, M.; Traldi, S.; Vistoli, C.; Zizzi, G.; Salomoni, D.

    2017-10-01

    The potential offered by the cloud paradigm is often limited by technical issues, rules and regulations. In particular, the activities related to the design and deployment of the Infrastructure as a Service (IaaS) cloud layer can be difficult to apply and time-consuming for the infrastructure maintainers. In this paper the research activity, carried out during the Open City Platform (OCP) research project [1], aimed at designing and developing an automatic tool for cloud-based IaaS deployment is presented. Open City Platform is an industrial research project funded by the Italian Ministry of University and Research (MIUR), started in 2014. It intends to research, develop and test new technological solutions open, interoperable and usable on-demand in the field of Cloud Computing, along with new sustainable organizational models that can be deployed for and adopted by the Public Administrations (PA). The presented work and the related outcomes are aimed at simplifying the deployment and maintenance of a complete IaaS cloud-based infrastructure.

  15. Gridification: Porting New Communities onto the WLCG/EGEE Infrastructure

    CERN Document Server

    Méndez-Lorenzo, P; Lamanna, M; Muraru, A

    2007-01-01

    The computational and storage capability of the Grid are attracting several research communities and we will discuss the general patterns observed in supporting new applications, porting them on the EGEE environment. In this talk we present the general infrastructure we have developed inside the application and support team at CERN (PSS and GD groups) to merge in a fast and feasible way all these applications inside the Grid, as for example Geant4, HARP, Garfield, UNOSAT or ITU. All these communities have different goals and requirements and the main challenge is the creation of a standard and general software infrastructure for the immersion of these communities onto the Grid. This general infrastructure effectively ‘shields’ the applications from the details of the Grid (the emphasis here is to run applications developed independently from the Grid middleware).It is stable enough to require few controls and supports by the members of the Grid team and also of the members of the user communities. Finally...

  16. Genomic cloud computing: legal and ethical points to consider.

    Science.gov (United States)

    Dove, Edward S; Joly, Yann; Tassé, Anne-Marie; Knoppers, Bartha M

    2015-10-01

    The biggest challenge in twenty-first century data-intensive genomic science, is developing vast computer infrastructure and advanced software tools to perform comprehensive analyses of genomic data sets for biomedical research and clinical practice. Researchers are increasingly turning to cloud computing both as a solution to integrate data from genomics, systems biology and biomedical data mining and as an approach to analyze data to solve biomedical problems. Although cloud computing provides several benefits such as lower costs and greater efficiency, it also raises legal and ethical issues. In this article, we discuss three key 'points to consider' (data control; data security, confidentiality and transfer; and accountability) based on a preliminary review of several publicly available cloud service providers' Terms of Service. These 'points to consider' should be borne in mind by genomic research organizations when negotiating legal arrangements to store genomic data on a large commercial cloud service provider's servers. Diligent genomic cloud computing means leveraging security standards and evaluation processes as a means to protect data and entails many of the same good practices that researchers should always consider in securing their local infrastructure.

  17. AGIS: Integration of new technologies used in ATLAS Distributed Computing

    OpenAIRE

    Anisenkov, Alexey; Di Girolamo, Alessandro; Alandes Pradillo, Maria

    2017-01-01

    The variety of the ATLAS Distributed Computing infrastructure requires a central information system to define the topology of computing resources and to store different parameters and configuration data which are needed by various ATLAS software components. The ATLAS Grid Information System (AGIS) is the system designed to integrate configuration and status information about resources, services and topology of the computing infrastructure used by ATLAS Distributed Computing applications and s...

  18. High Performance Computing in Science and Engineering '98 : Transactions of the High Performance Computing Center

    CERN Document Server

    Jäger, Willi

    1999-01-01

    The book contains reports about the most significant projects from science and industry that are using the supercomputers of the Federal High Performance Computing Center Stuttgart (HLRS). These projects are from different scientific disciplines, with a focus on engineering, physics and chemistry. They were carefully selected in a peer-review process and are showcases for an innovative combination of state-of-the-art physical modeling, novel algorithms and the use of leading-edge parallel computer technology. As HLRS is in close cooperation with industrial companies, special emphasis has been put on the industrial relevance of results and methods.

  19. Identification of critical locations across multiple infrastructures for terrorist actions

    International Nuclear Information System (INIS)

    Patterson, S.A.; Apostolakis, G.E.

    2007-01-01

    This paper presents a possible approach to ranking geographic regions that can influence multiple infrastructures. Once ranked, decision makers can determine whether these regions are critical locations based on their susceptibility to terrorist acts. We identify these locations by calculating a value for a geographic region that represents the combined values to the decision makers of all the infrastructures crossing through that region. These values, as well as the size of the geographic region, are conditional on an assumed destructive threat of a given size. In our case study, the threat is assumed to be minor, e.g., a bomb that can affect objects within 7 m of it. This approach first requires an assessment of the users of the system. During this assessment, each user is assigned a performance index (PI) based on the disutility of the loss of each infrastructure's resource via multi-attribute utility theory (MAUT). A Monte Carlo network analysis is then performed to develop importance measures (IM) for the elements of each infrastructure for their ability to service each user. We combine the IMs with the user PIs to a value that we call valued worth (VW) for each infrastructure's elements independently. Then we use spatial analysis techniques within a geographic information system (GIS) to combine the VWs of each infrastructure's elements in a geographic area, conditional on the threat, into a total value we call geographic valued worth (GVW). The GVW is displayed graphically in the GIS system in a color scheme that shows the numerical ranking of these geographic areas. The map and rankings are then submitted to the decision makers to better allocate anti-terrorism resources. A case study of this methodology is performed on the Massachusetts Institute of Technology (MIT) campus. The results of the study show how the methodology can bring attention to areas that are important when several infrastructures are considered, but may be ignored when infrastructures

