Development of integrated platform for computational material design

International Nuclear Information System (INIS)

Kiyoshi, Matsubara; Kumi, Itai; Nobutaka, Nishikawa; Akifumi, Kato; Hideaki, Koike

2003-01-01

The goal of our project is to design and develop a problem-solving environment (PSE) that will help computational scientists and engineers develop large complicated application software and simulate complex phenomena by using networking and parallel computing. The integrated platform, which is designed for PSE in the Japanese national project of Frontier Simulation Software for Industrial Science, is defined by supporting the entire range of problem solving activity from program formulation and data setup to numerical simulation, data management, and visualization. A special feature of our integrated platform is based on a new architecture called TASK FLOW. It integrates the computational resources such as hardware and software on the network and supports complex and large-scale simulation. This concept is applied to computational material design and the project 'comprehensive research for modeling, analysis, control, and design of large-scale complex system considering properties of human being'. Moreover this system will provide the best solution for developing large and complicated software and simulating complex and large-scaled phenomena in computational science and engineering. A prototype has already been developed and the validation and verification of an integrated platform will be scheduled by using the prototype in 2003. In the validation and verification, fluid-structure coupling analysis system for designing an industrial machine will be developed on the integrated platform. As other examples of validation and verification, integrated platform for quantum chemistry and bio-mechanical system are planned

The Challenges of Designing Digital Services for Multiple Mobile Platforms

DEFF Research Database (Denmark)

Ghazawneh, Ahmad

2016-01-01

on a multiple case study of three mobile application development firms from Sweden, Denmark and Norway, we synthesize the digital service design taxonomy to understand the challenges faced by third-party developers. Our study identifies a set of challenges in four different levels: user level, platform level...... to tap into and join the digital ecosystem. However, while there is an emerging literature on designing digital services, little empirical evidence exists about challenges faced by third-party developers while designing digital services, and in particular for multiple mobile platforms. Drawing......The value of digital services is increasingly recognized by owners of digital platforms. These services have central role in building and sustaining the business of the digital platform. In order to sustain the design of digital services, owners of digital platforms encourage third-party developers...

The TeraShake Computational Platform for Large-Scale Earthquake Simulations

Science.gov (United States)

Cui, Yifeng; Olsen, Kim; Chourasia, Amit; Moore, Reagan; Maechling, Philip; Jordan, Thomas

Geoscientific and computer science researchers with the Southern California Earthquake Center (SCEC) are conducting a large-scale, physics-based, computationally demanding earthquake system science research program with the goal of developing predictive models of earthquake processes. The computational demands of this program continue to increase rapidly as these researchers seek to perform physics-based numerical simulations of earthquake processes for larger meet the needs of this research program, a multiple-institution team coordinated by SCEC has integrated several scientific codes into a numerical modeling-based research tool we call the TeraShake computational platform (TSCP). A central component in the TSCP is a highly scalable earthquake wave propagation simulation program called the TeraShake anelastic wave propagation (TS-AWP) code. In this chapter, we describe how we extended an existing, stand-alone, wellvalidated, finite-difference, anelastic wave propagation modeling code into the highly scalable and widely used TS-AWP and then integrated this code into the TeraShake computational platform that provides end-to-end (initialization to analysis) research capabilities. We also describe the techniques used to enhance the TS-AWP parallel performance on TeraGrid supercomputers, as well as the TeraShake simulations phases including input preparation, run time, data archive management, and visualization. As a result of our efforts to improve its parallel efficiency, the TS-AWP has now shown highly efficient strong scaling on over 40K processors on IBM’s BlueGene/L Watson computer. In addition, the TSCP has developed into a computational system that is useful to many members of the SCEC community for performing large-scale earthquake simulations.

A mobile and portable trusted computing platform

Directory of Open Access Journals (Sweden)

Nepal Surya

2011-01-01

Full Text Available Abstract The mechanism of establishing trust in a computing platform is tightly coupled with the characteristics of a specific machine. This limits the portability and mobility of trust as demanded by many emerging applications that go beyond the organizational boundaries. In order to address this problem, we propose a mobile and portable trusted computing platform in a form of a USB device. First, we describe the design and implementation of the hardware and software architectures of the device. We then demonstrate the capabilities of the proposed device by developing a trusted application.

Trusted computing platforms TPM2.0 in context

CERN Document Server

Proudler, Graeme; Dalton, Chris

2015-01-01

In this book the authors first describe the background of trusted platforms and trusted computing and speculate about the future. They then describe the technical features and architectures of trusted platforms from several different perspectives, finally explaining second-generation TPMs, including a technical description intended to supplement the Trusted Computing Group's TPM2 specifications. The intended audience is IT managers and engineers and graduate students in information security.

Targeting multiple heterogeneous hardware platforms with OpenCL

Science.gov (United States)

Fox, Paul A.; Kozacik, Stephen T.; Humphrey, John R.; Paolini, Aaron; Kuller, Aryeh; Kelmelis, Eric J.

2014-06-01

The OpenCL API allows for the abstract expression of parallel, heterogeneous computing, but hardware implementations have substantial implementation differences. The abstractions provided by the OpenCL API are often insufficiently high-level to conceal differences in hardware architecture. Additionally, implementations often do not take advantage of potential performance gains from certain features due to hardware limitations and other factors. These factors make it challenging to produce code that is portable in practice, resulting in much OpenCL code being duplicated for each hardware platform being targeted. This duplication of effort offsets the principal advantage of OpenCL: portability. The use of certain coding practices can mitigate this problem, allowing a common code base to be adapted to perform well across a wide range of hardware platforms. To this end, we explore some general practices for producing performant code that are effective across platforms. Additionally, we explore some ways of modularizing code to enable optional optimizations that take advantage of hardware-specific characteristics. The minimum requirement for portability implies avoiding the use of OpenCL features that are optional, not widely implemented, poorly implemented, or missing in major implementations. Exposing multiple levels of parallelism allows hardware to take advantage of the types of parallelism it supports, from the task level down to explicit vector operations. Static optimizations and branch elimination in device code help the platform compiler to effectively optimize programs. Modularization of some code is important to allow operations to be chosen for performance on target hardware. Optional subroutines exploiting explicit memory locality allow for different memory hierarchies to be exploited for maximum performance. The C preprocessor and JIT compilation using the OpenCL runtime can be used to enable some of these techniques, as well as to factor in hardware

ALICE Connex : Mobile Volunteer Computing and Edutainment Platform

CERN Document Server

Chalumporn, Gantaphon

2016-01-01

Mobile devices are very powerful and trend to be developed. They have functions that are used in everyday life. One of their main tasks is to be an entertainment devices or gaming platform. A lot of technologies are now accepted and adopted to improve the potential of education. Edutainment is a combination of entertainment and education media together to make use of both benefits. In this work, we introduce a design of edutainment platform which is a part of mobile volunteer computing and edutainment platform called ‘ALICE Connex’ for ALICE at CERN. The edutainment platform focuses to deliver enjoyment and education, while promotes ALICE and Volunteer Computing platform to general public. The design in this work describes the functionality to build an effective edutainment with real-time multiplayer interaction on round-based gameplay, while integrates seamless edutainment with basic particle physic content though game mechanism and items design. For the assessment method we will observe the enjoyment o...

Model Infrastruktur dan Manajemen Platform Server Berbasis Cloud Computing

Directory of Open Access Journals (Sweden)

Mulki Indana Zulfa

2017-11-01

Full Text Available Cloud computing is a new technology that is still very rapidly growing. This technology makes the Internet as the main media for the management of data and applications remotely. Cloud computing allows users to run an application without having to think about infrastructure and its platforms. Other technical aspects such as memory, storage, backup and restore, can be done very easily. This research is intended to modeling the infrastructure and management of computer platform in computer network of Faculty of Engineering, University of Jenderal Soedirman. The first stage in this research is literature study, by finding out the implementation model in previous research. Then the result will be combined with a new approach to existing resources and try to implement directly on the existing server network. The results showed that the implementation of cloud computing technology is able to replace the existing platform network.

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.

Essential Means for Urban Computing: Specification of Web-Based Computing Platforms for Urban Planning, a Hitchhiker’s Guide

Directory of Open Access Journals (Sweden)

Pirouz Nourian

2018-03-01

Full Text Available This article provides an overview of the specifications of web-based computing platforms for urban data analytics and computational urban planning practice. There are currently a variety of tools and platforms that can be used in urban computing practices, including scientific computing languages, interactive web languages, data sharing platforms and still many desktop computing environments, e.g., GIS software applications. We have reviewed a list of technologies considering their potential and applicability in urban planning and urban data analytics. This review is not only based on the technical factors such as capabilities of the programming languages but also the ease of developing and sharing complex data processing workflows. The arena of web-based computing platforms is currently under rapid development and is too volatile to be predictable; therefore, in this article we focus on the specification of the requirements and potentials from an urban planning point of view rather than speculating about the fate of computing platforms or programming languages. The article presents a list of promising computing technologies, a technical specification of the essential data models and operators for geo-spatial data processing, and mathematical models for an ideal urban computing platform.

Essential Means for Urban Computing: Specification of Web-Based Computing Platforms for Urban Planning, a Hitchhiker’s Guide

OpenAIRE

Pirouz Nourian; Carlos Martinez-Ortiz; Ken Arroyo Ohori

2018-01-01

This article provides an overview of the specifications of web-based computing platforms for urban data analytics and computational urban planning practice. There are currently a variety of tools and platforms that can be used in urban computing practices, including scientific computing languages, interactive web languages, data sharing platforms and still many desktop computing environments, e.g., GIS software applications. We have reviewed a list of technologies considering their potential ...

Architectural analysis for wirelessly powered computing platforms

NARCIS (Netherlands)

Kapoor, A.; Pineda de Gyvez, J.

2013-01-01

We present a design framework for wirelessly powered generic computing platforms that takes into account various system parameters in response to a time-varying energy source. These parameters are the charging profile of the energy source, computing speed (fclk), digital supply voltage (VDD), energy

Essential Means for Urban Computing : Specification of Web-Based Computing Platforms for Urban Planning, a Hitchhiker’s Guide

NARCIS (Netherlands)

Nourian, P.; Martinez-Ortiz, Carlos; Arroyo Ohori, G.A.K.

2018-01-01

This article provides an overview of the specifications of web-based computing platforms for urban data analytics and computational urban planning practice. There are currently a variety of tools and platforms that can be used in urban computing practices, including scientific computing languages,

Hierarchical Parallel Matrix Multiplication on Large-Scale Distributed Memory Platforms

KAUST Repository

Quintin, Jean-Noel

2013-10-01

Matrix multiplication is a very important computation kernel both in its own right as a building block of many scientific applications and as a popular representative for other scientific applications. Cannon\\'s algorithm which dates back to 1969 was the first efficient algorithm for parallel matrix multiplication providing theoretically optimal communication cost. However this algorithm requires a square number of processors. In the mid-1990s, the SUMMA algorithm was introduced. SUMMA overcomes the shortcomings of Cannon\\'s algorithm as it can be used on a nonsquare number of processors as well. Since then the number of processors in HPC platforms has increased by two orders of magnitude making the contribution of communication in the overall execution time more significant. Therefore, the state of the art parallel matrix multiplication algorithms should be revisited to reduce the communication cost further. This paper introduces a new parallel matrix multiplication algorithm, Hierarchical SUMMA (HSUMMA), which is a redesign of SUMMA. Our algorithm reduces the communication cost of SUMMA by introducing a two-level virtual hierarchy into the two-dimensional arrangement of processors. Experiments on an IBM BlueGene/P demonstrate the reduction of communication cost up to 2.08 times on 2048 cores and up to 5.89 times on 16384 cores. © 2013 IEEE.

Hierarchical Parallel Matrix Multiplication on Large-Scale Distributed Memory Platforms

KAUST Repository

Quintin, Jean-Noel; Hasanov, Khalid; Lastovetsky, Alexey

2013-01-01

Matrix multiplication is a very important computation kernel both in its own right as a building block of many scientific applications and as a popular representative for other scientific applications. Cannon's algorithm which dates back to 1969 was the first efficient algorithm for parallel matrix multiplication providing theoretically optimal communication cost. However this algorithm requires a square number of processors. In the mid-1990s, the SUMMA algorithm was introduced. SUMMA overcomes the shortcomings of Cannon's algorithm as it can be used on a nonsquare number of processors as well. Since then the number of processors in HPC platforms has increased by two orders of magnitude making the contribution of communication in the overall execution time more significant. Therefore, the state of the art parallel matrix multiplication algorithms should be revisited to reduce the communication cost further. This paper introduces a new parallel matrix multiplication algorithm, Hierarchical SUMMA (HSUMMA), which is a redesign of SUMMA. Our algorithm reduces the communication cost of SUMMA by introducing a two-level virtual hierarchy into the two-dimensional arrangement of processors. Experiments on an IBM BlueGene/P demonstrate the reduction of communication cost up to 2.08 times on 2048 cores and up to 5.89 times on 16384 cores. © 2013 IEEE.

Micromagnetics on high-performance workstation and mobile computational platforms

Science.gov (United States)

Fu, S.; Chang, R.; Couture, S.; Menarini, M.; Escobar, M. A.; Kuteifan, M.; Lubarda, M.; Gabay, D.; Lomakin, V.

2015-05-01

The feasibility of using high-performance desktop and embedded mobile computational platforms is presented, including multi-core Intel central processing unit, Nvidia desktop graphics processing units, and Nvidia Jetson TK1 Platform. FastMag finite element method-based micromagnetic simulator is used as a testbed, showing high efficiency on all the platforms. Optimization aspects of improving the performance of the mobile systems are discussed. The high performance, low cost, low power consumption, and rapid performance increase of the embedded mobile systems make them a promising candidate for micromagnetic simulations. Such architectures can be used as standalone systems or can be built as low-power computing clusters.

ZIVIS: A City Computing Platform Based on Volunteer Computing

International Nuclear Information System (INIS)

Antoli, B.; Castejon, F.; Giner, A.; Losilla, G.; Reynolds, J. M.; Rivero, A.; Sangiao, S.; Serrano, F.; Tarancon, A.; Valles, R.; Velasco, J. L.

2007-01-01

Abstract Volunteer computing has come up as a new form of distributed computing. Unlike other computing paradigms like Grids, which use to be based on complex architectures, volunteer computing has demonstrated a great ability to integrate dispersed, heterogeneous computing resources with ease. This article presents ZIVIS, a project which aims to deploy a city-wide computing platform in Zaragoza (Spain). ZIVIS is based on BOINC (Berkeley Open Infrastructure for Network Computing), a popular open source framework to deploy volunteer and desktop grid computing systems. A scientific code which simulates the trajectories of particles moving inside a stellarator fusion device, has been chosen as the pilot application of the project. In this paper we describe the approach followed to port the code to the BOINC framework as well as some novel techniques, based on standard Grid protocols, we have used to access the output data present in the BOINC server from a remote visualizer. (Author)

Application research of cloud computing in emergency system platform of nuclear accidents

International Nuclear Information System (INIS)

Zhang Yan; Yue Huiguo; Lin Quanyi; Yue Feng

2013-01-01

This paper described the key technology of the concept of cloud computing, service type and implementation methods. Combined with the upgrade demand of nuclear accident emergency system platform, the paper also proposed the application design of private cloud computing platform, analyzed safety of cloud platform and the characteristics of cloud disaster recovery. (authors)

Hypergraph partitioning implementation for parallelizing matrix-vector multiplication using CUDA GPU-based parallel computing

Science.gov (United States)

Murni, Bustamam, A.; Ernastuti, Handhika, T.; Kerami, D.

2017-07-01

Calculation of the matrix-vector multiplication in the real-world problems often involves large matrix with arbitrary size. Therefore, parallelization is needed to speed up the calculation process that usually takes a long time. Graph partitioning techniques that have been discussed in the previous studies cannot be used to complete the parallelized calculation of matrix-vector multiplication with arbitrary size. This is due to the assumption of graph partitioning techniques that can only solve the square and symmetric matrix. Hypergraph partitioning techniques will overcome the shortcomings of the graph partitioning technique. This paper addresses the efficient parallelization of matrix-vector multiplication through hypergraph partitioning techniques using CUDA GPU-based parallel computing. CUDA (compute unified device architecture) is a parallel computing platform and programming model that was created by NVIDIA and implemented by the GPU (graphics processing unit).

Interactive Computer-Assisted Instruction in Acid-Base Physiology for Mobile Computer Platforms

Science.gov (United States)

Longmuir, Kenneth J.

2014-01-01

In this project, the traditional lecture hall presentation of acid-base physiology in the first-year medical school curriculum was replaced by interactive, computer-assisted instruction designed primarily for the iPad and other mobile computer platforms. Three learning modules were developed, each with ~20 screens of information, on the subjects…

Reliability Assessment of Cloud Computing Platform Based on Semiquantitative Information and Evidential Reasoning

Directory of Open Access Journals (Sweden)

Hang Wei

2016-01-01

Full Text Available A reliability assessment method based on evidential reasoning (ER rule and semiquantitative information is proposed in this paper, where a new reliability assessment architecture including four aspects with both quantitative data and qualitative knowledge is established. The assessment architecture is more objective in describing complex dynamic cloud computing environment than that in traditional method. In addition, the ER rule which has good performance for multiple attribute decision making problem is employed to integrate different types of the attributes in assessment architecture, which can obtain more accurate assessment results. The assessment results of the case study in an actual cloud computing platform verify the effectiveness and the advantage of the proposed method.

[Construction and analysis of a monitoring system with remote real-time multiple physiological parameters based on cloud computing].

Science.gov (United States)

Zhu, Lingyun; Li, Lianjie; Meng, Chunyan

2014-12-01

There have been problems in the existing multiple physiological parameter real-time monitoring system, such as insufficient server capacity for physiological data storage and analysis so that data consistency can not be guaranteed, poor performance in real-time, and other issues caused by the growing scale of data. We therefore pro posed a new solution which was with multiple physiological parameters and could calculate clustered background data storage and processing based on cloud computing. Through our studies, a batch processing for longitudinal analysis of patients' historical data was introduced. The process included the resource virtualization of IaaS layer for cloud platform, the construction of real-time computing platform of PaaS layer, the reception and analysis of data stream of SaaS layer, and the bottleneck problem of multi-parameter data transmission, etc. The results were to achieve in real-time physiological information transmission, storage and analysis of a large amount of data. The simulation test results showed that the remote multiple physiological parameter monitoring system based on cloud platform had obvious advantages in processing time and load balancing over the traditional server model. This architecture solved the problems including long turnaround time, poor performance of real-time analysis, lack of extensibility and other issues, which exist in the traditional remote medical services. Technical support was provided in order to facilitate a "wearable wireless sensor plus mobile wireless transmission plus cloud computing service" mode moving towards home health monitoring for multiple physiological parameter wireless monitoring.

Cross-Platform Learning: On the Nature of Children's Learning from Multiple Media Platforms

Science.gov (United States)

Fisch, Shalom M.

2013-01-01

It is increasingly common for an educational media project to span several media platforms (e.g., TV, Web, hands-on materials), assuming that the benefits of learning from multiple media extend beyond those gained from one medium alone. Yet research typically has investigated learning from a single medium in isolation. This paper reviews several…

Design Patterns for Sparse-Matrix Computations on Hybrid CPU/GPU Platforms

Directory of Open Access Journals (Sweden)

Valeria Cardellini

2014-01-01

Full Text Available We apply object-oriented software design patterns to develop code for scientific software involving sparse matrices. Design patterns arise when multiple independent developments produce similar designs which converge onto a generic solution. We demonstrate how to use design patterns to implement an interface for sparse matrix computations on NVIDIA GPUs starting from PSBLAS, an existing sparse matrix library, and from existing sets of GPU kernels for sparse matrices. We also compare the throughput of the PSBLAS sparse matrix–vector multiplication on two platforms exploiting the GPU with that obtained by a CPU-only PSBLAS implementation. Our experiments exhibit encouraging results regarding the comparison between CPU and GPU executions in double precision, obtaining a speedup of up to 35.35 on NVIDIA GTX 285 with respect to AMD Athlon 7750, and up to 10.15 on NVIDIA Tesla C2050 with respect to Intel Xeon X5650.

Numeric computation and statistical data analysis on the Java platform

CERN Document Server

Chekanov, Sergei V

2016-01-01

Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language. The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages. Numeric Computation and Statistical Data Analysis ...

A wireless computational platform for distributed computing based traffic monitoring involving mixed Eulerian-Lagrangian sensing

KAUST Repository

Jiang, Jiming

2013-06-01

This paper presents a new wireless platform designed for an integrated traffic monitoring system based on combined Lagrangian (mobile) and Eulerian (fixed) sensing. The sensor platform is built around a 32-bit ARM Cortex M4 micro-controller and a 2.4GHz 802.15.4 ISM compliant radio module, and can be interfaced with fixed traffic sensors, or receive data from vehicle transponders. The platform is specially designed and optimized to be integrated in a solar-powered wireless sensor network in which traffic flow maps are computed by the nodes directly using distributed computing. A MPPT circuitry is proposed to increase the power output of the attached solar panel. A self-recovering unit is designed to increase reliability and allow periodic hard resets, an essential requirement for sensor networks. A radio monitoring circuitry is proposed to monitor incoming and outgoing transmissions, simplifying software debug. An ongoing implementation is briefly discussed, and compared with existing platforms used in wireless sensor networks. © 2013 IEEE.

Platform-independent method for computer aided schematic drawings

Science.gov (United States)

Vell, Jeffrey L [Slingerlands, NY; Siganporia, Darius M [Clifton Park, NY; Levy, Arthur J [Fort Lauderdale, FL

2012-02-14

A CAD/CAM method is disclosed for a computer system to capture and interchange schematic drawing and associated design information. The schematic drawing and design information are stored in an extensible, platform-independent format.

Cloud computing for comparative genomics with windows azure platform.

Science.gov (United States)

Kim, Insik; Jung, Jae-Yoon; Deluca, Todd F; Nelson, Tristan H; Wall, Dennis P

2012-01-01

Cloud computing services have emerged as a cost-effective alternative for cluster systems as the number of genomes and required computation power to analyze them increased in recent years. Here we introduce the Microsoft Azure platform with detailed execution steps and a cost comparison with Amazon Web Services.

WCDMA Uplink Interference Assessment from Multiple High Altitude Platform Configurations

Directory of Open Access Journals (Sweden)

Grace D

2008-01-01

Full Text Available Abstract We investigate the possibility of multiple high altitude platform (HAP coverage of a common cell area using a wideband code division multiple access (WCDMA system. In particular, we study the uplink system performance of the system. The results show that depending on the traffic demand and the type of service used, there is a possibility of deploying 3–6 HAPs covering the same cell area. The results also show the effect of cell radius on performance and the position of the multiple HAP base stations which give the worst performance.

Model-driven product line engineering for mapping parallel algorithms to parallel computing platforms

NARCIS (Netherlands)

Arkin, Ethem; Tekinerdogan, Bedir

2016-01-01

Mapping parallel algorithms to parallel computing platforms requires several activities such as the analysis of the parallel algorithm, the definition of the logical configuration of the platform, the mapping of the algorithm to the logical configuration platform and the implementation of the

The Study of Pallet Pooling Information Platform Based on Cloud Computing

Directory of Open Access Journals (Sweden)

Jia-bin Li

2018-01-01

Full Text Available Effective implementation of pallet pooling system needs a strong information platform to support. Through the analysis of existing pallet pooling information platform (PPIP, the paper pointed out that the existing studies of PPIP are mainly based on traditional IT infrastructures and technologies which have software, hardware, resource utilization, and process restrictions. Because of the advantages of cloud computing technology like strong computing power, high flexibility, and low cost which meet the requirements of the PPIP well, this paper gave a PPIP architecture of two parts based on cloud computing: the users client and the cloud services. The cloud services include three layers, which are IaaS, PaaS, and SaaS. The method of how to deploy PPIP based on cloud computing is proposed finally.

Bioinformatics on the Cloud Computing Platform Azure

Science.gov (United States)

Shanahan, Hugh P.; Owen, Anne M.; Harrison, Andrew P.

2014-01-01

We discuss the applicability of the Microsoft cloud computing platform, Azure, for bioinformatics. We focus on the usability of the resource rather than its performance. We provide an example of how R can be used on Azure to analyse a large amount of microarray expression data deposited at the public database ArrayExpress. We provide a walk through to demonstrate explicitly how Azure can be used to perform these analyses in Appendix S1 and we offer a comparison with a local computation. We note that the use of the Platform as a Service (PaaS) offering of Azure can represent a steep learning curve for bioinformatics developers who will usually have a Linux and scripting language background. On the other hand, the presence of an additional set of libraries makes it easier to deploy software in a parallel (scalable) fashion and explicitly manage such a production run with only a few hundred lines of code, most of which can be incorporated from a template. We propose that this environment is best suited for running stable bioinformatics software by users not involved with its development. PMID:25050811

Simulating next-generation Cyber-physical computing platforms

OpenAIRE

Burgio, Paolo; Álvarez Martínez, Carlos; Ayguadé Parra, Eduard; Filgueras Izquierdo, Antonio; Jiménez González, Daniel; Martorell Bofill, Xavier; Navarro, Nacho; Giorgi, Roberto

2015-01-01

In specific domains, such as cyber-physical systems, platforms are quickly evolving to include multiple (many-) cores and programmable logic in a single system-on-chip, while includ- ing interfaces to commodity sensors/actuators. Programmable Logic (e.g., FPGA) allows for greater flexibility and dependability. However, the task of extracting the performance/watt potentia l of heterogeneous many-cores is often demanded at the application level, and this h...

A Platform-Independent Plugin for Navigating Online Radiology Cases.

Science.gov (United States)

Balkman, Jason D; Awan, Omer A

2016-06-01

Software methods that enable navigation of radiology cases on various digital platforms differ between handheld devices and desktop computers. This has resulted in poor compatibility of online radiology teaching files across mobile smartphones, tablets, and desktop computers. A standardized, platform-independent, or "agnostic" approach for presenting online radiology content was produced in this work by leveraging modern hypertext markup language (HTML) and JavaScript web software technology. We describe the design and evaluation of this software, demonstrate its use across multiple viewing platforms, and make it publicly available as a model for future development efforts.

WCDMA Uplink Interference Assessment from Multiple High Altitude Platform Configurations

Directory of Open Access Journals (Sweden)

A. Mohammed

2008-06-01

Full Text Available We investigate the possibility of multiple high altitude platform (HAP coverage of a common cell area using a wideband code division multiple access (WCDMA system. In particular, we study the uplink system performance of the system. The results show that depending on the traffic demand and the type of service used, there is a possibility of deploying 3–6 HAPs covering the same cell area. The results also show the effect of cell radius on performance and the position of the multiple HAP base stations which give the worst performance.

+Cloud: An Agent-Based Cloud Computing Platform

OpenAIRE

González, Roberto; Hernández de la Iglesia, Daniel; de la Prieta Pintado, Fernando; Gil González, Ana Belén

2017-01-01

Cloud computing is revolutionizing the services provided through the Internet, and is continually adapting itself in order to maintain the quality of its services. This study presents the platform +Cloud, which proposes a cloud environment for storing information and files by following the cloud paradigm. This study also presents Warehouse 3.0, a cloud-based application that has been developed to validate the services provided by +Cloud.

Performance of scientific computing platforms with MCNP4B

International Nuclear Information System (INIS)

McLaughlin, H.E.; Hendricks, J.S.

1998-01-01

Several computing platforms were evaluated with the MCNP4B Monte Carlo radiation transport code. The DEC AlphaStation 500/500 was the fastest to run MCNP4B. Compared to the HP 9000-735, the fastest platform 4 yr ago, the AlphaStation is 335% faster, the HP C180 is 133% faster, the SGI Origin 2000 is 82% faster, the Cray T94/4128 is 1% faster, the IBM RS/6000-590 is 93% as fast, the DEC 3000/600 is 81% as fast, the Sun Sparc20 is 57% as fast, the Cray YMP 8/8128 is 57% as fast, the sun Sparc5 is 33% as fast, and the Sun Sparc2 is 13% as fast. All results presented are reproducible and allow for comparison to computer platforms not included in this study. Timing studies are seen to be very problem dependent. The performance gains resulting from advances in software were also investigated. Various compilers and operating systems were seen to have a modest impact on performance, whereas hardware improvements have resulted in a factor of 4 improvement. MCNP4B also ran approximately as fast as MCNP4A

Homomorphic encryption experiments on IBM's cloud quantum computing platform

Science.gov (United States)

Huang, He-Liang; Zhao, You-Wei; Li, Tan; Li, Feng-Guang; Du, Yu-Tao; Fu, Xiang-Qun; Zhang, Shuo; Wang, Xiang; Bao, Wan-Su

2017-02-01

Quantum computing has undergone rapid development in recent years. Owing to limitations on scalability, personal quantum computers still seem slightly unrealistic in the near future. The first practical quantum computer for ordinary users is likely to be on the cloud. However, the adoption of cloud computing is possible only if security is ensured. Homomorphic encryption is a cryptographic protocol that allows computation to be performed on encrypted data without decrypting them, so it is well suited to cloud computing. Here, we first applied homomorphic encryption on IBM's cloud quantum computer platform. In our experiments, we successfully implemented a quantum algorithm for linear equations while protecting our privacy. This demonstration opens a feasible path to the next stage of development of cloud quantum information technology.

The design of an m-Health monitoring system based on a cloud computing platform

Science.gov (United States)

Xu, Boyi; Xu, Lida; Cai, Hongming; Jiang, Lihong; Luo, Yang; Gu, Yizhi

2017-01-01

Compared to traditional medical services provided within hospitals, m-Health monitoring systems (MHMSs) face more challenges in personalised health data processing. To achieve personalised and high-quality health monitoring by means of new technologies, such as mobile network and cloud computing, in this paper, a framework of an m-Health monitoring system based on a cloud computing platform (Cloud-MHMS) is designed to implement pervasive health monitoring. Furthermore, the modules of the framework, which are Cloud Storage and Multiple Tenants Access Control Layer, Healthcare Data Annotation Layer, and Healthcare Data Analysis Layer, are discussed. In the data storage layer, a multiple tenant access method is designed to protect patient privacy. In the data annotation layer, linked open data are adopted to augment health data interoperability semantically. In the data analysis layer, the process mining algorithm and similarity calculating method are implemented to support personalised treatment plan selection. These three modules cooperate to implement the core functions in the process of health monitoring, which are data storage, data processing, and data analysis. Finally, we study the application of our architecture in the monitoring of antimicrobial drug usage to demonstrate the usability of our method in personal healthcare analysis.

Atomdroid: a computational chemistry tool for mobile platforms.

Science.gov (United States)

Feldt, Jonas; Mata, Ricardo A; Dieterich, Johannes M

2012-04-23

We present the implementation of a new molecular mechanics program designed for use in mobile platforms, the first specifically built for these devices. The software is designed to run on Android operating systems and is compatible with several modern tablet-PCs and smartphones available in the market. It includes molecular viewer/builder capabilities with integrated routines for geometry optimizations and Monte Carlo simulations. These functionalities allow it to work as a stand-alone tool. We discuss some particular development aspects, as well as the overall feasibility of using computational chemistry software packages in mobile platforms. Benchmark calculations show that through efficient implementation techniques even hand-held devices can be used to simulate midsized systems using force fields.

A cloud computing based platform for sleep behavior and chronic diseases collaborative research.

Science.gov (United States)

Kuo, Mu-Hsing; Borycki, Elizabeth; Kushniruk, Andre; Huang, Yueh-Min; Hung, Shu-Hui

2014-01-01

The objective of this study is to propose a Cloud Computing based platform for sleep behavior and chronic disease collaborative research. The platform consists of two main components: (1) a sensing bed sheet with textile sensors to automatically record patient's sleep behaviors and vital signs, and (2) a service-oriented cloud computing architecture (SOCCA) that provides a data repository and allows for sharing and analysis of collected data. Also, we describe our systematic approach to implementing the SOCCA. We believe that the new cloud-based platform can provide nurse and other health professional researchers located in differing geographic locations with a cost effective, flexible, secure and privacy-preserved research environment.

Hierarchical approach to optimization of parallel matrix multiplication on large-scale platforms

KAUST Repository

Hasanov, Khalid

2014-03-04

© 2014, Springer Science+Business Media New York. Many state-of-the-art parallel algorithms, which are widely used in scientific applications executed on high-end computing systems, were designed in the twentieth century with relatively small-scale parallelism in mind. Indeed, while in 1990s a system with few hundred cores was considered a powerful supercomputer, modern top supercomputers have millions of cores. In this paper, we present a hierarchical approach to optimization of message-passing parallel algorithms for execution on large-scale distributed-memory systems. The idea is to reduce the communication cost by introducing hierarchy and hence more parallelism in the communication scheme. We apply this approach to SUMMA, the state-of-the-art parallel algorithm for matrix–matrix multiplication, and demonstrate both theoretically and experimentally that the modified Hierarchical SUMMA significantly improves the communication cost and the overall performance on large-scale platforms.

Open source acceleration of wave optics simulations on energy efficient high-performance computing platforms

Science.gov (United States)

Beck, Jeffrey; Bos, Jeremy P.

2017-05-01

We compare several modifications to the open-source wave optics package, WavePy, intended to improve execution time. Specifically, we compare the relative performance of the Intel MKL, a CPU based OpenCV distribution, and GPU-based version. Performance is compared between distributions both on the same compute platform and between a fully-featured computing workstation and the NVIDIA Jetson TX1 platform. Comparisons are drawn in terms of both execution time and power consumption. We have found that substituting the Fast Fourier Transform operation from OpenCV provides a marked improvement on all platforms. In addition, we show that embedded platforms offer some possibility for extensive improvement in terms of efficiency compared to a fully featured workstation.

Regional Platform on Personal Computer Electronic Waste in Latin ...

International Development Research Centre (IDRC) Digital Library (Canada)

Regional Platform on Personal Computer Electronic Waste in Latin America and the Caribbean. Donation of ... This project aims to identify environmentally responsible and sustainable solutions to the problem of e-waste. ... Policy in Focus publishes a special issue profiling evidence to empower women in the labour market.

A Web-based Distributed Voluntary Computing Platform for Large Scale Hydrological Computations

Science.gov (United States)

Demir, I.; Agliamzanov, R.

2014-12-01

Distributed volunteer computing can enable researchers and scientist to form large parallel computing environments to utilize the computing power of the millions of computers on the Internet, and use them towards running large scale environmental simulations and models to serve the common good of local communities and the world. Recent developments in web technologies and standards allow client-side scripting languages to run at speeds close to native application, and utilize the power of Graphics Processing Units (GPU). Using a client-side scripting language like JavaScript, we have developed an open distributed computing framework that makes it easy for researchers to write their own hydrologic models, and run them on volunteer computers. Users will easily enable their websites for visitors to volunteer sharing their computer resources to contribute running advanced hydrological models and simulations. Using a web-based system allows users to start volunteering their computational resources within seconds without installing any software. The framework distributes the model simulation to thousands of nodes in small spatial and computational sizes. A relational database system is utilized for managing data connections and queue management for the distributed computing nodes. In this paper, we present a web-based distributed volunteer computing platform to enable large scale hydrological simulations and model runs in an open and integrated environment.