  20. Information system of forecasting infrastructure development in tourism

    Directory of Open Access Journals (Sweden)

    Gats Bogdan

    2013-01-01

    Full Text Available Manuscript is devoted to the development of information system for tourist objects infrastructure growth and its practical implementation in form of information system using methods of fuzzy logic, theory of fractals and diffusion. Developed technology allows compute attractiveness of Carpathian region, structure, dynamics of the main tourist settlements Vorochta and Slavske, prospective territories for tourist business, growing strategies for region.

  1. Theory and Computation

    Data.gov (United States)

    Federal Laboratory Consortium — Flexible computational infrastructure, software tools and theoretical consultation are provided to support modeling and understanding of the structure and properties...

  2. Place-Specific Computing

    DEFF Research Database (Denmark)

    Messeter, Jörn

    2009-01-01

    An increased interest in the notion of place has evolved in interaction design based on the proliferation of wireless infrastructures, developments in digital media, and a ‘spatial turn’ in computing. In this article, place-specific computing is suggested as a genre of interaction design that add......An increased interest in the notion of place has evolved in interaction design based on the proliferation of wireless infrastructures, developments in digital media, and a ‘spatial turn’ in computing. In this article, place-specific computing is suggested as a genre of interaction design...... that addresses the shaping of interactions among people, place-specific resources and global socio-technical networks, mediated by digital technology, and influenced by the structuring conditions of place. The theoretical grounding for place-specific computing is located in the meeting between conceptions...... of place in human geography and recent research in interaction design focusing on embodied interaction. Central themes in this grounding revolve around place and its relation to embodiment and practice, as well as the social, cultural and material aspects conditioning the enactment of place. Selected...

  3. Embedded High Performance Scalable Computing Systems

    National Research Council Canada - National Science Library

    Ngo, David

    2003-01-01

    The Embedded High Performance Scalable Computing Systems (EHPSCS) program is a cooperative agreement between Sanders, A Lockheed Martin Company and DARPA that ran for three years, from Apr 1995 - Apr 1998...

  4. Integrating CAD modules in a PACS environment using a wide computing infrastructure.

    Science.gov (United States)

    Suárez-Cuenca, Jorge J; Tilve, Amara; López, Ricardo; Ferro, Gonzalo; Quiles, Javier; Souto, Miguel

    2017-04-01

    The aim of this paper is to describe a project designed to achieve a total integration of different CAD algorithms into the PACS environment by using a wide computing infrastructure. The aim is to build a system for the entire region of Galicia, Spain, to make CAD accessible to multiple hospitals by employing different PACSs and clinical workstations. The new CAD model seeks to connect different devices (CAD systems, acquisition modalities, workstations and PACS) by means of networking based on a platform that will offer different CAD services. This paper describes some aspects related to the health services of the region where the project was developed, CAD algorithms that were either employed or selected for inclusion in the project, and several technical aspects and results. We have built a standard-based platform with which users can request a CAD service and receive the results in their local PACS. The process runs through a web interface that allows sending data to the different CAD services. A DICOM SR object is received with the results of the algorithms stored inside the original study in the proper folder with the original images. As a result, a homogeneous service to the different hospitals of the region will be offered. End users will benefit from a homogeneous workflow and a standardised integration model to request and obtain results from CAD systems in any modality, not dependant on commercial integration models. This new solution will foster the deployment of these technologies in the entire region of Galicia.

  5. Development Model for Research Infrastructures

    Science.gov (United States)

    Wächter, Joachim; Hammitzsch, Martin; Kerschke, Dorit; Lauterjung, Jörn

    2015-04-01

    Research infrastructures (RIs) are platforms integrating facilities, resources and services used by the research communities to conduct research and foster innovation. RIs include scientific equipment, e.g., sensor platforms, satellites or other instruments, but also scientific data, sample repositories or archives. E-infrastructures on the other hand provide the technological substratum and middleware to interlink distributed RI components with computing systems and communication networks. The resulting platforms provide the foundation for the design and implementation of RIs and play an increasing role in the advancement and exploitation of knowledge and technology. RIs are regarded as essential to achieve and maintain excellence in research and innovation crucial for the European Research Area (ERA). The implementation of RIs has to be considered as a long-term, complex development process often over a period of 10 or more years. The ongoing construction of Spatial Data Infrastructures (SDIs) provides a good example for the general complexity of infrastructure development processes especially in system-of-systems environments. A set of directives issued by the European Commission provided a framework of guidelines for the implementation processes addressing the relevant content and the encoding of data as well as the standards for service interfaces and the integration of these services into networks. Additionally, a time schedule for the overall construction process has been specified. As a result this process advances with a strong participation of member states and responsible organisations. Today, SDIs provide the operational basis for new digital business processes in both national and local authorities. Currently, the development of integrated RIs in Earth and Environmental Sciences is characterised by the following properties: • A high number of parallel activities on European and national levels with numerous institutes and organisations participating