A Security Monitoring Method Based on Autonomic Computing for the Cloud Platform

Directory of Open Access Journals (Sweden)

Jingjie Zhang

2018-01-01

Full Text Available With the continuous development of cloud computing, cloud security has become one of the most important issues in cloud computing. For example, data stored in the cloud platform may be attacked, and its security is difficult to be guaranteed. Therefore, we must attach weight to the issue of how to protect the data stored in the cloud. To protect data, data monitoring is a necessary process. Based on autonomic computing, we develop a cloud data monitoring system on the cloud platform, monitoring whether the data is abnormal in the cycle and analyzing the security of the data according to the monitored results. In this paper, the feasibility of the scheme can be verified through simulation. The results show that the proposed method can adapt to the dynamic change of cloud platform load, and it can also accurately evaluate the degree of abnormal data. Meanwhile, by adjusting monitoring frequency automatically, it improves the accuracy and timeliness of monitoring. Furthermore, it can reduce the monitoring cost of the system in normal operation process.

Cloud computing platform for real-time measurement and verification of energy performance

International Nuclear Information System (INIS)

Ke, Ming-Tsun; Yeh, Chia-Hung; Su, Cheng-Jie

2017-01-01

Highlights: • Application of PSO algorithm can improve the accuracy of the baseline model. • M&V cloud platform automatically calculates energy performance. • M&V cloud platform can be applied in all energy conservation measures. • Real-time operational performance can be monitored through the proposed platform. • M&V cloud platform facilitates the development of EE programs and ESCO industries. - Abstract: Nations worldwide are vigorously promoting policies to improve energy efficiency. The use of measurement and verification (M&V) procedures to quantify energy performance is an essential topic in this field. Currently, energy performance M&V is accomplished via a combination of short-term on-site measurements and engineering calculations. This requires extensive amounts of time and labor and can result in a discrepancy between actual energy savings and calculated results. In addition, the M&V period typically lasts for periods as long as several months or up to a year, the failure to immediately detect abnormal energy performance not only decreases energy performance, results in the inability to make timely correction, and misses the best opportunity to adjust or repair equipment and systems. In this study, a cloud computing platform for the real-time M&V of energy performance is developed. On this platform, particle swarm optimization and multivariate regression analysis are used to construct accurate baseline models. Instantaneous and automatic calculations of the energy performance and access to long-term, cumulative information about the energy performance are provided via a feature that allows direct uploads of the energy consumption data. Finally, the feasibility of this real-time M&V cloud platform is tested for a case study involving improvements to a cold storage system in a hypermarket. Cloud computing platform for real-time energy performance M&V is applicable to any industry and energy conservation measure. With the M&V cloud platform, real

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

Integrative set enrichment testing for multiple omics platforms

Directory of Open Access Journals (Sweden)

Poisson Laila M

2011-11-01

Full Text Available Abstract Background Enrichment testing assesses the overall evidence of differential expression behavior of the elements within a defined set. When we have measured many molecular aspects, e.g. gene expression, metabolites, proteins, it is desirable to assess their differential tendencies jointly across platforms using an integrated set enrichment test. In this work we explore the properties of several methods for performing a combined enrichment test using gene expression and metabolomics as the motivating platforms. Results Using two simulation models we explored the properties of several enrichment methods including two novel methods: the logistic regression 2-degree of freedom Wald test and the 2-dimensional permutation p-value for the sum-of-squared statistics test. In relation to their univariate counterparts we find that the joint tests can improve our ability to detect results that are marginal univariately. We also find that joint tests improve the ranking of associated pathways compared to their univariate counterparts. However, there is a risk of Type I error inflation with some methods and self-contained methods lose specificity when the sets are not representative of underlying association. Conclusions In this work we show that consideration of data from multiple platforms, in conjunction with summarization via a priori pathway information, leads to increased power in detection of genomic associations with phenotypes.

Analytical simulation platform describing projections in computed tomography systems

International Nuclear Information System (INIS)

Youn, Hanbean; Kim, Ho Kyung

2013-01-01

To reduce the patient dose, several approaches such as spectral imaging using photon counting detectors and statistical image reconstruction, are being considered. Although image-reconstruction algorithms may significantly enhance image quality in reconstructed images with low dose, true signal-to-noise properties are mainly determined by image quality in projections. We are developing an analytical simulation platform describing projections to investigate how quantum-interaction physics in each component configuring CT systems affect image quality in projections. This simulator will be very useful for an improved design or optimization of CT systems in economy as well as the development of novel image-reconstruction algorithms. In this study, we present the progress of development of the simulation platform with an emphasis on the theoretical framework describing the generation of projection data. We have prepared the analytical simulation platform describing projections in computed tomography systems. The remained further study before the meeting includes the following: Each stage in the cascaded signal-transfer model for obtaining projections will be validated by the Monte Carlo simulations. We will build up energy-dependent scatter and pixel-crosstalk kernels, and show their effects on image quality in projections and reconstructed images. We will investigate the effects of projections obtained from various imaging conditions and system (or detector) operation parameters on reconstructed images. It is challenging to include the interaction physics due to photon-counting detectors into the simulation platform. Detailed descriptions of the simulator will be presented with discussions on its performance and limitation as well as Monte Carlo validations. Computational cost will also be addressed in detail. The proposed method in this study is simple and can be used conveniently in lab environment

Ex Machina: Analytical platforms, Law and the Challenges of Computational Legal Science

Directory of Open Access Journals (Sweden)

Nicola Lettieri

2018-04-01

Full Text Available Over the years, computation has become a fundamental part of the scientific practice in several research fields that goes far beyond the boundaries of natural sciences. Data mining, machine learning, simulations and other computational methods lie today at the hearth of the scientific endeavour in a growing number of social research areas from anthropology to economics. In this scenario, an increasingly important role is played by analytical platforms: integrated environments allowing researchers to experiment cutting-edge data-driven and computation-intensive analyses. The paper discusses the appearance of such tools in the emerging field of computational legal science. After a general introduction to the impact of computational methods on both natural and social sciences, we describe the concept and the features of an analytical platform exploring innovative cross-methodological approaches to the academic and investigative study of crime. Stemming from an ongoing project involving researchers from law, computer science and bioinformatics, the initiative is presented and discussed as an opportunity to raise a debate about the future of legal scholarship and, inside of it, about the challenges of computational legal science.

MRMer, an interactive open source and cross-platform system for data extraction and visualization of multiple reaction monitoring experiments.

Science.gov (United States)

Martin, Daniel B; Holzman, Ted; May, Damon; Peterson, Amelia; Eastham, Ashley; Eng, Jimmy; McIntosh, Martin

2008-11-01

Multiple reaction monitoring (MRM) mass spectrometry identifies and quantifies specific peptides in a complex mixture with very high sensitivity and speed and thus has promise for the high throughput screening of clinical samples for candidate biomarkers. We have developed an interactive software platform, called MRMer, for managing highly complex MRM-MS experiments, including quantitative analyses using heavy/light isotopic peptide pairs. MRMer parses and extracts information from MS files encoded in the platform-independent mzXML data format. It extracts and infers precursor-product ion transition pairings, computes integrated ion intensities, and permits rapid visual curation for analyses exceeding 1000 precursor-product pairs. Results can be easily output for quantitative comparison of consecutive runs. Additionally MRMer incorporates features that permit the quantitative analysis experiments including heavy and light isotopic peptide pairs. MRMer is open source and provided under the Apache 2.0 license.

My4Sight: A Human Computation Platform for Improving Flu Predictions

OpenAIRE

Akupatni, Vivek Bharath

2015-01-01

While many human computation (human-in-the-loop) systems exist in the field of Artificial Intelligence (AI) to solve problems that can't be solved by computers alone, comparatively fewer platforms exist for collecting human knowledge, and evaluation of various techniques for harnessing human insights in improving forecasting models for infectious diseases, such as Influenza and Ebola. In this thesis, we present the design and implementation of My4Sight, a human computation system develope...

Unified, Cross-Platform, Open-Source Library Package for High-Performance Computing

Energy Technology Data Exchange (ETDEWEB)

Kozacik, Stephen [EM Photonics, Inc., Newark, DE (United States)

2017-05-15

Compute power is continually increasing, but this increased performance is largely found in sophisticated computing devices and supercomputer resources that are difficult to use, resulting in under-utilization. We developed a unified set of programming tools that will allow users to take full advantage of the new technology by allowing them to work at a level abstracted away from the platform specifics, encouraging the use of modern computing systems, including government-funded supercomputer facilities.

Cloud Computing as Evolution of Distributed Computing – A Case Study for SlapOS Distributed Cloud Computing Platform

Directory of Open Access Journals (Sweden)

George SUCIU

2013-01-01

Full Text Available The cloud computing paradigm has been defined from several points of view, the main two directions being either as an evolution of the grid and distributed computing paradigm, or, on the contrary, as a disruptive revolution in the classical paradigms of operating systems, network layers and web applications. This paper presents a distributed cloud computing platform called SlapOS, which unifies technologies and communication protocols into a new technology model for offering any application as a service. Both cloud and distributed computing can be efficient methods for optimizing resources that are aggregated from a grid of standard PCs hosted in homes, offices and small data centers. The paper fills a gap in the existing distributed computing literature by providing a distributed cloud computing model which can be applied for deploying various applications.

UrbanWeb: a Platform for Mobile Context-aware Social Computing

DEFF Research Database (Denmark)

Hansen, Frank Allan; Grønbæk, Kaj

2010-01-01

UrbanWeb is a novel Web-based context-aware hypermedia plat- form. It provides essential mechanisms for mobile social comput- ing applications: the framework implements context as an exten- sion to Web 2.0 tagging and provides developers with an easy to use platform for mobile context......-aware applications. Services can be statically or dynamically defined in the user’s context, data can be pre-cached for data intensive mobile applications, and shared state supports synchronization between running applications such as games. The paper discusses how UrbanWeb acquires cues about the user’s context...... from sensors in mobile phones, ranging from GPS data, to 2D barcodes, and manual entry of context in- formation, as well as how to utilize this context in applications. The experiences show that the UrbanWeb platform efficiently supports a rich variety of urban computing applications in differ- ent...

Single-Chip Multiple-Frequency RF MEMS Resonant Platform for Wireless Communications, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — A novel, single-chip, multiple-frequency platform for RF/IF filtering and clock reference based on contour-mode aluminum nitride (AlN) MEMS piezoelectric resonators...

CPSS: a computational platform for the analysis of small RNA deep sequencing data.

Science.gov (United States)

Zhang, Yuanwei; Xu, Bo; Yang, Yifan; Ban, Rongjun; Zhang, Huan; Jiang, Xiaohua; Cooke, Howard J; Xue, Yu; Shi, Qinghua

2012-07-15

Next generation sequencing (NGS) techniques have been widely used to document the small ribonucleic acids (RNAs) implicated in a variety of biological, physiological and pathological processes. An integrated computational tool is needed for handling and analysing the enormous datasets from small RNA deep sequencing approach. Herein, we present a novel web server, CPSS (a computational platform for the analysis of small RNA deep sequencing data), designed to completely annotate and functionally analyse microRNAs (miRNAs) from NGS data on one platform with a single data submission. Small RNA NGS data can be submitted to this server with analysis results being returned in two parts: (i) annotation analysis, which provides the most comprehensive analysis for small RNA transcriptome, including length distribution and genome mapping of sequencing reads, small RNA quantification, prediction of novel miRNAs, identification of differentially expressed miRNAs, piwi-interacting RNAs and other non-coding small RNAs between paired samples and detection of miRNA editing and modifications and (ii) functional analysis, including prediction of miRNA targeted genes by multiple tools, enrichment of gene ontology terms, signalling pathway involvement and protein-protein interaction analysis for the predicted genes. CPSS, a ready-to-use web server that integrates most functions of currently available bioinformatics tools, provides all the information wanted by the majority of users from small RNA deep sequencing datasets. CPSS is implemented in PHP/PERL+MySQL+R and can be freely accessed at http://mcg.ustc.edu.cn/db/cpss/index.html or http://mcg.ustc.edu.cn/sdap1/cpss/index.html.

An Application Development Platform for Neuromorphic Computing

Energy Technology Data Exchange (ETDEWEB)

Dean, Mark [University of Tennessee (UT); Chan, Jason [University of Tennessee (UT); Daffron, Christopher [University of Tennessee (UT); Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT); Rose, Garrett [University of Tennessee (UT); Plank, James [University of Tennessee (UT); Birdwell, John Douglas [University of Tennessee (UT); Schuman, Catherine D [ORNL

2016-01-01

Dynamic Adaptive Neural Network Arrays (DANNAs) are neuromorphic computing systems developed as a hardware based approach to the implementation of neural networks. They feature highly adaptive and programmable structural elements, which model arti cial neural networks with spiking behavior. We design them to solve problems using evolutionary optimization. In this paper, we highlight the current hardware and software implementations of DANNA, including their features, functionalities and performance. We then describe the development of an Application Development Platform (ADP) to support efficient application implementation and testing of DANNA based solutions. We conclude with future directions.

Smart SOA platforms in cloud computing architectures

CERN Document Server

Exposito , Ernesto

2014-01-01

This book is intended to introduce the principles of the Event-Driven and Service-Oriented Architecture (SOA 2.0) and its role in the new interconnected world based on the cloud computing architecture paradigm. In this new context, the concept of "service" is widely applied to the hardware and software resources available in the new generation of the Internet. The authors focus on how current and future SOA technologies provide the basis for the smart management of the service model provided by the Platform as a Service (PaaS) layer.

Processing-Efficient Distributed Adaptive RLS Filtering for Computationally Constrained Platforms

Directory of Open Access Journals (Sweden)

Noor M. Khan

2017-01-01

Full Text Available In this paper, a novel processing-efficient architecture of a group of inexpensive and computationally incapable small platforms is proposed for a parallely distributed adaptive signal processing (PDASP operation. The proposed architecture runs computationally expensive procedures like complex adaptive recursive least square (RLS algorithm cooperatively. The proposed PDASP architecture operates properly even if perfect time alignment among the participating platforms is not available. An RLS algorithm with the application of MIMO channel estimation is deployed on the proposed architecture. Complexity and processing time of the PDASP scheme with MIMO RLS algorithm are compared with sequentially operated MIMO RLS algorithm and liner Kalman filter. It is observed that PDASP scheme exhibits much lesser computational complexity parallely than the sequential MIMO RLS algorithm as well as Kalman filter. Moreover, the proposed architecture provides an improvement of 95.83% and 82.29% decreased processing time parallely compared to the sequentially operated Kalman filter and MIMO RLS algorithm for low doppler rate, respectively. Likewise, for high doppler rate, the proposed architecture entails an improvement of 94.12% and 77.28% decreased processing time compared to the Kalman and RLS algorithms, respectively.

H-Shaped Multiple Linear Motor Drive Platform Control System Design Based on an Inverse System Method

NARCIS (Netherlands)

Qin, Caiyan; Zhang, Chaoning; Lu, H.

2017-01-01

Due to its simple mechanical structure and high motion stability, the H-shaped platform has been increasingly widely used in precision measuring, numerical control machining and semiconductor packaging equipment, etc. The H-shaped platform is normally driven by multiple (three) permanent magnet

Fundamentals of power integrity for computer platforms and systems

CERN Document Server

DiBene, Joseph T

2014-01-01

An all-encompassing text that focuses on the fundamentals of power integrity Power integrity is the study of power distribution from the source to the load and the system level issues that can occur across it. For computer systems, these issues can range from inside the silicon to across the board and may egress into other parts of the platform, including thermal, EMI, and mechanical. With a focus on computer systems and silicon level power delivery, this book sheds light on the fundamentals of power integrity, utilizing the author's extensive background in the power integrity industry and un

Computational Platform About Amazon Web Services (Aws Distributed Rendering

Directory of Open Access Journals (Sweden)

Gabriel Rojas-Albarracín

2017-09-01

Full Text Available Today has created a dynamic in which people require higher image quality in different media formats (games, movies, animations. Further definition usually requires image processing larger; this brings the need for increased computing power. This paper presents a case study in which the implementation of a low-cost platform on the Amazon cloud for parallel processing of images and animation.

Secure Multiparty Quantum Computation for Summation and Multiplication.

Science.gov (United States)

Shi, Run-hua; Mu, Yi; Zhong, Hong; Cui, Jie; Zhang, Shun

2016-01-21

As a fundamental primitive, Secure Multiparty Summation and Multiplication can be used to build complex secure protocols for other multiparty computations, specially, numerical computations. However, there is still lack of systematical and efficient quantum methods to compute Secure Multiparty Summation and Multiplication. In this paper, we present a novel and efficient quantum approach to securely compute the summation and multiplication of multiparty private inputs, respectively. Compared to classical solutions, our proposed approach can ensure the unconditional security and the perfect privacy protection based on the physical principle of quantum mechanics.

The potential benefits of photonics in the computing platform

Science.gov (United States)

Bautista, Jerry

2005-03-01

The increase in computational requirements for real-time image processing, complex computational fluid dynamics, very large scale data mining in the health industry/Internet, and predictive models for financial markets are driving computer architects to consider new paradigms that rely upon very high speed interconnects within and between computing elements. Further challenges result from reduced power requirements, reduced transmission latency, and greater interconnect density. Optical interconnects may solve many of these problems with the added benefit extended reach. In addition, photonic interconnects provide relative EMI immunity which is becoming an increasing issue with a greater dependence on wireless connectivity. However, to be truly functional, the optical interconnect mesh should be able to support arbitration, addressing, etc. completely in the optical domain with a BER that is more stringent than "traditional" communication requirements. Outlined are challenges in the advanced computing environment, some possible optical architectures and relevant platform technologies, as well roughly sizing these opportunities which are quite large relative to the more "traditional" optical markets.

An Interactive Platform to Visualize Data-Driven Clinical Pathways for the Management of Multiple Chronic Conditions.