  6. Conceptual design of an ALICE Tier-2 centre. Integrated into a multi-purpose computing facility

    Energy Technology Data Exchange (ETDEWEB)

    Zynovyev, Mykhaylo

    2012-06-29

    This thesis discusses the issues and challenges associated with the design and operation of a data analysis facility for a high-energy physics experiment at a multi-purpose computing centre. At the spotlight is a Tier-2 centre of the distributed computing model of the ALICE experiment at the Large Hadron Collider at CERN in Geneva, Switzerland. The design steps, examined in the thesis, include analysis and optimization of the I/O access patterns of the user workload, integration of the storage resources, and development of the techniques for effective system administration and operation of the facility in a shared computing environment. A number of I/O access performance issues on multiple levels of the I/O subsystem, introduced by utilization of hard disks for data storage, have been addressed by the means of exhaustive benchmarking and thorough analysis of the I/O of the user applications in the ALICE software framework. Defining the set of requirements to the storage system, describing the potential performance bottlenecks and single points of failure and examining possible ways to avoid them allows one to develop guidelines for selecting the way how to integrate the storage resources. The solution, how to preserve a specific software stack for the experiment in a shared environment, is presented along with its effects on the user workload performance. The proposal for a flexible model to deploy and operate the ALICE Tier-2 infrastructure and applications in a virtual environment through adoption of the cloud computing technology and the 'Infrastructure as Code' concept completes the thesis. Scientific software applications can be efficiently computed in a virtual environment, and there is an urgent need to adapt the infrastructure for effective usage of cloud resources.

  7. Conceptual design of an ALICE Tier-2 centre. Integrated into a multi-purpose computing facility

    International Nuclear Information System (INIS)

    Zynovyev, Mykhaylo

    2012-01-01

    This thesis discusses the issues and challenges associated with the design and operation of a data analysis facility for a high-energy physics experiment at a multi-purpose computing centre. At the spotlight is a Tier-2 centre of the distributed computing model of the ALICE experiment at the Large Hadron Collider at CERN in Geneva, Switzerland. The design steps, examined in the thesis, include analysis and optimization of the I/O access patterns of the user workload, integration of the storage resources, and development of the techniques for effective system administration and operation of the facility in a shared computing environment. A number of I/O access performance issues on multiple levels of the I/O subsystem, introduced by utilization of hard disks for data storage, have been addressed by the means of exhaustive benchmarking and thorough analysis of the I/O of the user applications in the ALICE software framework. Defining the set of requirements to the storage system, describing the potential performance bottlenecks and single points of failure and examining possible ways to avoid them allows one to develop guidelines for selecting the way how to integrate the storage resources. The solution, how to preserve a specific software stack for the experiment in a shared environment, is presented along with its effects on the user workload performance. The proposal for a flexible model to deploy and operate the ALICE Tier-2 infrastructure and applications in a virtual environment through adoption of the cloud computing technology and the 'Infrastructure as Code' concept completes the thesis. Scientific software applications can be efficiently computed in a virtual environment, and there is an urgent need to adapt the infrastructure for effective usage of cloud resources.

  8. Usage of super high speed computer for clarification of complex phenomena

    International Nuclear Information System (INIS)

    Sekiguchi, Tomotsugu; Sato, Mitsuhisa; Nakata, Hideki; Tatebe, Osami; Takagi, Hiromitsu

    1999-01-01

    This study aims at construction of an efficient super high speed computer system application environment in response to parallel distributed system with easy transplantation to different computer system and different number by conducting research and development on super high speed computer application technology required for elucidation of complicated phenomenon in elucidation of complicated phenomenon of nuclear power field due to computed scientific method. In order to realize such environment, the Electrotechnical Laboratory has conducted development on Ninf, a network numerical information library. This Ninf system can supply a global network infrastructure for worldwide computing with high performance on further wide range distributed network (G.K.)

  9. 76 FR 14590 - Defense Federal Acquisition Regulation Supplement; Safety of Facilities, Infrastructure, and...

    Science.gov (United States)

    2011-03-17

    ... makes it unlikely that a small business could afford to sustain the infrastructure required to perform...-AG73 Defense Federal Acquisition Regulation Supplement; Safety of Facilities, Infrastructure, and... facilities, infrastructure, and equipment that are intended for use by military or civilian personnel of the...