Science.gov (United States)

Zhang, Yiye; Padman, Rema

2017-01-01

Patients with multiple chronic conditions (MCC) pose an increasingly complex health management challenge worldwide, particularly due to the significant gap in our understanding of how to provide coordinated care. Drawing on our prior research on learning data-driven clinical pathways from actual practice data, this paper describes a prototype, interactive platform for visualizing the pathways of MCC to support shared decision making. Created using Python web framework, JavaScript library and our clinical pathway learning algorithm, the visualization platform allows clinicians and patients to learn the dominant patterns of co-progression of multiple clinical events from their own data, and interactively explore and interpret the pathways. We demonstrate functionalities of the platform using a cluster of 36 patients, identified from a dataset of 1,084 patients, who are diagnosed with at least chronic kidney disease, hypertension, and diabetes. Future evaluation studies will explore the use of this platform to better understand and manage MCC.

H-Shaped Multiple Linear Motor Drive Platform Control System Design Based on an Inverse System Method

Directory of Open Access Journals (Sweden)

Caiyan Qin

2017-12-01

Full Text Available Due to its simple mechanical structure and high motion stability, the H-shaped platform has been increasingly widely used in precision measuring, numerical control machining and semiconductor packaging equipment, etc. The H-shaped platform is normally driven by multiple (three permanent magnet synchronous linear motors. The main challenges for H-shaped platform-control include synchronous control between the two linear motors in the Y direction as well as total positioning error of the platform mover, a combination of position deviation in X and Y directions. To deal with the above challenges, this paper proposes a control strategy based on the inverse system method through state feedback and dynamic decoupling of the thrust force. First, mechanical dynamics equations have been deduced through the analysis of system coupling based on the platform structure. Second, the mathematical model of the linear motors and the relevant coordinate transformation between dq-axis currents and ABC-phase currents are analyzed. Third, after the main concept of inverse system method being explained, the inverse system model of the platform control system has been designed after defining relevant system variables. Inverse system model compensates the original nonlinear coupled system into pseudo-linear decoupled linear system, for which typical linear control methods, like PID, can be adopted to control the system. The simulation model of the control system is built in MATLAB/Simulink and the simulation result shows that the designed control system has both small synchronous deviation and small total trajectory tracking error. Furthermore, the control program has been run on NI controller for both fixed-loop-time and free-loop-time modes, and the test result shows that the average loop computation time needed is rather small, which makes it suitable for real industrial applications. Overall, it proves that the proposed new control strategy can be used in

The COMET Sleep Research Platform.

Science.gov (United States)

Nichols, Deborah A; DeSalvo, Steven; Miller, Richard A; Jónsson, Darrell; Griffin, Kara S; Hyde, Pamela R; Walsh, James K; Kushida, Clete A

2014-01-01

The Comparative Outcomes Management with Electronic Data Technology (COMET) platform is extensible and designed for facilitating multicenter electronic clinical research. Our research goals were the following: (1) to conduct a comparative effectiveness trial (CET) for two obstructive sleep apnea treatments-positive airway pressure versus oral appliance therapy; and (2) to establish a new electronic network infrastructure that would support this study and other clinical research studies. The COMET platform was created to satisfy the needs of CET with a focus on creating a platform that provides comprehensive toolsets, multisite collaboration, and end-to-end data management. The platform also provides medical researchers the ability to visualize and interpret data using business intelligence (BI) tools. COMET is a research platform that is scalable and extensible, and which, in a future version, can accommodate big data sets and enable efficient and effective research across multiple studies and medical specialties. The COMET platform components were designed for an eventual move to a cloud computing infrastructure that enhances sustainability, overall cost effectiveness, and return on investment.

Computer-operated analytical platform for the determination of nutrients in hydroponic systems.

Science.gov (United States)

Rius-Ruiz, F Xavier; Andrade, Francisco J; Riu, Jordi; Rius, F Xavier

2014-03-15

Hydroponics is a water, energy, space, and cost efficient system for growing plants in constrained spaces or land exhausted areas. Precise control of hydroponic nutrients is essential for growing healthy plants and producing high yields. In this article we report for the first time on a new computer-operated analytical platform which can be readily used for the determination of essential nutrients in hydroponic growing systems. The liquid-handling system uses inexpensive components (i.e., peristaltic pump and solenoid valves), which are discretely computer-operated to automatically condition, calibrate and clean a multi-probe of solid-contact ion-selective electrodes (ISEs). These ISEs, which are based on carbon nanotubes, offer high portability, robustness and easy maintenance and storage. With this new computer-operated analytical platform we performed automatic measurements of K(+), Ca(2+), NO3(-) and Cl(-) during tomato plants growth in order to assure optimal nutritional uptake and tomato production. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Perseus computational platform for comprehensive analysis of (prote)omics data.

Science.gov (United States)

Tyanova, Stefka; Temu, Tikira; Sinitcyn, Pavel; Carlson, Arthur; Hein, Marco Y; Geiger, Tamar; Mann, Matthias; Cox, Jürgen

2016-09-01

A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.

Arc4nix: A cross-platform geospatial analytical library for cluster and cloud computing

Science.gov (United States)

Tang, Jingyin; Matyas, Corene J.

2018-02-01

Big Data in geospatial technology is a grand challenge for processing capacity. The ability to use a GIS for geospatial analysis on Cloud Computing and High Performance Computing (HPC) clusters has emerged as a new approach to provide feasible solutions. However, users lack the ability to migrate existing research tools to a Cloud Computing or HPC-based environment because of the incompatibility of the market-dominating ArcGIS software stack and Linux operating system. This manuscript details a cross-platform geospatial library "arc4nix" to bridge this gap. Arc4nix provides an application programming interface compatible with ArcGIS and its Python library "arcpy". Arc4nix uses a decoupled client-server architecture that permits geospatial analytical functions to run on the remote server and other functions to run on the native Python environment. It uses functional programming and meta-programming language to dynamically construct Python codes containing actual geospatial calculations, send them to a server and retrieve results. Arc4nix allows users to employ their arcpy-based script in a Cloud Computing and HPC environment with minimal or no modification. It also supports parallelizing tasks using multiple CPU cores and nodes for large-scale analyses. A case study of geospatial processing of a numerical weather model's output shows that arcpy scales linearly in a distributed environment. Arc4nix is open-source software.

Reconfigurable microfluidic platform in ice

OpenAIRE

Varejka, M.

2008-01-01

Microfluidic devices are popular tools in the biotechnology industry where they provide smaller reagent requirements, high speed of analysis and the possibility for automation. The aim of the project is to make a flexible biocompatible microfluidic platform adapted to different specific applications, mainly analytical and separations which parameters and configuration can be changed multiple times by changing corresponding computer programme. The current project has been sup...

The development of a computational platform to design and simulate on-board hydrogen storage systems

DEFF Research Database (Denmark)

Mazzucco, Andrea; Rokni, Masoud

2017-01-01

A computational platform is developed in the Modelica® language within the Dymola™ environment to provide a tool for the design and performance comparison of on-board hydrogen storage systems. The platform has been coupled with an open source library for hydrogen fueling stations to investigate...... the vehicular tank within the frame of a complete refueling system. The two technologies that are integrated in the platform are solid-state hydrogen storage in the form of metal hydrides and compressed gas systems. In this work the computational platform is used to compare the storage performance of two tank...... to a storage capacity four times larger than a tube-in-tube solution of the same size. The volumetric and gravimetric densities of the shell and tube are 2.46% and 1.25% respectively. The dehydriding ability of this solution is proven to withstand intense discharging conditions....

An Application-Based Performance Evaluation of NASAs Nebula Cloud Computing Platform

Science.gov (United States)

Saini, Subhash; Heistand, Steve; Jin, Haoqiang; Chang, Johnny; Hood, Robert T.; Mehrotra, Piyush; Biswas, Rupak

2012-01-01

The high performance computing (HPC) community has shown tremendous interest in exploring cloud computing as it promises high potential. In this paper, we examine the feasibility, performance, and scalability of production quality scientific and engineering applications of interest to NASA on NASA's cloud computing platform, called Nebula, hosted at Ames Research Center. This work represents the comprehensive evaluation of Nebula using NUTTCP, HPCC, NPB, I/O, and MPI function benchmarks as well as four applications representative of the NASA HPC workload. Specifically, we compare Nebula performance on some of these benchmarks and applications to that of NASA s Pleiades supercomputer, a traditional HPC system. We also investigate the impact of virtIO and jumbo frames on interconnect performance. Overall results indicate that on Nebula (i) virtIO and jumbo frames improve network bandwidth by a factor of 5x, (ii) there is a significant virtualization layer overhead of about 10% to 25%, (iii) write performance is lower by a factor of 25x, (iv) latency for short MPI messages is very high, and (v) overall performance is 15% to 48% lower than that on Pleiades for NASA HPC applications. We also comment on the usability of the cloud platform.

Reconfiguration in FPGA-Based Multi-Core Platforms for Hard Real-Time Applications

DEFF Research Database (Denmark)

Pezzarossa, Luca; Schoeberl, Martin; Sparsø, Jens

2016-01-01

-case execution-time of tasks of an application that determines the systems ability to respond in time. To support this focus, the platform must provide service guarantees for both communication and computation resources. In addition, many hard real-time applications have multiple modes of operation, and each......In general-purpose computing multi-core platforms, hardware accelerators and reconfiguration are means to improve performance; i.e., the average-case execution time of a software application. In hard real-time systems, such average-case speed-up is not in itself relevant - it is the worst...... mode has specific requirements. An interesting perspective on reconfigurable computing is to exploit run-time reconfiguration to support mode changes. In this paper we explore approaches to reconfiguration of communication and computation resources in the T-CREST hard real-time multi-core platform...

Design of e-Science platform for biomedical imaging research cross multiple academic institutions and hospitals

Science.gov (United States)

Zhang, Jianguo; Zhang, Kai; Yang, Yuanyuan; Ling, Tonghui; Wang, Tusheng; Wang, Mingqing; Hu, Haibo; Xu, Xuemin

2012-02-01

More and more image informatics researchers and engineers are considering to re-construct imaging and informatics infrastructure or to build new framework to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment. In this presentation, we show an outline and our preliminary design work of building an e-Science platform for biomedical imaging and informatics research and application in Shanghai. We will present our consideration and strategy on designing this platform, and preliminary results. We also will discuss some challenges and solutions in building this platform.

Development of a Very Dense Liquid Cooled Compute Platform

Energy Technology Data Exchange (ETDEWEB)

Hughes, Phillip N.; Lipp, Robert J.

2013-12-10

The objective of this project was to design and develop a prototype very energy efficient high density compute platform with 100% pumped refrigerant liquid cooling using commodity components and high volume manufacturing techniques. Testing at SLAC has indicated that we achieved a DCIE of 0.93 against our original goal of 0.85. This number includes both cooling and power supply and was achieved employing some of the highest wattage processors available.

Micropillar arrays as a high-throughput screening platform for therapeutics in multiple sclerosis.

Science.gov (United States)

Mei, Feng; Fancy, Stephen P J; Shen, Yun-An A; Niu, Jianqin; Zhao, Chao; Presley, Bryan; Miao, Edna; Lee, Seonok; Mayoral, Sonia R; Redmond, Stephanie A; Etxeberria, Ainhoa; Xiao, Lan; Franklin, Robin J M; Green, Ari; Hauser, Stephen L; Chan, Jonah R

2014-08-01

Functional screening for compounds that promote remyelination represents a major hurdle in the development of rational therapeutics for multiple sclerosis. Screening for remyelination is problematic, as myelination requires the presence of axons. Standard methods do not resolve cell-autonomous effects and are not suited for high-throughput formats. Here we describe a binary indicant for myelination using micropillar arrays (BIMA). Engineered with conical dimensions, micropillars permit resolution of the extent and length of membrane wrapping from a single two-dimensional image. Confocal imaging acquired from the base to the tip of the pillars allows for detection of concentric wrapping observed as 'rings' of myelin. The platform is formatted in 96-well plates, amenable to semiautomated random acquisition and automated detection and quantification. Upon screening 1,000 bioactive molecules, we identified a cluster of antimuscarinic compounds that enhance oligodendrocyte differentiation and remyelination. Our findings demonstrate a new high-throughput screening platform for potential regenerative therapeutics in multiple sclerosis.

Overview of Parallel Platforms for Common High Performance Computing

Directory of Open Access Journals (Sweden)

T. Fryza

2012-04-01

Full Text Available The paper deals with various parallel platforms used for high performance computing in the signal processing domain. More precisely, the methods exploiting the multicores central processing units such as message passing interface and OpenMP are taken into account. The properties of the programming methods are experimentally proved in the application of a fast Fourier transform and a discrete cosine transform and they are compared with the possibilities of MATLAB's built-in functions and Texas Instruments digital signal processors with very long instruction word architectures. New FFT and DCT implementations were proposed and tested. The implementation phase was compared with CPU based computing methods and with possibilities of the Texas Instruments digital signal processing library on C6747 floating-point DSPs. The optimal combination of computing methods in the signal processing domain and new, fast routines' implementation is proposed as well.

Optimization of sparse matrix-vector multiplication on emerging multicore platforms

Energy Technology Data Exchange (ETDEWEB)

Williams, Samuel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Vuduc, Richard [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Shalf, John [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Yelick, Katherine [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); Demmel, James [Univ. of California, Berkeley, CA (United States)

2007-01-01

We are witnessing a dramatic change in computer architecture due to the multicore paradigm shift, as every electronic device from cell phones to supercomputers confronts parallelism of unprecedented scale. To fully unleash the potential of these systems, the HPC community must develop multicore specific optimization methodologies for important scientific computations. In this work, we examine sparse matrix-vector multiply (SpMV) - one of the most heavily used kernels in scientific computing - across a broad spectrum of multicore designs. Our experimental platform includes the homogeneous AMD dual-core and Intel quad-core designs, the heterogeneous STI Cell, as well as the first scientific study of the highly multithreaded Sun Niagara2. We present several optimization strategies especially effective for the multicore environment, and demonstrate significant performance improvements compared to existing state-of-the-art serial and parallel SpMV implementations. Additionally, we present key insights into the architectural tradeoffs of leading multicore design strategies, in the context of demanding memory-bound numerical algorithms.

Artificial and Computational Intelligence for Games on Mobile Platforms

OpenAIRE

Congdon, Clare Bates; Hingston, Philip; Kendall, Graham

2013-01-01

In this chapter, we consider the possibilities of creating new and innovative games that are targeted for mobile devices, such as smart phones and tablets, and that showcase AI (Artificial Intelligence) and CI (Computational Intelligence) approaches. Such games might take advantage of the sensors and facilities that are not available on other platforms, or might simply rely on the "app culture" to facilitate getting the games into users' hands. While these games might be profitable in themsel...

SoC-Based Edge Computing Gateway in the Context of the Internet of Multimedia Things: Experimental Platform

Directory of Open Access Journals (Sweden)

Maher Jridi

2018-01-01

Full Text Available This paper presents an algorithm/architecture and Hardware/Software co-designs for implementing a digital edge computing layer on a Zynq platform in the context of the Internet of Multimedia Things (IoMT. Traditional cloud computing is no longer suitable for applications that require image processing due to cloud latency and privacy concerns. With edge computing, data are processed, analyzed, and encrypted very close to the device, which enable the ability to secure data and act rapidly on connected things. The proposed edge computing system is composed of a reconfigurable module to simultaneously compress and encrypt multiple images, along with wireless image transmission and display functionalities. A lightweight implementation of the proposed design is obtained by approximate computing of the discrete cosine transform (DCT and by using a simple chaotic generator which greatly enhances the encryption efficiency. The deployed solution includes four configurations based on HW/SW partitioning in order to handle the compromise between execution time, area, and energy consumption. It was found with the experimental setup that by moving more components to hardware execution, a timing speedup of more than nine times could be achieved with a negligible amount of energy consumption. The power efficiency was then enhanced by a ratio of 7.7 times.

A Dedicated Computational Platform for Cellular Monte Carlo T-CAD Software Tools

Science.gov (United States)

2015-07-14

computer that establishes an encrypted Virtual Private Network ( OpenVPN [44]) based on the Secure Socket Layer (SSL) paradigm. Each user is given a...security certificate for each device used to connect to the computing nodes. Stable OpenVPN clients are available for Linux, Microsoft Windows, Apple OSX...platform is granted by an encrypted connection base on the Secure Socket Layer (SSL) protocol, and implemented in the OpenVPN Virtual Personal Network

Digital imaging of root traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics.

Science.gov (United States)

Das, Abhiram; Schneider, Hannah; Burridge, James; Ascanio, Ana Karine Martinez; Wojciechowski, Tobias; Topp, Christopher N; Lynch, Jonathan P; Weitz, Joshua S; Bucksch, Alexander

2015-01-01

Plant root systems are key drivers of plant function and yield. They are also under-explored targets to meet global food and energy demands. Many new technologies have been developed to characterize crop root system architecture (CRSA). These technologies have the potential to accelerate the progress in understanding the genetic control and environmental response of CRSA. Putting this potential into practice requires new methods and algorithms to analyze CRSA in digital images. Most prior approaches have solely focused on the estimation of root traits from images, yet no integrated platform exists that allows easy and intuitive access to trait extraction and analysis methods from images combined with storage solutions linked to metadata. Automated high-throughput phenotyping methods are increasingly used in laboratory-based efforts to link plant genotype with phenotype, whereas similar field-based studies remain predominantly manual low-throughput. Here, we present an open-source phenomics platform "DIRT", as a means to integrate scalable supercomputing architectures into field experiments and analysis pipelines. DIRT is an online platform that enables researchers to store images of plant roots, measure dicot and monocot root traits under field conditions, and share data and results within collaborative teams and the broader community. The DIRT platform seamlessly connects end-users with large-scale compute "commons" enabling the estimation and analysis of root phenotypes from field experiments of unprecedented size. DIRT is an automated high-throughput computing and collaboration platform for field based crop root phenomics. The platform is accessible at http://www.dirt.iplantcollaborative.org/ and hosted on the iPlant cyber-infrastructure using high-throughput grid computing resources of the Texas Advanced Computing Center (TACC). DIRT is a high volume central depository and high-throughput RSA trait computation platform for plant scientists working on crop roots

[The Key Technology Study on Cloud Computing Platform for ECG Monitoring Based on Regional Internet of Things].

Science.gov (United States)

Yang, Shu; Qiu, Yuyan; Shi, Bo

2016-09-01

This paper explores the methods of building the internet of things of a regional ECG monitoring, focused on the implementation of ECG monitoring center based on cloud computing platform. It analyzes implementation principles of automatic identifi cation in the types of arrhythmia. It also studies the system architecture and key techniques of cloud computing platform, including server load balancing technology, reliable storage of massive smalfi les and the implications of quick search function.

MACBenAbim: A Multi-platform Mobile Application for searching keyterms in Computational Biology and Bioinformatics.

Science.gov (United States)

Oluwagbemi, Olugbenga O; Adewumi, Adewole; Esuruoso, Abimbola

2012-01-01

Computational biology and bioinformatics are gradually gaining grounds in Africa and other developing nations of the world. However, in these countries, some of the challenges of computational biology and bioinformatics education are inadequate infrastructures, and lack of readily-available complementary and motivational tools to support learning as well as research. This has lowered the morale of many promising undergraduates, postgraduates and researchers from aspiring to undertake future study in these fields. In this paper, we developed and described MACBenAbim (Multi-platform Mobile Application for Computational Biology and Bioinformatics), a flexible user-friendly tool to search for, define and describe the meanings of keyterms in computational biology and bioinformatics, thus expanding the frontiers of knowledge of the users. This tool also has the capability of achieving visualization of results on a mobile multi-platform context. MACBenAbim is available from the authors for non-commercial purposes.

ClusterCAD: a computational platform for type I modular polyketide synthase design

DEFF Research Database (Denmark)

Eng, Clara H.; Backman, Tyler W. H.; Bailey, Constance B.

2018-01-01

barrier to the design of active variants, and identifying strategies to reliably construct functional PKS chimeras remains an active area of research. In this work, we formalize a paradigm for the design of PKS chimeras and introduce ClusterCAD as a computational platform to streamline and simplify...

e-Science platform for translational biomedical imaging research: running, statistics, and analysis

Science.gov (United States)

Wang, Tusheng; Yang, Yuanyuan; Zhang, Kai; Wang, Mingqing; Zhao, Jun; Xu, Lisa; Zhang, Jianguo

2015-03-01

In order to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment, we had designed an e-Science platform for biomedical imaging research and application cross multiple academic institutions and hospitals in Shanghai and presented this work in SPIE Medical Imaging conference held in San Diego in 2012. In past the two-years, we implemented a biomedical image chain including communication, storage, cooperation and computing based on this e-Science platform. In this presentation, we presented the operating status of this system in supporting biomedical imaging research, analyzed and discussed results of this system in supporting multi-disciplines collaboration cross-multiple institutions.

Optimization of Sparse Matrix-Vector Multiplication on Emerging Multicore Platforms

Energy Technology Data Exchange (ETDEWEB)

Williams, Samuel; Oliker, Leonid; Vuduc, Richard; Shalf, John; Yelick, Katherine; Demmel, James

2008-10-16

We are witnessing a dramatic change in computer architecture due to the multicore paradigm shift, as every electronic device from cell phones to supercomputers confronts parallelism of unprecedented scale. To fully unleash the potential of these systems, the HPC community must develop multicore specific-optimization methodologies for important scientific computations. In this work, we examine sparse matrix-vector multiply (SpMV) - one of the most heavily used kernels in scientific computing - across a broad spectrum of multicore designs. Our experimental platform includes the homogeneous AMD quad-core, AMD dual-core, and Intel quad-core designs, the heterogeneous STI Cell, as well as one of the first scientific studies of the highly multithreaded Sun Victoria Falls (a Niagara2 SMP). We present several optimization strategies especially effective for the multicore environment, and demonstrate significant performance improvements compared to existing state-of-the-art serial and parallel SpMV implementations. Additionally, we present key insights into the architectural trade-offs of leading multicore design strategies, in the context of demanding memory-bound numerical algorithms.

Cpu/gpu Computing for AN Implicit Multi-Block Compressible Navier-Stokes Solver on Heterogeneous Platform

Science.gov (United States)

Deng, Liang; Bai, Hanli; Wang, Fang; Xu, Qingxin

2016-06-01

CPU/GPU computing allows scientists to tremendously accelerate their numerical codes. In this paper, we port and optimize a double precision alternating direction implicit (ADI) solver for three-dimensional compressible Navier-Stokes equations from our in-house Computational Fluid Dynamics (CFD) software on heterogeneous platform. First, we implement a full GPU version of the ADI solver to remove a lot of redundant data transfers between CPU and GPU, and then design two fine-grain schemes, namely “one-thread-one-point” and “one-thread-one-line”, to maximize the performance. Second, we present a dual-level parallelization scheme using the CPU/GPU collaborative model to exploit the computational resources of both multi-core CPUs and many-core GPUs within the heterogeneous platform. Finally, considering the fact that memory on a single node becomes inadequate when the simulation size grows, we present a tri-level hybrid programming pattern MPI-OpenMP-CUDA that merges fine-grain parallelism using OpenMP and CUDA threads with coarse-grain parallelism using MPI for inter-node communication. We also propose a strategy to overlap the computation with communication using the advanced features of CUDA and MPI programming. We obtain speedups of 6.0 for the ADI solver on one Tesla M2050 GPU in contrast to two Xeon X5670 CPUs. Scalability tests show that our implementation can offer significant performance improvement on heterogeneous platform.

Application of microarray analysis on computer cluster and cloud platforms.

Science.gov (United States)

Bernau, C; Boulesteix, A-L; Knaus, J

2013-01-01

Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

Analytics Platform for ATLAS Computing Services

CERN Document Server

Vukotic, Ilija; The ATLAS collaboration; Bryant, Lincoln

2016-01-01

Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Log file data and database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data so as to simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of machine learning tools like Spark, Jupyter, R, S...

Applications integration in a hybrid cloud computing environment: modelling and platform

Science.gov (United States)

Li, Qing; Wang, Ze-yuan; Li, Wei-hua; Li, Jun; Wang, Cheng; Du, Rui-yang

2013-08-01

With the development of application services providers and cloud computing, more and more small- and medium-sized business enterprises use software services and even infrastructure services provided by professional information service companies to replace all or part of their information systems (ISs). These information service companies provide applications, such as data storage, computing processes, document sharing and even management information system services as public resources to support the business process management of their customers. However, no cloud computing service vendor can satisfy the full functional IS requirements of an enterprise. As a result, enterprises often have to simultaneously use systems distributed in different clouds and their intra enterprise ISs. Thus, this article presents a framework to integrate applications deployed in public clouds and intra ISs. A run-time platform is developed and a cross-computing environment process modelling technique is also developed to improve the feasibility of ISs under hybrid cloud computing environments.

Performance Analysis of Multiple Wave Energy Converters Placed on a Floating Platform in the Frequency Domain

Directory of Open Access Journals (Sweden)

Hyebin Lee

2018-02-01

Full Text Available Wind-wave hybrid power generation systems have the potential to become a significant source of affordable renewable energy. However, their strong interactions with both wind- and wave-induced forces raise a number of technical challenges for modelling. The present study undertakes a numerical investigation on multi-body hydrodynamic interaction between a wind-wave hybrid floating platform and multiple wave energy converters (WECs in a frequency domain. In addition to the exact responses of the platform and the WECs, the power take-off (PTO mechanism was taken into account for analysis. The coupled hydrodynamic coefficients and wave exciting forces were obtained from WAMIT, the 3D diffraction/radiation solver based on the boundary element method. The overall performance of the multiple WECs is presented and compared with the performance of a single isolated WEC. The analysis showed significant differences in the dynamic responses of the WECs when the multi-body interaction was considered. In addition, the PTO damping effect made a considerable difference to the responses of the WECs. However, the platform response was only minimally affected by PTO damping. With regard to energy capture, the interaction effect of the designed multiple WEC array layout is evaluated. The WEC array configuration showed both constructive and destructive effects in accordance with the incident wave frequency and direction.

Google Earth Engine: a new cloud-computing platform for global-scale earth observation data and analysis

Science.gov (United States)

Moore, R. T.; Hansen, M. C.

2011-12-01

Google Earth Engine is a new technology platform that enables monitoring and measurement of changes in the earth's environment, at planetary scale, on a large catalog of earth observation data. The platform offers intrinsically-parallel computational access to thousands of computers in Google's data centers. Initial efforts have focused primarily on global forest monitoring and measurement, in support of REDD+ activities in the developing world. The intent is to put this platform into the hands of scientists and developing world nations, in order to advance the broader operational deployment of existing scientific methods, and strengthen the ability for public institutions and civil society to better understand, manage and report on the state of their natural resources. Earth Engine currently hosts online nearly the complete historical Landsat archive of L5 and L7 data collected over more than twenty-five years. Newly-collected Landsat imagery is downloaded from USGS EROS Center into Earth Engine on a daily basis. Earth Engine also includes a set of historical and current MODIS data products. The platform supports generation, on-demand, of spatial and temporal mosaics, "best-pixel" composites (for example to remove clouds and gaps in satellite imagery), as well as a variety of spectral indices. Supervised learning methods are available over the Landsat data catalog. The platform also includes a new application programming framework, or "API", that allows scientists access to these computational and data resources, to scale their current algorithms or develop new ones. Under the covers of the Google Earth Engine API is an intrinsically-parallel image-processing system. Several forest monitoring applications powered by this API are currently in development and expected to be operational in 2011. Combining science with massive data and technology resources in a cloud-computing framework can offer advantages of computational speed, ease-of-use and collaboration, as

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.

Information-computational platform for collaborative multidisciplinary investigations of regional climatic changes and their impacts

Science.gov (United States)

Gordov, Evgeny; Lykosov, Vasily; Krupchatnikov, Vladimir; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara

2013-04-01

Analysis of growing volume of related to climate change data from sensors and model outputs requires collaborative multidisciplinary efforts of researchers. To do it timely and in reliable way one needs in modern information-computational infrastructure supporting integrated studies in the field of environmental sciences. Recently developed experimental software and hardware platform Climate (http://climate.scert.ru/) provides required environment for regional climate change related investigations. The platform combines modern web 2.0 approach, GIS-functionality and capabilities to run climate and meteorological models, process large geophysical datasets and support relevant analysis. It also supports joint software development by distributed research groups, and organization of thematic education for students and post-graduate students. In particular, platform software developed includes dedicated modules for numerical processing of regional and global modeling results for consequent analysis and visualization. Also run of integrated into the platform WRF and «Planet Simulator» models, modeling results data preprocessing and visualization is provided. All functions of the platform are accessible by a user through a web-portal using common graphical web-browser in the form of an interactive graphical user interface which provides, particularly, capabilities of selection of geographical region of interest (pan and zoom), data layers manipulation (order, enable/disable, features extraction) and visualization of results. Platform developed provides users with capabilities of heterogeneous geophysical data analysis, including high-resolution data, and discovering of tendencies in climatic and ecosystem changes in the framework of different multidisciplinary researches. Using it even unskilled user without specific knowledge can perform reliable computational processing and visualization of large meteorological, climatic and satellite monitoring datasets through

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.

Targeting Accuracy of Image-Guided Radiosurgery for Intracranial Lesions: A Comparison Across Multiple Linear Accelerator Platforms.

Science.gov (United States)

Huang, Yimei; Zhao, Bo; Chetty, Indrin J; Brown, Stephen; Gordon, James; Wen, Ning

2016-04-01

To evaluate the overall positioning accuracy of image-guided intracranial radiosurgery across multiple linear accelerator platforms. A computed tomography scan with a slice thickness of 1.0 mm was acquired of an anthropomorphic head phantom in a BrainLAB U-frame mask. The phantom was embedded with three 5-mm diameter tungsten ball bearings, simulating a central, a left, and an anterior cranial lesion. The ball bearings were positioned to radiation isocenter under ExacTrac X-ray or cone-beam computed tomography image guidance on 3 Linacs: (1) ExacTrac X-ray localization on a Novalis Tx; (2) cone-beam computed tomography localization on the Novalis Tx; (3) cone-beam computed tomography localization on a TrueBeam; and (4) cone-beam computed tomography localization on an Edge. Each ball bearing was positioned 5 times to the radiation isocenter with different initial setup error following the 4 image guidance procedures on the 3 Linacs, and the mean (µ) and one standard deviation (σ) of the residual error were compared. Averaged overall 3 ball bearing locations, the vector length of the residual setup error in mm (µ ± σ) was 0.6 ± 0.2, 1.0 ± 0.5, 0.2 ± 0.1, and 0.3 ± 0.1 on ExacTrac X-ray localization on a Novalis Tx, cone-beam computed tomography localization on the Novalis Tx, cone-beam computed tomography localization on a TrueBeam, and cone-beam computed tomography localization on an Edge, with their range in mm being 0.4 to 1.1, 0.4 to 1.9, 0.1 to 0.5, and 0.2 to 0.6, respectively. The congruence between imaging and radiation isocenters in mm was 0.6 ± 0.1, 0.7 ± 0.1, 0.3 ± 0.1, and 0.2 ± 0.1, for the 4 systems, respectively. Targeting accuracy comparable to frame-based stereotactic radiosurgery can be achieved with image-guided intracranial stereotactic radiosurgery treatment. © The Author(s) 2015.

Acceleration of Cherenkov angle reconstruction with the new Intel Xeon/FPGA compute platform for the particle identification in the LHCb Upgrade

Science.gov (United States)

Faerber, Christian

2017-10-01

The LHCb experiment at the LHC will upgrade its detector by 2018/2019 to a ‘triggerless’ readout scheme, where all the readout electronics and several sub-detector parts will be replaced. The new readout electronics will be able to readout the detector at 40 MHz. This increases the data bandwidth from the detector down to the Event Filter farm to 40 TBit/s, which also has to be processed to select the interesting proton-proton collision for later storage. The architecture of such a computing farm, which can process this amount of data as efficiently as possible, is a challenging task and several compute accelerator technologies are being considered for use inside the new Event Filter farm. In the high performance computing sector more and more FPGA compute accelerators are used to improve the compute performance and reduce the power consumption (e.g. in the Microsoft Catapult project and Bing search engine). Also for the LHCb upgrade the usage of an experimental FPGA accelerated computing platform in the Event Building or in the Event Filter farm is being considered and therefore tested. This platform from Intel hosts a general CPU and a high performance FPGA linked via a high speed link which is for this platform a QPI link. On the FPGA an accelerator is implemented. The used system is a two socket platform from Intel with a Xeon CPU and an FPGA. The FPGA has cache-coherent memory access to the main memory of the server and can collaborate with the CPU. As a first step, a computing intensive algorithm to reconstruct Cherenkov angles for the LHCb RICH particle identification was successfully ported in Verilog to the Intel Xeon/FPGA platform and accelerated by a factor of 35. The same algorithm was ported to the Intel Xeon/FPGA platform with OpenCL. The implementation work and the performance will be compared. Also another FPGA accelerator the Nallatech 385 PCIe accelerator with the same Stratix V FPGA were tested for performance. The results show that the Intel

Multiple Intelligences: The Most Effective Platform for Global 21st Century Educational and Instructional Methodologies

Science.gov (United States)

McFarlane, Donovan A.

2011-01-01

This paper examines the theory of Multiple Intelligences (MI) as the most viable and effective platform for 21st century educational and instructional methodologies based on the understanding of the value of diversity in today's classrooms and educational institutions, the unique qualities and characteristics of individual learners, the…

Multiple Embedded Processors for Fault-Tolerant Computing

Science.gov (United States)

Bolotin, Gary; Watson, Robert; Katanyoutanant, Sunant; Burke, Gary; Wang, Mandy

2005-01-01

A fault-tolerant computer architecture has been conceived in an effort to reduce vulnerability to single-event upsets (spurious bit flips caused by impingement of energetic ionizing particles or photons). As in some prior fault-tolerant architectures, the redundancy needed for fault tolerance is obtained by use of multiple processors in one computer. Unlike prior architectures, the multiple processors are embedded in a single field-programmable gate array (FPGA). What makes this new approach practical is the recent commercial availability of FPGAs that are capable of having multiple embedded processors. A working prototype (see figure) consists of two embedded IBM PowerPC 405 processor cores and a comparator built on a Xilinx Virtex-II Pro FPGA. This relatively simple instantiation of the architecture implements an error-detection scheme. A planned future version, incorporating four processors and two comparators, would correct some errors in addition to detecting them.

Possibilities of computer tomography in multiple sclerosis

International Nuclear Information System (INIS)

Vymazal, J.; Bauer, J.

1983-01-01

Computer tomography was performed in 41 patients with multiple sclerosis, the average age of patients being 40.8 years. Native examinations were made of 17 patients, examinations with contrast medium of 19, both methods were used in the examination of 5 patients. In 26 patients, i.e. in almost two-thirds, cerebral atrophy was found, in 11 of a severe type. In 9 patients atrophy affected only the hemispheres, in 16 also the stem and cerebellum. The stem and cerebellum only were affected in 1 patient. Hypodense foci were found in 21 patients, i.e. more than half of those examined. In 9 there were multiple foci. In most of the 19 examined patients the hypodense changes were in the hemispheres and only in 2 in the cerebellum and brain stem. No hyperdense changes were detected. The value and possibilities are discussed of examinations by computer tomography multiple sclerosis. (author)

Scientific data analysis on data-parallel platforms.

Energy Technology Data Exchange (ETDEWEB)

Ulmer, Craig D.; Bayer, Gregory W.; Choe, Yung Ryn; Roe, Diana C.