  10. Security Analysis of Smart Grid Cyber Physical Infrastructures Using Modeling and Game Theoretic Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Abercrombie, Robert K [ORNL; Sheldon, Frederick T. [University of Idaho

    2015-01-01

    Cyber physical computing infrastructures typically consist of a number of sites are interconnected. Its operation critically depends both on cyber components and physical components. Both types of components are subject to attacks of different kinds and frequencies, which must be accounted for the initial provisioning and subsequent operation of the infrastructure via information security analysis. Information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. We concentrated our analysis on the electric sector failure scenarios and impact analyses by the NESCOR Working Group Study, From the Section 5 electric sector representative failure scenarios; we extracted the four generic failure scenarios and grouped them into three specific threat categories (confidentiality, integrity, and availability) to the system. These specific failure scenarios serve as a demonstration of our simulation. The analysis using our ABGT simulation demonstrates how to model the electric sector functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the cyber physical infrastructure network with respect to CIA.

  11. MAGI: a Node.js web service for fast microRNA-Seq analysis in a GPU infrastructure

    OpenAIRE

    Kim, Jihoon; Levy, Eric; Ferbrache, Alex; Stepanowsky, Petra; Farcas, Claudiu; Wang, Shuang; Brunner, Stefan; Bath, Tyler; Wu, Yuan; Ohno-Machado, Lucila

    2014-01-01

    Summary: MAGI is a web service for fast MicroRNA-Seq data analysis in a graphics processing unit (GPU) infrastructure. Using just a browser, users have access to results as web reports in just a few hours—>600% end-to-end performance improvement over state of the art. MAGI’s salient features are (i) transfer of large input files in native FASTA with Qualities (FASTQ) format through drag-and-drop operations, (ii) rapid prediction of microRNA target genes leveraging parallel computing with GPU ...

  12. Computational Fluid Dynamics (CFD) Computations With Zonal Navier-Stokes Flow Solver (ZNSFLOW) Common High Performance Computing Scalable Software Initiative (CHSSI) Software

    National Research Council Canada - National Science Library

    Edge, Harris

    1999-01-01

    ...), computational fluid dynamics (CFD) 6 project. Under the project, a proven zonal Navier-Stokes solver was rewritten for scalable parallel performance on both shared memory and distributed memory high performance computers...

  13. Conceptual Model of IT Infrastructure Capability and Its Empirical Justification

    Institute of Scientific and Technical Information of China (English)

    QI Xianfeng; LAN Boxiong; GUO Zhenwei

    2008-01-01

    Increasing importance has been attached to the value of information technology (IT) infrastructure in today's organizations. The development of efficacious IT infrastructure capability enhances business performance and brings sustainable competitive advantage. This study analyzed the IT infrastructure capability in a holistic way and then presented a concept model of IT capability. IT infrastructure capability was categorized into sharing capability, service capability, and flexibility. This study then empirically tested the model using a set of survey data collected from 145 firms. Three factors emerge from the factor analysis as IT flexibility, IT service capability, and IT sharing capability, which agree with those in the conceptual model built in this study.

  14. Real-time performance monitoring and management system

    Science.gov (United States)

    Budhraja, Vikram S [Los Angeles, CA; Dyer, James D [La Mirada, CA; Martinez Morales, Carlos A [Upland, CA

    2007-06-19

    A real-time performance monitoring system for monitoring an electric power grid. The electric power grid has a plurality of grid portions, each grid portion corresponding to one of a plurality of control areas. The real-time performance monitoring system includes a monitor computer for monitoring at least one of reliability metrics, generation metrics, transmission metrics, suppliers metrics, grid infrastructure security metrics, and markets metrics for the electric power grid. The data for metrics being monitored by the monitor computer are stored in a data base, and a visualization of the metrics is displayed on at least one display computer having a monitor. The at least one display computer in one said control area enables an operator to monitor the grid portion corresponding to a different said control area.

  15. Building a cluster computer for the computing grid of tomorrow

    International Nuclear Information System (INIS)

    Wezel, J. van; Marten, H.

    2004-01-01

    The Grid Computing Centre Karlsruhe takes part in the development, test and deployment of hardware and cluster infrastructure, grid computing middleware, and applications for particle physics. The construction of a large cluster computer with thousands of nodes and several PB data storage capacity is a major task and focus of research. CERN based accelerator experiments will use GridKa, one of only 8 world wide Tier-1 computing centers, for its huge computer demands. Computing and storage is provided already for several other running physics experiments on the exponentially expanding cluster. (orig.)

  16. Enabling high performance computational science through combinatorial algorithms

    International Nuclear Information System (INIS)

    Boman, Erik G; Bozdag, Doruk; Catalyurek, Umit V; Devine, Karen D; Gebremedhin, Assefaw H; Hovland, Paul D; Pothen, Alex; Strout, Michelle Mills

    2007-01-01

    The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation

  17. Enabling high performance computational science through combinatorial algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Boman, Erik G [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Bozdag, Doruk [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Catalyurek, Umit V [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Devine, Karen D [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Gebremedhin, Assefaw H [Computer Science and Center for Computational Science, Old Dominion University (United States); Hovland, Paul D [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Pothen, Alex [Computer Science and Center for Computational Science, Old Dominion University (United States); Strout, Michelle Mills [Computer Science, Colorado State University (United States)

    2007-07-15

    The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation.

  18. Towards a single seismological service infrastructure in Europe

    Science.gov (United States)

    Spinuso, A.; Trani, L.; Frobert, L.; Van Eck, T.