2010-09-01

As scientific computing users migrate to petaflop platforms that promise to generate multi-terabyte datasets, there is a growing need in the community to be able to embed sophisticated analysis algorithms in the computing platforms' storage systems. Data Warehouse Appliances (DWAs) are attractive for this work, due to their ability to store and process massive datasets efficiently. While DWAs have been utilized effectively in data-mining and informatics applications, they remain largely unproven in scientific workloads. In this paper we present our experiences in adapting two mesh analysis algorithms to function on five different DWA architectures: two Netezza database appliances, an XtremeData dbX database, a LexisNexis DAS, and multiple Hadoop MapReduce clusters. The main contribution of this work is insight into the differences between these DWAs from a user's perspective. In addition, we present performance measurements for ten DWA systems to help understand the impact of different architectural trade-offs in these systems.

The Relationship between Chief Information Officer Transformational Leadership and Computing Platform Operating Systems

Science.gov (United States)

Anderson, George W.

2010-01-01

The purpose of this study was to relate the strength of Chief Information Officer (CIO) transformational leadership behaviors to 1 of 5 computing platform operating systems (OSs) that may be selected for a firm's Enterprise Resource Planning (ERP) business system. Research shows executive leader behaviors may promote innovation through the use of…

Cross-platform digital assessment forms for evaluating surgical skills

Directory of Open Access Journals (Sweden)

Steven Arild Wuyts Andersen

2015-04-01

Full Text Available A variety of structured assessment tools for use in surgical training have been reported, but extant assessment tools often employ paper-based rating forms. Digital assessment forms for evaluating surgical skills could potentially offer advantages over paper-based forms, especially in complex assessment situations. In this paper, we report on the development of cross-platform digital assessment forms for use with multiple raters in order to facilitate the automatic processing of surgical skills assessments that include structured ratings. The FileMaker 13 platform was used to create a database containing the digital assessment forms, because this software has cross-platform functionality on both desktop computers and handheld devices. The database is hosted online, and the rating forms can therefore also be accessed through most modern web browsers. Cross-platform digital assessment forms were developed for the rating of surgical skills. The database platform used in this study was reasonably priced, intuitive for the user, and flexible. The forms have been provided online as free downloads that may serve as the basis for further development or as inspiration for future efforts. In conclusion, digital assessment forms can be used for the structured rating of surgical skills and have the potential to be especially useful in complex assessment situations with multiple raters, repeated assessments in various times and locations, and situations requiring substantial subsequent data processing or complex score calculations.

Design and performance of the virtualization platform for offline computing on the ATLAS TDAQ Farm

Science.gov (United States)

Ballestrero, S.; Batraneanu, S. M.; Brasolin, F.; Contescu, C.; Di Girolamo, A.; Lee, C. J.; Pozo Astigarraga, M. E.; Scannicchio, D. A.; Twomey, M. S.; Zaytsev, A.

2014-06-01

With the LHC collider at CERN currently going through the period of Long Shutdown 1 there is an opportunity to use the computing resources of the experiments' large trigger farms for other data processing activities. In the case of the ATLAS experiment, the TDAQ farm, consisting of more than 1500 compute nodes, is suitable for running Monte Carlo (MC) production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of the design and deployment of a virtualized platform running on this computing resource and of its use to run large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to guarantee the security and the usability of the ATLAS private network, and to minimize interference with TDAQ's usage of the farm. Openstack has been chosen to provide a cloud management layer. The experience gained in the last 3.5 months shows that the use of the TDAQ farm for the MC simulation contributes to the ATLAS data processing at the level of a large Tier-1 WLCG site, despite the opportunistic nature of the underlying computing resources being used.

A Novel Wiki-Based Remote Laboratory Platform for Engineering Education

Science.gov (United States)

Wang, Ning; Chen, Xuemin; Lan, Qianlong; Song, Gangbing; Parsaei, Hamid R.; Ho, Siu-Chun

2017-01-01

With the unprecedented growth of e-learning, more and more new IT technologies are used to develop e-learning tools. As one of the most common forms of social computing, Wiki technology has been used to develop the collaborative and cooperative learning platform to support multiple users learning online effectively. In this paper, we propose a new…

Real-Time Audio Processing on the T-CREST Multicore Platform

DEFF Research Database (Denmark)

Ausin, Daniel Sanz; Pezzarossa, Luca; Schoeberl, Martin

2017-01-01

of the audio signal. This paper presents a real-time multicore audio processing system based on the T-CREST platform. T-CREST is a time-predictable multicore processor for real-time embedded systems. Multiple audio effect tasks have been implemented, which can be connected together in different configurations...... forming sequential and parallel effect chains, and using a network-onchip for intercommunication between processors. The evaluation of the system shows that real-time processing of multiple effect configurations is possible, and that the estimation and control of latency ensures real-time behavior.......Multicore platforms are nowadays widely used for audio processing applications, due to the improvement of computational power that they provide. However, some of these systems are not optimized for temporally constrained environments, which often leads to an undesired increase in the latency...

High-Throughput Computing on High-Performance Platforms: A Case Study

Energy Technology Data Exchange (ETDEWEB)

Oleynik, D [University of Texas at Arlington; Panitkin, S [Brookhaven National Laboratory (BNL); Matteo, Turilli [Rutgers University; Angius, Alessio [Rutgers University; Oral, H Sarp [ORNL; De, K [University of Texas at Arlington; Klimentov, A [Brookhaven National Laboratory (BNL); Wells, Jack C. [ORNL; Jha, S [Rutgers University

2017-10-01

The computing systems used by LHC experiments has historically consisted of the federation of hundreds to thousands of distributed resources, ranging from small to mid-size resource. In spite of the impressive scale of the existing distributed computing solutions, the federation of small to mid-size resources will be insufficient to meet projected future demands. This paper is a case study of how the ATLAS experiment has embraced Titan -- a DOE leadership facility in conjunction with traditional distributed high- throughput computing to reach sustained production scales of approximately 52M core-hours a years. The three main contributions of this paper are: (i) a critical evaluation of design and operational considerations to support the sustained, scalable and production usage of Titan; (ii) a preliminary characterization of a next generation executor for PanDA to support new workloads and advanced execution modes; and (iii) early lessons for how current and future experimental and observational systems can be integrated with production supercomputers and other platforms in a general and extensible manner.

Development of a Cloud Computing-Based Pier Type Port Structure Stability Evaluation Platform Using Fiber Bragg Grating Sensors.

Science.gov (United States)

Jo, Byung Wan; Jo, Jun Ho; Khan, Rana Muhammad Asad; Kim, Jung Hoon; Lee, Yun Sung

2018-05-23

Structure Health Monitoring is a topic of great interest in port structures due to the ageing of structures and the limitations of evaluating structures. This paper presents a cloud computing-based stability evaluation platform for a pier type port structure using Fiber Bragg Grating (FBG) sensors in a system consisting of a FBG strain sensor, FBG displacement gauge, FBG angle meter, gateway, and cloud computing-based web server. The sensors were installed on core components of the structure and measurements were taken to evaluate the structures. The measurement values were transmitted to the web server via the gateway to analyze and visualize them. All data were analyzed and visualized in the web server to evaluate the structure based on the safety evaluation index (SEI). The stability evaluation platform for pier type port structures involves the efficient monitoring of the structures which can be carried out easily anytime and anywhere by converging new technologies such as cloud computing and FBG sensors. In addition, the platform has been successfully implemented at “Maryang Harbor” situated in Maryang-Meyon of Korea to test its durability.

Multiple-User, Multitasking, Virtual-Memory Computer System

Science.gov (United States)

Generazio, Edward R.; Roth, Don J.; Stang, David B.

1993-01-01

Computer system designed and programmed to serve multiple users in research laboratory. Provides for computer control and monitoring of laboratory instruments, acquisition and anlaysis of data from those instruments, and interaction with users via remote terminals. System provides fast access to shared central processing units and associated large (from megabytes to gigabytes) memories. Underlying concept of system also applicable to monitoring and control of industrial processes.

Multivariate Gradient Analysis for Evaluating and Visualizing a Learning System Platform for Computer Programming

Science.gov (United States)

Mather, Richard

2015-01-01

This paper explores the application of canonical gradient analysis to evaluate and visualize student performance and acceptance of a learning system platform. The subject of evaluation is a first year BSc module for computer programming. This uses "Ceebot," an animated and immersive game-like development environment. Multivariate…

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...

Design and Delivery of Multiple Server-Side Computer Languages Course

Science.gov (United States)

Wang, Shouhong; Wang, Hai

2011-01-01

Given the emergence of service-oriented architecture, IS students need to be knowledgeable of multiple server-side computer programming languages to be able to meet the needs of the job market. This paper outlines the pedagogy of an innovative course of multiple server-side computer languages for the undergraduate IS majors. The paper discusses…

Design and Performance of the Virtualization Platform for Offline computing on the ATLAS TDAQ Farm

CERN Document Server

Ballestrero, S; The ATLAS collaboration; Brasolin, F; Contescu, C; Di Girolamo, A; Lee, C J; Pozo Astigarraga, M E; Scannicchio, D A; Twomey, M S; Zaytsev, A

2013-01-01

With the LHC collider at CERN currently going through the period of Long Shutdown 1 (LS1) there is a remarkable opportunity to use the computing resources of the large trigger farms of the experiments for other data processing activities. In the case of ATLAS experiment the TDAQ farm, consisting of more than 1500 compute nodes, is particularly suitable for running Monte Carlo production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of all the stages of Sim@P1 project dedicated to the design and deployment of a virtualized platform running on the ATLAS TDAQ computing resources and using it to run the large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to avoid interference with TDAQ usage of the farm and to guarantee the security and the usability of the ATLAS private network; Openstack has been chosen to provide a cloud management layer. The approaches to organizing support for the sustained operation of...

Design and Performance of the Virtualization Platform for Offline computing on the ATLAS TDAQ Farm

CERN Document Server

Ballestrero, S; The ATLAS collaboration; Brasolin, F; Contescu, C; Di Girolamo, A; Lee, C J; Pozo Astigarraga, M E; Scannicchio, D A; Twomey, M S; Zaytsev, A

2014-01-01

With the LHC collider at CERN currently going through the period of Long Shutdown 1 (LS1) there is a remarkable opportunity to use the computing resources of the large trigger farms of the experiments for other data processing activities. In the case of ATLAS experiment the TDAQ farm, consisting of more than 1500 compute nodes, is particularly suitable for running Monte Carlo production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of all the stages of Sim@P1 project dedicated to the design and deployment of a virtualized platform running on the ATLAS TDAQ computing resources and using it to run the large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to avoid interference with TDAQ usage of the farm and to guarantee the security and the usability of the ATLAS private network; Openstack has been chosen to provide a cloud management layer. The approaches to organizing support for the sustained operation of...

Contributing to global computing platform: gliding, tunneling standard services and high energy physics application

International Nuclear Information System (INIS)

Lodygensky, O.

2006-09-01

Centralized computers have been replaced by 'client/server' distributed architectures which are in turn in competition with new distributed systems known as 'peer to peer'. These new technologies are widely spread, and trading, industry and the research world have understood the new goals involved and massively invest around these new technologies, named 'grid'. One of the fields is about calculating. This is the subject of the works presented here. At the Paris Orsay University, a synergy emerged between the Computing Science Laboratory (LRI) and the Linear Accelerator Laboratory (LAL) on grid infrastructure, opening new investigations fields for the first and new high computing perspective for the other. Works presented here are the results of this multi-discipline collaboration. They are based on XtremWeb, the LRI global computing platform. We first introduce a state of the art of the large scale distributed systems, its principles, its architecture based on services. We then introduce XtremWeb and detail modifications and improvements we had to specify and implement to achieve our goals. We present two different studies, first interconnecting grids in order to generalize resource sharing and secondly, be able to use legacy services on such platforms. We finally explain how a research community like the community of high energy cosmic radiation detection can gain access to these services and detail Monte Carlos and data analysis processes over the grids. (author)

SWIMS: a small-angle multiple scattering computer code

International Nuclear Information System (INIS)

Sayer, R.O.

1976-07-01

SWIMS (Sigmund and WInterbon Multiple Scattering) is a computer code for calculation of the angular dispersion of ion beams that undergo small-angle, incoherent multiple scattering by gaseous or solid media. The code uses the tabulated angular distributions of Sigmund and Winterbon for a Thomas-Fermi screened Coulomb potential. The fraction of the incident beam scattered into a cone defined by the polar angle α is computed as a function of α for reduced thicknesses over the range 0.01 less than or equal to tau less than or equal to 10.0. 1 figure, 2 tables

A high performance, low power computational platform for complex sensing operations in smart cities

KAUST Repository

Jiang, Jiming; Claudel, Christian

2017-01-01

This paper presents a new wireless platform designed for an integrated traffic/flash flood monitoring system. The sensor platform is built around a 32-bit ARM Cortex M4 microcontroller and a 2.4GHz 802.15.4802.15.4 ISM compliant radio module. It can be interfaced with fixed traffic sensors, or receive data from vehicle transponders. This platform is specifically designed for solar-powered, low bandwidth, high computational performance wireless sensor network applications. A self-recovering unit is designed to increase reliability and allow periodic hard resets, an essential requirement for sensor networks. A radio monitoring circuitry is proposed to monitor incoming and outgoing transmissions, simplifying software debugging. We illustrate the performance of this wireless sensor platform on complex problems arising in smart cities, such as traffic flow monitoring, machine-learning-based flash flood monitoring or Kalman-filter based vehicle trajectory estimation. All design files have been uploaded and shared in an open science framework, and can be accessed from [1]. The hardware design is under CERN Open Hardware License v1.2.

A high performance, low power computational platform for complex sensing operations in smart cities

KAUST Repository

Jiang, Jiming

2017-02-02

This paper presents a new wireless platform designed for an integrated traffic/flash flood monitoring system. The sensor platform is built around a 32-bit ARM Cortex M4 microcontroller and a 2.4GHz 802.15.4802.15.4 ISM compliant radio module. It can be interfaced with fixed traffic sensors, or receive data from vehicle transponders. This platform is specifically designed for solar-powered, low bandwidth, high computational performance wireless sensor network applications. A self-recovering unit is designed to increase reliability and allow periodic hard resets, an essential requirement for sensor networks. A radio monitoring circuitry is proposed to monitor incoming and outgoing transmissions, simplifying software debugging. We illustrate the performance of this wireless sensor platform on complex problems arising in smart cities, such as traffic flow monitoring, machine-learning-based flash flood monitoring or Kalman-filter based vehicle trajectory estimation. All design files have been uploaded and shared in an open science framework, and can be accessed from [1]. The hardware design is under CERN Open Hardware License v1.2.

Cloud Computing Platform for an Online Model Library System

Directory of Open Access Journals (Sweden)

Mingang Chen

2013-01-01

Full Text Available The rapid developing of digital content industry calls for online model libraries. For the efficiency, user experience, and reliability merits of the model library, this paper designs a Web 3D model library system based on a cloud computing platform. Taking into account complex models, which cause difficulties in real-time 3D interaction, we adopt the model simplification and size adaptive adjustment methods to make the system with more efficient interaction. Meanwhile, a cloud-based architecture is developed to ensure the reliability and scalability of the system. The 3D model library system is intended to be accessible by online users with good interactive experiences. The feasibility of the solution has been tested by experiments.

Design Tools for Accelerating Development and Usage of Multi-Core Computing Platforms

Science.gov (United States)

2014-04-01

Government formulated or supplied the drawings, specifications, or other data does not license the holder or any other person or corporation ; or convey...multicore PDSP platforms. The GPU- based capabilities of TDIF are currently oriented towards NVIDIA GPUs, based on the Compute Unified Device Architecture...CUDA) programming language [ NVIDIA 2007], which can be viewed as an extension of C. The multicore PDSP capabilities currently in TDIF are oriented

A Framework for the Generation and Dissemination of Drop Size Distribution (DSD) Characteristics Using Multiple Platforms

Science.gov (United States)

Wolf, David B.; Tokay, Ali; Petersen, Walt; Williams, Christopher; Gatlin, Patrick; Wingo, Mathew

2010-01-01

Proper characterization of the precipitation drop size distribution (DSD) is integral to providing realistic and accurate space- and ground-based precipitation retrievals. Current technology allows for the development of DSD products from a variety of platforms, including disdrometers, vertical profilers and dual-polarization radars. Up to now, however, the dissemination or availability of such products has been limited to individual sites and/or field campaigns, in a variety of formats, often using inconsistent algorithms for computing the integral DSD parameters, such as the median- and mass-weighted drop diameter, total number concentration, liquid water content, rain rate, etc. We propose to develop a framework for the generation and dissemination of DSD characteristic products using a unified structure, capable of handling the myriad collection of disdrometers, profilers, and dual-polarization radar data currently available and to be collected during several upcoming GPM Ground Validation field campaigns. This DSD super-structure paradigm is an adaptation of the radar super-structure developed for NASA s Radar Software Library (RSL) and RSL_in_IDL. The goal is to provide the DSD products in a well-documented format, most likely NetCDF, along with tools to ingest and analyze the products. In so doing, we can develop a robust archive of DSD products from multiple sites and platforms, which should greatly benefit the development and validation of precipitation retrieval algorithms for GPM and other precipitation missions. An outline of this proposed framework will be provided as well as a discussion of the algorithms used to calculate the DSD parameters.

Computed Tomography diagnosis of skeletal involvement in multiple myeloma

International Nuclear Information System (INIS)

Scutellari, Pier Nuccio; Galeotti, Roberto; Leprotti, Stefano; Piva, Nadia; Spanedda, Romedio

1997-01-01

The authors assess the role of Computed Topography in the diagnosis and management of multiple myeloma (MM) and investigate if Computed Tomography findings can influence the clinical approach, prognosis and treatment. 273 multiple myeloma patients submitted to Computed Tomography June 1994, to December, 1996. The patients were 143 men and 130 women (mean age: 65 years): 143 were stage I, 38 stage II and 92 stage III according to Durie and Salomon's clinical classification. All patients were submitted to blood tests, spinal radiography and Computed Tomography, the latter with serial 5-mm scans on several vertebral bodies. Computed Tomography despicted vertebral arch and process involvement in 3 cases with the vertebral pedicle sign. Moreover, Computed Tomography proved superior to radiography in showing the spread of myelomatous masses into the soft tissues in a case with solitary permeative lesion in the left public bone, which facilitated subsequent biopsy. As for extraosseous localizations, Computed Tomography demonstrated thoracic soft tissue (1 woman) and pelvic (1 man) involvement by myelomtous masses penetrating into surrounding tissues. In our series, only a case of osteosclerotic bone myeloma was observed in the pelvis, associated with lytic abnormalities. Computed Tomography findings do not seem to improve the clinical approach and therapeutic management of the disease. Nevertheless, the authors reccommend Computed Tomography for some myelomatous conditions, namely: a) in the patients with focal bone pain but normal skeletal radiographs; b) in the patients with M protein, bone marrow plasmocytosis and back pain, but with an incoclusive multiple myeloma diagnosis; c) to asses bone spread in the regions which are anatomically complex or difficult to study with radiography and to depict soft tissue involvement; d) for bone biopsy

Homemade Buckeye-Pi: A Learning Many-Node Platform for High-Performance Parallel Computing

Science.gov (United States)

Amooie, M. A.; Moortgat, J.

2017-12-01

We report on the "Buckeye-Pi" cluster, the supercomputer developed in The Ohio State University School of Earth Sciences from 128 inexpensive Raspberry Pi (RPi) 3 Model B single-board computers. Each RPi is equipped with fast Quad Core 1.2GHz ARMv8 64bit processor, 1GB of RAM, and 32GB microSD card for local storage. Therefore, the cluster has a total RAM of 128GB that is distributed on the individual nodes and a flash capacity of 4TB with 512 processors, while it benefits from low power consumption, easy portability, and low total cost. The cluster uses the Message Passing Interface protocol to manage the communications between each node. These features render our platform the most powerful RPi supercomputer to date and suitable for educational applications in high-performance-computing (HPC) and handling of large datasets. In particular, we use the Buckeye-Pi to implement optimized parallel codes in our in-house simulator for subsurface media flows with the goal of achieving a massively-parallelized scalable code. We present benchmarking results for the computational performance across various number of RPi nodes. We believe our project could inspire scientists and students to consider the proposed unconventional cluster architecture as a mainstream and a feasible learning platform for challenging engineering and scientific problems.

Interactive computer-assisted instruction in acid-base physiology for mobile computer platforms.

Science.gov (United States)

Longmuir, Kenneth J

2014-03-01

In this project, the traditional lecture hall presentation of acid-base physiology in the first-year medical school curriculum was replaced by interactive, computer-assisted instruction designed primarily for the iPad and other mobile computer platforms. Three learning modules were developed, each with ∼20 screens of information, on the subjects of the CO2-bicarbonate buffer system, other body buffer systems, and acid-base disorders. Five clinical case modules were also developed. For the learning modules, the interactive, active learning activities were primarily step-by-step learner control of explanations of complex physiological concepts, usually presented graphically. For the clinical cases, the active learning activities were primarily question-and-answer exercises that related clinical findings to the relevant basic science concepts. The student response was remarkably positive, with the interactive, active learning aspect of the instruction cited as the most important feature. Also, students cited the self-paced instruction, extensive use of interactive graphics, and side-by-side presentation of text and graphics as positive features. Most students reported that it took less time to study the subject matter with this online instruction compared with subject matter presented in the lecture hall. However, the approach to learning was highly examination driven, with most students delaying the study of the subject matter until a few days before the scheduled examination. Wider implementation of active learning computer-assisted instruction will require that instructors present subject matter interactively, that students fully embrace the responsibilities of independent learning, and that institutional administrations measure instructional effort by criteria other than scheduled hours of instruction.

Design and performance of the virtualization platform for offline computing on the ATLAS TDAQ Farm

International Nuclear Information System (INIS)

Ballestrero, S; Lee, C J; Batraneanu, S M; Scannicchio, D A; Brasolin, F; Contescu, C; Girolamo, A Di; Astigarraga, M E Pozo; Twomey, M S; Zaytsev, A

2014-01-01

With the LHC collider at CERN currently going through the period of Long Shutdown 1 there is an opportunity to use the computing resources of the experiments' large trigger farms for other data processing activities. In the case of the ATLAS experiment, the TDAQ farm, consisting of more than 1500 compute nodes, is suitable for running Monte Carlo (MC) production jobs that are mostly CPU and not I/O bound. This contribution gives a thorough review of the design and deployment of a virtualized platform running on this computing resource and of its use to run large groups of CernVM based virtual machines operating as a single CERN-P1 WLCG site. This platform has been designed to guarantee the security and the usability of the ATLAS private network, and to minimize interference with TDAQ's usage of the farm. Openstack has been chosen to provide a cloud management layer. The experience gained in the last 3.5 months shows that the use of the TDAQ farm for the MC simulation contributes to the ATLAS data processing at the level of a large Tier-1 WLCG site, despite the opportunistic nature of the underlying computing resources being used.

Virtual network computing: cross-platform remote display and collaboration software.

Science.gov (United States)

Konerding, D E

1999-04-01

VNC (Virtual Network Computing) is a computer program written to address the problem of cross-platform remote desktop/application display. VNC uses a client/server model in which an image of the desktop of the server is transmitted to the client and displayed. The client collects mouse and keyboard input from the user and transmits them back to the server. The VNC client and server can run on Windows 95/98/NT, MacOS, and Unix (including Linux) operating systems. VNC is multi-user on Unix machines (any number of servers can be run are unrelated to the primary display of the computer), while it is effectively single-user on Macintosh and Windows machines (only one server can be run, displaying the contents of the primary display of the server). The VNC servers can be configured to allow more than one client to connect at one time, effectively allowing collaboration through the shared desktop. I describe the function of VNC, provide details of installation, describe how it achieves its goal, and evaluate the use of VNC for molecular modelling. VNC is an extremely useful tool for collaboration, instruction, software development, and debugging of graphical programs with remote users.

A computer simulation platform for the estimation of measurement uncertainties in dimensional X-ray computed tomography

DEFF Research Database (Denmark)

Hiller, Jochen; Reindl, Leonard M

2012-01-01

into account the main error sources for the measurement. This method has the potential to deal with all kinds of systematic and random errors that influence a dimensional CT measurement. A case study demonstrates the practical application of the VCT simulator using numerically generated CT data and statistical......The knowledge of measurement uncertainty is of great importance in conformance testing in production. The tolerance limit for production must be reduced by the amounts of measurement uncertainty to ensure that the parts are in fact within the tolerance. Over the last 5 years, industrial X......-ray computed tomography (CT) has become an important technology for dimensional quality control. In this paper a computer simulation platform is presented which is able to investigate error sources in dimensional CT measurements. The typical workflow in industrial CT metrology is described and methods...

The “Chimera”: An Off-The-Shelf CPU/GPGPU/FPGA Hybrid Computing Platform

Directory of Open Access Journals (Sweden)

Ra Inta

2012-01-01

Full Text Available The nature of modern astronomy means that a number of interesting problems exhibit a substantial computational bound and this situation is gradually worsening. Scientists, increasingly fighting for valuable resources on conventional high-performance computing (HPC facilities—often with a limited customizable user environment—are increasingly looking to hardware acceleration solutions. We describe here a heterogeneous CPU/GPGPU/FPGA desktop computing system (the “Chimera”, built with commercial-off-the-shelf components. We show that this platform may be a viable alternative solution to many common computationally bound problems found in astronomy, however, not without significant challenges. The most significant bottleneck in pipelines involving real data is most likely to be the interconnect (in this case the PCI Express bus residing on the CPU motherboard. Finally, we speculate on the merits of our Chimera system on the entire landscape of parallel computing, through the analysis of representative problems from UC Berkeley’s “Thirteen Dwarves.”

3D virtual human atria: A computational platform for studying clinical atrial fibrillation.

Science.gov (United States)

Aslanidi, Oleg V; Colman, Michael A; Stott, Jonathan; Dobrzynski, Halina; Boyett, Mark R; Holden, Arun V; Zhang, Henggui

2011-10-01

Despite a vast amount of experimental and clinical data on the underlying ionic, cellular and tissue substrates, the mechanisms of common atrial arrhythmias (such as atrial fibrillation, AF) arising from the functional interactions at the whole atria level remain unclear. Computational modelling provides a quantitative framework for integrating such multi-scale data and understanding the arrhythmogenic behaviour that emerges from the collective spatio-temporal dynamics in all parts of the heart. In this study, we have developed a multi-scale hierarchy of biophysically detailed computational models for the human atria--the 3D virtual human atria. Primarily, diffusion tensor MRI reconstruction of the tissue geometry and fibre orientation in the human sinoatrial node (SAN) and surrounding atrial muscle was integrated into the 3D model of the whole atria dissected from the Visible Human dataset. The anatomical models were combined with the heterogeneous atrial action potential (AP) models, and used to simulate the AP conduction in the human atria under various conditions: SAN pacemaking and atrial activation in the normal rhythm, break-down of regular AP wave-fronts during rapid atrial pacing, and the genesis of multiple re-entrant wavelets characteristic of AF. Contributions of different properties of the tissue to mechanisms of the normal rhythm and arrhythmogenesis were investigated. Primarily, the simulations showed that tissue heterogeneity caused the break-down of the normal AP wave-fronts at rapid pacing rates, which initiated a pair of re-entrant spiral waves; and tissue anisotropy resulted in a further break-down of the spiral waves into multiple meandering wavelets characteristic of AF. The 3D virtual atria model itself was incorporated into the torso model to simulate the body surface ECG patterns in the normal and arrhythmic conditions. Therefore, a state-of-the-art computational platform has been developed, which can be used for studying multi

Phonon-based scalable platform for chip-scale quantum computing

Directory of Open Access Journals (Sweden)

Charles M. Reinke

2016-12-01

Full Text Available We present a scalable phonon-based quantum computer on a phononic crystal platform. Practical schemes involve selective placement of a single acceptor atom in the peak of the strain field in a high-Q phononic crystal cavity that enables coupling of the phonon modes to the energy levels of the atom. We show theoretical optimization of the cavity design and coupling waveguide, along with estimated performance figures of the coupled system. A qubit can be created by entangling a phonon at the resonance frequency of the cavity with the atom states. Qubits based on this half-sound, half-matter quasi-particle, called a phoniton, may outcompete other quantum architectures in terms of combined emission rate, coherence lifetime, and fabrication demands.

Integrated reconfigurable multiple-input–multiple-output antenna system with an ultra-wideband sensing antenna for cognitive radio platforms

KAUST Repository

Hussain, Rifaqat

2015-06-18

© The Institution of Engineering and Technology 2015. A compact, novel multi-mode, multi-band frequency reconfigurable multiple-input-multiple-output (MIMO) antenna system, integrated with ultra-wideband (UWB) sensing antenna, is presented. The developed model can be used as a complete antenna platform for cognitive radio applications. The antenna system is developed on a single substrate area of dimensions 65 × 120 mm². The proposed sensing antenna is used to cover a wide range of frequency bands from 710 to 3600 MHz. The frequency reconfigurable dual-element MIMO antenna is integrated with P-type, intrinsic, N-type (PIN) diodes for frequency agility. Different modes of selection are used for the MIMO antenna system reconfigurability to support different wireless system standards. The proposed MIMO antenna configuration is used to cover various frequency bands from 755 to 3450 MHz. The complete system comprising the multi-band reconfigurable MIMO antennas and UWB sensing antenna for cognitive radio applications is proposed with a compact form factor.

GENESIS 1.1: A hybrid-parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms.

Science.gov (United States)

Kobayashi, Chigusa; Jung, Jaewoon; Matsunaga, Yasuhiro; Mori, Takaharu; Ando, Tadashi; Tamura, Koichi; Kamiya, Motoshi; Sugita, Yuji

2017-09-30

GENeralized-Ensemble SImulation System (GENESIS) is a software package for molecular dynamics (MD) simulation of biological systems. It is designed to extend limitations in system size and accessible time scale by adopting highly parallelized schemes and enhanced conformational sampling algorithms. In this new version, GENESIS 1.1, new functions and advanced algorithms have been added. The all-atom and coarse-grained potential energy functions used in AMBER and GROMACS packages now become available in addition to CHARMM energy functions. The performance of MD simulations has been greatly improved by further optimization, multiple time-step integration, and hybrid (CPU + GPU) computing. The string method and replica-exchange umbrella sampling with flexible collective variable choice are used for finding the minimum free-energy pathway and obtaining free-energy profiles for conformational changes of a macromolecule. These new features increase the usefulness and power of GENESIS for modeling and simulation in biological research. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Comparison Of Hybrid Sorting Algorithms Implemented On Different Parallel Hardware Platforms

Directory of Open Access Journals (Sweden)

Dominik Zurek

2013-01-01

Full Text Available Sorting is a common problem in computer science. There are lot of well-known sorting algorithms created for sequential execution on a single processor. Recently, hardware platforms enable to create wide parallel algorithms. We have standard processors consist of multiple cores and hardware accelerators like GPU. The graphic cards with their parallel architecture give new possibility to speed up many algorithms. In this paper we describe results of implementation of a few different sorting algorithms on GPU cards and multicore processors. Then hybrid algorithm will be presented which consists of parts executed on both platforms, standard CPU and GPU.

A peer-to-peer platform for decentralized logistics

OpenAIRE

Gallay, Olivier; Korpela, Kari; Tapio, Niemi; Nurminen, Jukka K.; Kersten, Wolfgang; Blecker, Thorsten; Ringle, Christian M.

2017-01-01

We introduce a novel platform for decentralized logistics, the aim of which is to magnify and accelerate the impact offered by the integration of the most recent advances in Information and Communication Technologies (ICTs) to multi-modal freight operations. The essence of our peer-to-peer (P2P) framework distributes the management of the logistics operations to the multiple actors according to their available computational resources. As a result, this new approach prevents the dominant playe...

University Students Use of Computers and Mobile Devices for Learning and Their Reading Speed on Different Platforms

Science.gov (United States)

Mpofu, Bongeka

2016-01-01

This research was aimed at the investigation of mobile device and computer use at a higher learning institution. The goal was to determine the current use of computers and mobile devices for learning and the students' reading speed on different platforms. The research was contextualised in a sample of students at the University of South Africa.…

Computer studies of multiple-quantum spin dynamics

Energy Technology Data Exchange (ETDEWEB)

Murdoch, J.B.

1982-11-01

The excitation and detection of multiple-quantum (MQ) transitions in Fourier transform NMR spectroscopy is an interesting problem in the quantum mechanical dynamics of spin systems as well as an important new technique for investigation of molecular structure. In particular, multiple-quantum spectroscopy can be used to simplify overly complex spectra or to separate the various interactions between a nucleus and its environment. The emphasis of this work is on computer simulation of spin-system evolution to better relate theory and experiment.

Computer studies of multiple-quantum spin dynamics

International Nuclear Information System (INIS)

Murdoch, J.B.

1982-11-01

The excitation and detection of multiple-quantum (MQ) transitions in Fourier transform NMR spectroscopy is an interesting problem in the quantum mechanical dynamics of spin systems as well as an important new technique for investigation of molecular structure. In particular, multiple-quantum spectroscopy can be used to simplify overly complex spectra or to separate the various interactions between a nucleus and its environment. The emphasis of this work is on computer simulation of spin-system evolution to better relate theory and experiment

A Model for Comparing Free Cloud Platforms

Directory of Open Access Journals (Sweden)

Radu LIXANDROIU

2014-01-01

Full Text Available VMware, VirtualBox, Virtual PC and other popular desktop virtualization applications are used only by a few users of IT techniques. This article attempts to make a comparison model for choosing the best cloud platform. Many virtualization applications such as VMware (VMware Player, Oracle VirtualBox and Microsoft Virtual PC are free for home users. The main goal of the virtualization software is that it allows users to run multiple operating systems simultane-ously on one virtual environment, using one computer desktop.

Vertical Load Distribution for Cloud Computing via Multiple Implementation Options

Science.gov (United States)

Phan, Thomas; Li, Wen-Syan

Cloud computing looks to deliver software as a provisioned service to end users, but the underlying infrastructure must be sufficiently scalable and robust. In our work, we focus on large-scale enterprise cloud systems and examine how enterprises may use a service-oriented architecture (SOA) to provide a streamlined interface to their business processes. To scale up the business processes, each SOA tier usually deploys multiple servers for load distribution and fault tolerance, a scenario which we term horizontal load distribution. One limitation of this approach is that load cannot be distributed further when all servers in the same tier are loaded. In complex multi-tiered SOA systems, a single business process may actually be implemented by multiple different computation pathways among the tiers, each with different components, in order to provide resilience and scalability. Such multiple implementation options gives opportunities for vertical load distribution across tiers. In this chapter, we look at a novel request routing framework for SOA-based enterprise computing with multiple implementation options that takes into account the options of both horizontal and vertical load distribution.

Architecture and Initial Development of a Digital Library Platform for Computable Knowledge Objects for Health.

Science.gov (United States)

Flynn, Allen J; Bahulekar, Namita; Boisvert, Peter; Lagoze, Carl; Meng, George; Rampton, James; Friedman, Charles P

2017-01-01

Throughout the world, biomedical knowledge is routinely generated and shared through primary and secondary scientific publications. However, there is too much latency between publication of knowledge and its routine use in practice. To address this latency, what is actionable in scientific publications can be encoded to make it computable. We have created a purpose-built digital library platform to hold, manage, and share actionable, computable knowledge for health called the Knowledge Grid Library. Here we present it with its system architecture.

Temperature, salinity, nutrients, and meteorological data collected from 1926 to 1991 aboard multiple platforms in Caspian Sea (NODC Accession 0072200)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — NODC Accession 0072200 contains temperature, salinity, nutrients, and meteorological data collected from 1926 to 1991 aboard multiple platforms in Caspian Sea.