    2012-04-01

    within a data-intensive computation framework, which will be tailored to the specific needs of the community. It will provide a new interoperable infrastructure, as the computational backbone laying behind the publicly available interfaces. VERCE will have to face the challenges of implementing a service oriented architecture providing an efficient layer between the Data and the Grid infrastructures, coupling HPC data analysis and HPC data modeling applications through the execution of workflows and data sharing mechanism. Online registries of interoperable worklflow components, storage of intermediate results and data provenance are those aspects that are currently under investigations to make the VERCE facilities usable from a large scale of users, data and service providers. For such purposes the adoption of a Digital Object Architecture, to create online catalogs referencing and describing semantically all these distributed resources, such as datasets, computational processes and derivative products, is seen as one of the viable solution to monitor and steer the usage of the infrastructure, increasing its efficiency and the cooperation among the community.

  19. Protecting Critical Infrastructure by Identifying Pathways of Exposure to Risk

    Directory of Open Access Journals (Sweden)

    Philip O’Neill

    2013-08-01

    Full Text Available Increasingly, our critical infrastructure is managed and controlled by computers and the information networks that connect them. Cyber-terrorists and other malicious actors understand the economic and social impact that a successful attack on these systems could have. While it is imperative that we defend against such attacks, it is equally imperative that we realize how best to react to them. This article presents the strongest-path method of analyzing all potential pathways of exposure to risk – no matter how indirect or circuitous they may be – in a network model of infrastructure and operations. The method makes direct use of expert knowledge about entities and dependency relationships without the need for any simulation or any other models. By using path analysis in a directed graph model of critical infrastructure, planners can model and assess the effects of a potential attack and develop resilient responses.

  20. Evolving a lingua franca and associated software infrastructure for computational systems biology: the Systems Biology Markup Language (SBML) project.

    Science.gov (United States)

    Hucka, M; Finney, A; Bornstein, B J; Keating, S M; Shapiro, B E; Matthews, J; Kovitz, B L; Schilstra, M J; Funahashi, A; Doyle, J C; Kitano, H

    2004-06-01

    Biologists are increasingly recognising that computational modelling is crucial for making sense of the vast quantities of complex experimental data that are now being collected. The systems biology field needs agreed-upon information standards if models are to be shared, evaluated and developed cooperatively. Over the last four years, our team has been developing the Systems Biology Markup Language (SBML) in collaboration with an international community of modellers and software developers. SBML has become a de facto standard format for representing formal, quantitative and qualitative models at the level of biochemical reactions and regulatory networks. In this article, we summarise the current and upcoming versions of SBML and our efforts at developing software infrastructure for supporting and broadening its use. We also provide a brief overview of the many SBML-compatible software tools available today.

  1. Function Follows Performance in Evolutionary Computational Processing

    DEFF Research Database (Denmark)

    Pasold, Anke; Foged, Isak Worre

    2011-01-01

    As the title ‘Function Follows Performance in Evolutionary Computational Processing’ suggests, this paper explores the potentials of employing multiple design and evaluation criteria within one processing model in order to account for a number of performative parameters desired within varied...

  2. CUDA/GPU Technology : Parallel Programming For High Performance Scientific Computing

    OpenAIRE

    YUHENDRA; KUZE, Hiroaki; JOSAPHAT, Tetuko Sri Sumantyo

    2009-01-01

    [ABSTRACT]Graphics processing units (GP Us) originally designed for computer video cards have emerged as the most powerful chip in a high-performance workstation. In the high performance computation capabilities, graphic processing units (GPU) lead to much more powerful performance than conventional CPUs by means of parallel processing. In 2007, the birth of Compute Unified Device Architecture (CUDA) and CUDA-enabled GPUs by NVIDIA Corporation brought a revolution in the general purpose GPU a...

  3. Computer Self-Efficacy, Computer Anxiety, Performance and Personal Outcomes of Turkish Physical Education Teachers

    Science.gov (United States)

    Aktag, Isil

    2015-01-01

    The purpose of this study is to determine the computer self-efficacy, performance outcome, personal outcome, and affect and anxiety level of physical education teachers. Influence of teaching experience, computer usage and participation of seminars or in-service programs on computer self-efficacy level were determined. The subjects of this study…

  4. ATLAS Distributed Computing in LHC Run2

    CERN Document Server

    Campana, Simone; The ATLAS collaboration

    2015-01-01

    The ATLAS Distributed Computing infrastructure has evolved after the first period of LHC data taking in order to cope with the challenges of the upcoming LHC Run2. An increased data rate and computing demands of the Monte-Carlo simulation, as well as new approaches to ATLAS analysis, dictated a more dynamic workload management system (ProdSys2) and data management system (Rucio), overcoming the boundaries imposed by the design of the old computing model. In particular, the commissioning of new central computing system components was the core part of the migration toward the flexible computing model. The flexible computing utilization exploring the opportunistic resources such as HPC, cloud, and volunteer computing is embedded in the new computing model, the data access mechanisms have been enhanced with the remote access, and the network topology and performance is deeply integrated into the core of the system. Moreover a new data management strategy, based on defined lifetime for each dataset, has been defin...

  5. The CMS software performance at the start of data taking

    CERN Document Server

    Benelli, Gabriele

    2009-01-01

    The CMS software framework (CMSSW) is a complex project evolving very rapidly as the first LHC colliding beams approach. The computing requirements constrain performance in terms of CPU time, memory footprint and event size on disk to allow for planning and managing the computing infrastructure necessary to handle the needs of the experiment. A performance suite of tools has been developed to track all aspects of code performance, through the software release cycles, allowing for regression and guiding code development for optimization. In this talk, we describe the CMSSW performance suite tools used and present some sample performance results from the release integration process for the CMS software.

  6. Modelling the South African fruit export infrastructure: A case study

    Directory of Open Access Journals (Sweden)

    FG Ortmann

    2006-06-01

    Full Text Available A description is provided of work performed as part of the fruit logistics infrastructure project commissioned by the South African Deciduous Fruit Producers’ Trust and coordinated by the South African Council for Scientific and Industrial Research, as described in [Van Dyk FE & Maspero E, 2004, An analysis of the South African fruit logistics infrastructure, ORiON, 20(1, pp. 55–72]. After a brief introduction to the problem, two models (a single-commodity graph theoretic model and a multi-commodity mathematical programming model are derived for determining the maximal weekly flow or throughput of fresh fruit through the South African national export infrastructure. These models are solved for two extreme seasonal export scenarios and the solutions show that no export infrastructure expansion is required in the near future - observed bottlenecks are not fundamental to the infrastructure and its capacities, but are rather due to sub-optimal management and utilisation of the existing infrastructure.

  7. A high performance scientific cloud computing environment for materials simulations

    Science.gov (United States)

    Jorissen, K.; Vila, F. D.; Rehr, J. J.

    2012-09-01

    We describe the development of a scientific cloud computing (SCC) platform that offers high performance computation capability. The platform consists of a scientific virtual machine prototype containing a UNIX operating system and several materials science codes, together with essential interface tools (an SCC toolset) that offers functionality comparable to local compute clusters. In particular, our SCC toolset provides automatic creation of virtual clusters for parallel computing, including tools for execution and monitoring performance, as well as efficient I/O utilities that enable seamless connections to and from the cloud. Our SCC platform is optimized for the Amazon Elastic Compute Cloud (EC2). We present benchmarks for prototypical scientific applications and demonstrate performance comparable to local compute clusters. To facilitate code execution and provide user-friendly access, we have also integrated cloud computing capability in a JAVA-based GUI. Our SCC platform may be an alternative to traditional HPC resources for materials science or quantum chemistry applications.

  8. New developments in the CREAM Computing Element

    International Nuclear Information System (INIS)

    Andreetto, Paolo; Bertocco, Sara; Dorigo, Alvise; Capannini, Fabio; Cecchi, Marco; Zangrando, Luigi

    2012-01-01

    The EU-funded project EMI aims at providing a unified, standardized, easy to install software for distributed computing infrastructures. CREAM is one of the middleware products part of the EMI middleware distribution: it implements a Grid job management service which allows the submission, management and monitoring of computational jobs to local resource management systems. In this paper we discuss about some new features being implemented in the CREAM Computing Element. The implementation of the EMI Execution Service (EMI-ES) specification (an agreement in the EMI consortium on interfaces and protocols to be used in order to enable computational job submission and management required across technologies) is one of the new functions being implemented. New developments are also focusing in the High Availability (HA) area, to improve performance, scalability, availability and fault tolerance.

  9. Development of a Data Acquisition Program for the Purpose of Monitoring Processing Statistics Throughout the BaBar Online Computing Infrastructure's Farm Machines

    Energy Technology Data Exchange (ETDEWEB)

    Stonaha, P.

    2004-09-03

    A current shortcoming of the BaBar monitoring system is the lack of systematic gathering, archiving, and access to the running statistics of the BaBar Online Computing Infrastructure's farm machines. Using C, a program has been written to gather the raw data of each machine's running statistics and compute various rates and percentages that can be used for system monitoring. These rates and percentages then can be stored in an EPICS database for graphing, archiving, and future access. Graphical outputs show the reception of the data into the EPICS database. The C program can read if the data are 32- or 64-bit and correct for overflows. This program is not exclusive to BaBar and can be easily modified for any system.

  10. Space-Based Information Infrastructure Architecture for Broadband Services

    Science.gov (United States)

    Price, Kent M.; Inukai, Tom; Razdan, Rajendev; Lazeav, Yvonne M.

    1996-01-01

    This study addressed four tasks: (1) identify satellite-addressable information infrastructure markets; (2) perform network analysis for space-based information infrastructure; (3) develop conceptual architectures; and (4) economic assessment of architectures. The report concludes that satellites will have a major role in the national and global information infrastructure, requiring seamless integration between terrestrial and satellite networks. The proposed LEO, MEO, and GEO satellite systems have satellite characteristics that vary widely. They include delay, delay variations, poorer link quality and beam/satellite handover. The barriers against seamless interoperability between satellite and terrestrial networks are discussed. These barriers are the lack of compatible parameters, standards and protocols, which are presently being evaluated and reduced.

  11. Deploying and managing a cloud infrastructure real-world skills for the Comptia cloud+ certification and beyond exam CV0-001

    CERN Document Server

    Salam, Abdul; Ul Haq, Salman

    2015-01-01

    Learn in-demand cloud computing skills from industry experts Deploying and Managing a Cloud Infrastructure is an excellent resource for IT professionals seeking to tap into the demand for cloud administrators. This book helps prepare candidates for the CompTIA Cloud+ Certification (CV0-001) cloud computing certification exam. Designed for IT professionals with 2-3 years of networking experience, this certification provides validation of your cloud infrastructure knowledge. With over 30 years of combined experience in cloud computing, the author team provides the latest expert perspectives on

  12. BEAM: A computational workflow system for managing and modeling material characterization data in HPC environments

    Energy Technology Data Exchange (ETDEWEB)

    Lingerfelt, Eric J [ORNL; Endeve, Eirik [ORNL; Ovchinnikov, Oleg S [ORNL; Borreguero Calvo, Jose M [ORNL; Park, Byung H [ORNL; Archibald, Richard K [ORNL; Symons, Christopher T [ORNL; Kalinin, Sergei V [ORNL; Messer, Bronson [ORNL; Shankar, Mallikarjun [ORNL; Jesse, Stephen [ORNL

    2016-01-01

    Improvements in scientific instrumentation allow imaging at mesoscopic to atomic length scales, many spectroscopic modes, and now with the rise of multimodal acquisition systems and the associated processing capability the era of multidimensional, informationally dense data sets has arrived. Technical issues in these combinatorial scientific fields are exacerbated by computational challenges best summarized as a necessity for drastic improvement in the capability to transfer, store, and analyze large volumes of data. The Bellerophon Environment for Analysis of Materials (BEAM) platform provides material scientists the capability to directly leverage the integrated computational and analytical power of High Performance Computing (HPC) to perform scalable data analysis and simulation via an intuitive, cross-platform client user interface. This framework delivers authenticated, push-button execution of complex user workflows that deploy data analysis algorithms and computational simulations utilizing the converged compute-and-data infrastructure at Oak Ridge National Laboratory s (ORNL) Compute and Data Environment for Science (CADES) and HPC environments like Titan at the Oak Ridge Leadership Computing Facility (OLCF). In this work we address the underlying HPC needs for characterization in the material science community, elaborate how BEAM s design and infrastructure tackle those needs, and present a small sub-set of user cases where scientists utilized BEAM across a broad range of analytical techniques and analysis modes.

  13. Cloud computing methods and practical approaches

    CERN Document Server

    Mahmood, Zaigham

    2013-01-01

    This book presents both state-of-the-art research developments and practical guidance on approaches, technologies and frameworks for the emerging cloud paradigm. Topics and features: presents the state of the art in cloud technologies, infrastructures, and service delivery and deployment models; discusses relevant theoretical frameworks, practical approaches and suggested methodologies; offers guidance and best practices for the development of cloud-based services and infrastructures, and examines management aspects of cloud computing; reviews consumer perspectives on mobile cloud computing an

  14. Armenia - Irrigation Infrastructure

    Data.gov (United States)

    Millennium Challenge Corporation — This study evaluates irrigation infrastructure rehabilitation in Armenia. The study separately examines the impacts of tertiary canals and other large infrastructure...

  15. A Multidisciplinary Research Framework on Green Schools: Infrastructure, Social Environment, Occupant Health, and Performance.

    Science.gov (United States)

    Magzamen, Sheryl; Mayer, Adam P; Barr, Stephanie; Bohren, Lenora; Dunbar, Brian; Manning, Dale; Reynolds, Stephen J; Schaeffer, Joshua W; Suter, Jordan; Cross, Jennifer E

    2017-05-01

    Sustainable school buildings hold much promise to reducing operating costs, improve occupant well-being and, ultimately, teacher and student performance. However, there is a scarcity of evidence on the effects of sustainable school buildings on health and performance indicators. We sought to create a framework for a multidisciplinary research agenda that links school facilities, health, and educational outcomes. We conducted a nonsystematic review of peer review publications, government documents, organizational documents, and school climate measurement instruments. We found that studies on the impact of physical environmental factors (air, lighting, and thermal comfort) on health and occupant performance are largely independent of research on the social climate. The current literature precludes the formation of understanding the causal relation among school facilities, social climate, occupant health, and occupant performance. Given the average age of current school facilities in the United States, construction of new school facilities or retrofits of older facilities will be a major infrastructure investment for many municipalities over the next several decades. Multidisciplinary research that seeks to understand the impact of sustainable design on the health and performance of occupants will need to include both an environmental science and social science perspective to inform best practices and quantification of benefits that go beyond general measures of costs savings from energy efficiencies. © 2017, American School Health Association.

  16. Final Report Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

    Energy Technology Data Exchange (ETDEWEB)

    O' Leary, Patrick [Kitware, Inc., Clifton Park, NY (United States)

    2017-09-13

    The primary challenge motivating this project is the widening gap between the ability to compute information and to store it for subsequent analysis. This gap adversely impacts science code teams, who can perform analysis only on a small fraction of the data they calculate, resulting in the substantial likelihood of lost or missed science, when results are computed but not analyzed. Our approach is to perform as much analysis or visualization processing on data while it is still resident in memory, which is known as in situ processing. The idea in situ processing was not new at the time of the start of this effort in 2014, but efforts in that space were largely ad hoc, and there was no concerted effort within the research community that aimed to foster production-quality software tools suitable for use by Department of Energy (DOE) science projects. Our objective was to produce and enable the use of production-quality in situ methods and infrastructure, at scale, on DOE high-performance computing (HPC) facilities, though we expected to have an impact beyond DOE due to the widespread nature of the challenges, which affect virtually all large-scale computational science efforts. To achieve this objective, we engaged in software technology research and development (R&D), in close partnerships with DOE science code teams, to produce software technologies that were shown to run efficiently at scale on DOE HPC platforms.

  17. Assessing the risk posed by natural hazards to infrastructures

    Science.gov (United States)

    Eidsvig, Unni Marie K.; Kristensen, Krister; Vidar Vangelsten, Bjørn

    2017-03-01

    This paper proposes a model for assessing the risk posed by natural hazards to infrastructures, with a focus on the indirect losses and loss of stability for the population relying on the infrastructure. The model prescribes a three-level analysis with increasing level of detail, moving from qualitative to quantitative analysis. The focus is on a methodology for semi-quantitative analyses to be performed at the second level. The purpose of this type of analysis is to perform a screening of the scenarios of natural hazards threatening the infrastructures, identifying the most critical scenarios and investigating the need for further analyses (third level). The proposed semi-quantitative methodology considers the frequency of the natural hazard, different aspects of vulnerability, including the physical vulnerability of the infrastructure itself, and the societal dependency on the infrastructure. An indicator-based approach is applied, ranking the indicators on a relative scale according to pre-defined ranking criteria. The proposed indicators, which characterise conditions that influence the probability of an infrastructure malfunctioning caused by a natural event, are defined as (1) robustness and buffer capacity, (2) level of protection, (3) quality/level of maintenance and renewal, (4) adaptability and quality of operational procedures and (5) transparency/complexity/degree of coupling. Further indicators describe conditions influencing the socio-economic consequences of the infrastructure malfunctioning, such as (1) redundancy and/or substitution, (2) cascading effects and dependencies, (3) preparedness and (4) early warning, emergency response and measures. The aggregated risk estimate is a combination of the semi-quantitative vulnerability indicators, as well as quantitative estimates of the frequency of the natural hazard, the potential duration of the infrastructure malfunctioning (e.g. depending on the required restoration effort) and the number of users of

  18. Building an Agent-Based Laboratory Infrastructure for Higher Education

    Directory of Open Access Journals (Sweden)

    Muna Saqer

    2009-08-01

    Full Text Available We present an ongoing project at the University of Houston- Downtown (UHD that aims to build a grid as a laboratory environment to support undergraduate education. We intend to use this PC clusters centered grid to allow students to perform laboratory exercises through web interfaces. In order to accommodate lab packages of a growing number of courses, we design the system as a modular system using multi-agent modeling. Students are recruited to implement the units of the system as senior student project topics or research activities sponsored by the Scholar's Academy of UHD. Through these projects, we geared our research toward higher education and provided students with opportunities to participate in building a computational infrastructure for curriculum improvement. This is very important for a minority-serving institution (MSI with limited resources such as UHD.

  19. EGI-EUDAT integration activity - Pair data and high-throughput computing resources together

    Science.gov (United States)

    Scardaci, Diego; Viljoen, Matthew; Vitlacil, Dejan; Fiameni, Giuseppe; Chen, Yin; sipos, Gergely; Ferrari, Tiziana

    2016-04-01

    relevant European Research infrastructure in the field of Earth Science (EPOS and ICOS), Bioinformatics (BBMRI and ELIXIR) and Space Physics (EISCAT-3D). The first outcome of this activity has been the definition of a generic use case that captures the typical user scenario with respect the integrated use of the EGI and EUDAT infrastructures. This generic use case allows a user to instantiate a set of Virtual Machine images on the EGI Federated Cloud to perform computational jobs that analyse data previously stored on EUDAT long-term storage systems. The results of such analysis can be staged back to EUDAT storages, and if needed, allocated with Permanent identifyers (PIDs) for future use. The implementation of this generic use case requires the following integration activities between EGI and EUDAT: (1) harmonisation of the user authentication and authorisation models, (2) implementing interface connectors between the relevant EGI and EUDAT services, particularly EGI Cloud compute facilities and EUDAT long-term storage and PID systems. In the presentation, the collected user requirements and the implementation status of the universal use case will be showed. Furthermore, how the universal use case is currently applied to satisfy EPOS and ICOS needs will be described.

  20. First Experiences with LHC Grid Computing and Distributed Analysis

    CERN Document Server

    Fisk, Ian

    2010-01-01

    In this presentation the experiences of the LHC experiments using grid computing were presented with a focus on experience with distributed analysis. After many years of development, preparation, exercises, and validation the LHC (Large Hadron Collider) experiments are in operations. The computing infrastructure has been heavily utilized in the first 6 months of data collection. The general experience of exploiting the grid infrastructure for organized processing and preparation is described, as well as the successes employing the infrastructure for distributed analysis. At the end the expected evolution and future plans are outlined.