Can Nuclear Installations and Research Centres Adopt Cloud Computing Platform-

International Nuclear Information System (INIS)

Pichan, A.; Lazarescu, M.; Soh, S.T.

2015-01-01

Cloud Computing is arguably one of the recent and highly significant advances in information technology today. It produces transformative changes in the history of computing and presents many promising technological and economic opportunities. The pay-per-use model, the computing power, abundance of storage, skilled resources, fault tolerance and the economy of scale it offers, provides significant advantages to enterprises to adopt cloud platform for their business needs. However, customers especially those dealing with national security, high end scientific research institutions, critical national infrastructure service providers (like power, water) remain very much reluctant to move their business system to the cloud. One of the main concerns is the question of information security in the cloud and the threat of the unknown. Cloud Service Providers (CSP) indirectly encourages this perception by not letting their customers see what is behind their virtual curtain. Jurisdiction (information assets being stored elsewhere), data duplication, multi-tenancy, virtualisation and decentralized nature of data processing are the default characteristics of cloud computing. Therefore traditional approach of enforcing and implementing security controls remains a big challenge and largely depends upon the service provider. The other biggest challenge and open issue is the ability to perform digital forensic investigations in the cloud in case of security breaches. Traditional approaches to evidence collection and recovery are no longer practical as they rely on unrestricted access to the relevant systems and user data, something that is not available in the cloud model. This continues to fuel high insecurity for the cloud customers. In this paper we analyze the cyber security and digital forensics challenges, issues and opportunities for nuclear facilities to adopt cloud computing. We also discuss the due diligence process and applicable industry best practices which shall be

Windows Azure Platform

CERN Document Server

Redkar, Tejaswi

2011-01-01

The Windows Azure Platform has rapidly established itself as one of the most sophisticated cloud computing platforms available. With Microsoft working to continually update their product and keep it at the cutting edge, the future looks bright - if you have the skills to harness it. In particular, new features such as remote desktop access, dynamic content caching and secure content delivery using SSL make the latest version of Azure a more powerful solution than ever before. It's widely agreed that cloud computing has produced a paradigm shift in traditional architectural concepts by providin

HySDeP: a computational platform for on-board hydrogen storage systems – hybrid high-pressure solid-state and gaseous storage

DEFF Research Database (Denmark)

Mazzucco, Andrea; Rokni, Masoud

2016-01-01

A computational platform is developed in the Modelica® language within the DymolaTM environment to provide a tool for the design and performance comparison of on-board hydrogen storage systems. The platform has been coupled with an open source library for hydrogen fueling stations to investigate...

A platform independent communication library for distributed computing

NARCIS (Netherlands)

Groen, D.; Rieder, S.; Grosso, P.; de Laat, C.; Portegies Zwart, S.

2010-01-01

We present MPWide, a platform independent communication library for performing message passing between supercomputers. Our library couples several local MPI applications through a long distance network using, for example, optical links. The implementation is deliberately kept light-weight, platform

Software platform virtualization in chemistry research and university teaching.

Science.gov (United States)

Kind, Tobias; Leamy, Tim; Leary, Julie A; Fiehn, Oliver

2009-11-16

Modern chemistry laboratories operate with a wide range of software applications under different operating systems, such as Windows, LINUX or Mac OS X. Instead of installing software on different computers it is possible to install those applications on a single computer using Virtual Machine software. Software platform virtualization allows a single guest operating system to execute multiple other operating systems on the same computer. We apply and discuss the use of virtual machines in chemistry research and teaching laboratories. Virtual machines are commonly used for cheminformatics software development and testing. Benchmarking multiple chemistry software packages we have confirmed that the computational speed penalty for using virtual machines is low and around 5% to 10%. Software virtualization in a teaching environment allows faster deployment and easy use of commercial and open source software in hands-on computer teaching labs. Software virtualization in chemistry, mass spectrometry and cheminformatics is needed for software testing and development of software for different operating systems. In order to obtain maximum performance the virtualization software should be multi-core enabled and allow the use of multiprocessor configurations in the virtual machine environment. Server consolidation, by running multiple tasks and operating systems on a single physical machine, can lead to lower maintenance and hardware costs especially in small research labs. The use of virtual machines can prevent software virus infections and security breaches when used as a sandbox system for internet access and software testing. Complex software setups can be created with virtual machines and are easily deployed later to multiple computers for hands-on teaching classes. We discuss the popularity of bioinformatics compared to cheminformatics as well as the missing cheminformatics education at universities worldwide.

A Comparative Study of Multiple Object Detection Using Haar-Like Feature Selection and Local Binary Patterns in Several Platforms

Directory of Open Access Journals (Sweden)

Souhail Guennouni

2015-01-01

Full Text Available Object detection has been attracting much interest due to the wide spectrum of applications that use it. It has been driven by an increasing processing power available in software and hardware platforms. In this work we present a developed application for multiple objects detection based on OpenCV libraries. The complexity-related aspects that were considered in the object detection using cascade classifier are described. Furthermore, we discuss the profiling and porting of the application into an embedded platform and compare the results with those obtained on traditional platforms. The proposed application deals with real-time systems implementation and the results give a metric able to select where the cases of object detection applications may be more complex and where it may be simpler.

Cross-Platform Technologies

Directory of Open Access Journals (Sweden)

Maria Cristina ENACHE

2017-04-01

Full Text Available Cross-platform - a concept becoming increasingly used in recent years especially in the development of mobile apps, but this consistently over time and in the development of conventional desktop applications. The notion of cross-platform software (multi-platform or platform-independent refers to a software application that can run on more than one operating system or computing architecture. Thus, a cross-platform application can operate independent of software or hardware platform on which it is execute. As a generic definition presents a wide range of meanings for purposes of this paper we individualize this definition as follows: we will reduce the horizon of meaning and we use functionally following definition: a cross-platform application is a software application that can run on more than one operating system (desktop or mobile identical or in a similar way.

Getting the Most from Distributed Resources With an Analytics Platform for ATLAS Computing Services

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00225336; The ATLAS collaboration; Gardner, Robert; Bryant, Lincoln

2016-01-01

To meet a sharply increasing demand for computing resources for LHC Run 2, ATLAS distributed computing systems reach far and wide to gather CPU resources and storage capacity to execute an evolving ecosystem of production and analysis workflow tools. Indeed more than a hundred computing sites from the Worldwide LHC Computing Grid, plus many “opportunistic” facilities at HPC centers, universities, national laboratories, and public clouds, combine to meet these requirements. These resources have characteristics (such as local queuing availability, proximity to data sources and target destinations, network latency and bandwidth capacity, etc.) affecting the overall processing efficiency and throughput. To quantitatively understand and in some instances predict behavior, we have developed a platform to aggregate, index (for user queries), and analyze the more important information streams affecting performance. These data streams come from the ATLAS production system (PanDA), the distributed data management s...

Computer code MLCOSP for multiple-correlation and spectrum analysis with a hybrid computer

International Nuclear Information System (INIS)

Oguma, Ritsuo; Fujii, Yoshio; Usui, Hozumi; Watanabe, Koichi

1975-10-01

Usage of the computer code MLCOSP(Multiple Correlation and Spectrum) developed is described for a hybrid computer installed in JAERI Functions of the hybrid computer and its terminal devices are utilized ingeniously in the code to reduce complexity of the data handling which occurrs in analysis of the multivariable experimental data and to perform the analysis in perspective. Features of the code are as follows; Experimental data can be fed to the digital computer through the analog part of the hybrid computer by connecting with a data recorder. The computed results are displayed in figures, and hardcopies are taken when necessary. Series-messages to the code are shown on the terminal, so man-machine communication is possible. And further the data can be put in through a keyboard, so case study according to the results of analysis is possible. (auth.)

Platform for Distributed 3D Gaming

Directory of Open Access Journals (Sweden)

A. Jurgelionis

2009-01-01

Full Text Available Video games are typically executed on Windows platforms with DirectX API and require high performance CPUs and graphics hardware. For pervasive gaming in various environments like at home, hotels, or internet cafes, it is beneficial to run games also on mobile devices and modest performance CE devices avoiding the necessity of placing a noisy workstation in the living room or costly computers/consoles in each room of a hotel. This paper presents a new cross-platform approach for distributed 3D gaming in wired/wireless local networks. We introduce the novel system architecture and protocols used to transfer the game graphics data across the network to end devices. Simultaneous execution of video games on a central server and a novel streaming approach of the 3D graphics output to multiple end devices enable the access of games on low cost set top boxes and handheld devices that natively lack the power of executing a game with high-quality graphical output.

A computational platform for modeling and simulation of pipeline georeferencing systems

Energy Technology Data Exchange (ETDEWEB)

Guimaraes, A.G.; Pellanda, P.C.; Gois, J.A. [Instituto Militar de Engenharia (IME), Rio de Janeiro, RJ (Brazil); Roquette, P.; Pinto, M.; Durao, R. [Instituto de Pesquisas da Marinha (IPqM), Rio de Janeiro, RJ (Brazil); Silva, M.S.V.; Martins, W.F.; Camillo, L.M.; Sacsa, R.P.; Madeira, B. [Ministerio de Ciencia e Tecnologia (CT-PETRO2006MCT), Brasilia, DF (Brazil). Financiadora de Estudos e Projetos (FINEP). Plano Nacional de Ciencia e Tecnologia do Setor Petroleo e Gas Natural

2009-07-01

This work presents a computational platform for modeling and simulation of pipeline geo referencing systems, which was developed based on typical pipeline characteristics, on the dynamical modeling of Pipeline Inspection Gauge (PIG) and on the analysis and implementation of an inertial navigation algorithm. The software environment of PIG trajectory simulation and navigation allows the user, through a friendly interface, to carry-out evaluation tests of the inertial navigation system under different scenarios. Therefore, it is possible to define the required specifications of the pipeline geo referencing system components, such as: required precision of inertial sensors, characteristics of the navigation auxiliary system (GPS surveyed control points, odometers etc.), pipeline construction information to be considered in order to improve the trajectory estimation precision, and the signal processing techniques more suitable for the treatment of inertial sensors data. The simulation results are analyzed through the evaluation of several performance metrics usually considered in inertial navigation applications, and 2D and 3D plots of trajectory estimation error and of recovered trajectory in the three coordinates are made available to the user. This paper presents the simulation platform and its constituting modules and defines their functional characteristics and interrelationships.(author)

gLibrary/DRI: A grid-based platform to host multiple repositories for digital content

International Nuclear Information System (INIS)

Calanducci, A.; Gonzalez Martin, J. M.; Ramos Pollan, R.; Rubio del Solar, M.; Tcaci, S.

2007-01-01

In this work we present the gLibrary/DRI (Digital Repositories Infrastructure) platform. gLibrary/DRI extends gLibrary, a system with a easy-to-use web front-end designed to save and organize multimedia assets on Grid-based storage resources. The main goal of the extended platform is to reduce the cost in terms of time and effort that a repository provider spends to get its repository deployed. This is achieved by providing a common infrastructure and a set of mechanisms (APIs and specifications) that the repository providers use to define the data model, the access to the content (by navigation trees and filters) and the storage model. DRI offers a generic way to provide all this functionality; nevertheless the providers can add specific behaviours to the default functions for their repositories. The architecture is Grid based (VO system, data federation and distribution, computing power, etc). A working example based on a mammograms repository is also presented. (Author)

NiftyNet: a deep-learning platform for medical imaging.

Science.gov (United States)

Gibson, Eli; Li, Wenqi; Sudre, Carole; Fidon, Lucas; Shakir, Dzhoshkun I; Wang, Guotai; Eaton-Rosen, Zach; Gray, Robert; Doel, Tom; Hu, Yipeng; Whyntie, Tom; Nachev, Parashkev; Modat, Marc; Barratt, Dean C; Ourselin, Sébastien; Cardoso, M Jorge; Vercauteren, Tom

2018-05-01

Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this domain of application requires substantial implementation effort. Consequently, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups. This work presents the open-source NiftyNet platform for deep learning in medical imaging. The ambition of NiftyNet is to accelerate and simplify the development of these solutions, and to provide a common mechanism for disseminating research outputs for the community to use, adapt and build upon. The NiftyNet infrastructure provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications. Components of the NiftyNet pipeline including data loading, data augmentation, network architectures, loss functions and evaluation metrics are tailored to, and take advantage of, the idiosyncracies of medical image analysis and computer-assisted intervention. NiftyNet is built on the TensorFlow framework and supports features such as TensorBoard visualization of 2D and 3D images and computational graphs by default. We present three illustrative medical image analysis applications built using NiftyNet infrastructure: (1) segmentation of multiple abdominal organs from computed tomography; (2) image regression to predict computed tomography attenuation maps from brain magnetic resonance images; and (3) generation of simulated ultrasound images for specified anatomical poses. The NiftyNet infrastructure enables researchers to rapidly develop and distribute deep learning solutions for segmentation, regression, image generation and representation learning applications, or extend the platform to new

An update on MS Nurse PROfessional, an ongoing project of the European Multiple Sclerosis Platform.

Science.gov (United States)

Winslow, Anne

2016-12-01

Within the multidisciplinary team required to manage people with multiple sclerosis (MS) effectively, the nurse is the central component of coordinated care and support. A 2009 survey led by the European Multiple Sclerosis Platform, an umbrella organization of national MS associations, identified variance and disparity across Europe in the nursing care of MS patients. This led to development of MS Nurse PROfessional, a continuing medical education-accredited modular online learning program endorsed and approved by leading international nursing and professional groups, and people with MS, as a tool to support the evolving role of the European MS nurse. Analysis of participant experience and nurse practice to date has been overwhelmingly positive. Expansion of MS Nurse PRO is underway or planned for future.

A Test Platform for Planned Field Operations Using LEGO Mindstorms NXT

Directory of Open Access Journals (Sweden)

Gareth Edwards

2013-11-01

Full Text Available Testing agricultural operations and management practices associated with different machinery, systems and planning approaches can be both costly and time-consuming. Computer simulations of such systems are used for development and testing; however, to gain the experience of real-world performance, an intermediate step between simulation and full-scale testing should be included. In this paper, a potential common framework using the LEGO Mindstorms NXT micro-tractor platform is described in terms of its hardware and software components. The performance of the platform is demonstrated and tested in terms of its capability of supporting decision making on infield operation planning. The proposed system represents the basic measures for developing a complete test platform for field operations, where route plans, mission plans, multiple-machinery cooperation strategies and machinery coordination can be executed and tested in the laboratory.

Wireless sensor platform

Science.gov (United States)

Joshi, Pooran C.; Killough, Stephen M.; Kuruganti, Phani Teja

2017-08-08

A wireless sensor platform and methods of manufacture are provided. The platform involves providing a plurality of wireless sensors, where each of the sensors is fabricated on flexible substrates using printing techniques and low temperature curing. Each of the sensors can include planar sensor elements and planar antennas defined using the printing and curing. Further, each of the sensors can include a communications system configured to encode the data from the sensors into a spread spectrum code sequence that is transmitted to a central computer(s) for use in monitoring an area associated with the sensors.

Development of a cloud-based Bioinformatics Training Platform.

Science.gov (United States)

Revote, Jerico; Watson-Haigh, Nathan S; Quenette, Steve; Bethwaite, Blair; McGrath, Annette; Shang, Catherine A

2017-05-01

The Bioinformatics Training Platform (BTP) has been developed to provide access to the computational infrastructure required to deliver sophisticated hands-on bioinformatics training courses. The BTP is a cloud-based solution that is in active use for delivering next-generation sequencing training to Australian researchers at geographically dispersed locations. The BTP was built to provide an easy, accessible, consistent and cost-effective approach to delivering workshops at host universities and organizations with a high demand for bioinformatics training but lacking the dedicated bioinformatics training suites required. To support broad uptake of the BTP, the platform has been made compatible with multiple cloud infrastructures. The BTP is an open-source and open-access resource. To date, 20 training workshops have been delivered to over 700 trainees at over 10 venues across Australia using the BTP. © The Author 2016. Published by Oxford University Press.

CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing.

Science.gov (United States)

Angiuoli, Samuel V; Matalka, Malcolm; Gussman, Aaron; Galens, Kevin; Vangala, Mahesh; Riley, David R; Arze, Cesar; White, James R; White, Owen; Fricke, W Florian

2011-08-30

Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.

Contribution to global computation infrastructure: inter-platform delegation, integration of standard services and application to high-energy physics

International Nuclear Information System (INIS)

Lodygensky, Oleg

2006-01-01

The generalization and implementation of the current information resources, particularly the large storing capacities and the networks allow conceiving new methods of work and ways of entertainment. Centralized stand-alone, monolithic computing stations have been gradually replaced by distributed client-tailored architectures which in turn are challenged by the new distributed systems called 'pair-by pair' systems. This migration is no longer with the specialists' realm but users of more modest skills get used with this new techniques for e-mailing commercial information and exchanging various sorts of files on a 'equal-to-equal' basis. Trade, industry and research as well make profits largely of the new technique called 'grid', this new technique of handling information at a global scale. The present work concerns the grid utilisation for computation. A synergy was created with Paris-Sud University at Orsay, between the Information Research Laboratory (LRI) and the Linear Accelerator Laboratory (LAL) in order to foster the works on grid infrastructure of high research interest for LRI and offering new working methods for LAL. The results of the work developed within this inter-disciplinary-collaboration are based on XtremWeb, the research and production platform for global computation elaborated at LRI. First one presents the current status of the large-scale distributed systems, their basic principles and user-oriented architecture. The XtremWeb is then described focusing the modifications which were effected upon both architecture and implementation in order to fulfill optimally the requirements imposed to such a platform. Then one presents studies with the platform allowing a generalization of the inter-grid resources and development of a user-oriented grid adapted to special services, as well,. Finally one presents the operation modes, the problems to solve and the advantages of this new platform for the high-energy research community, the most demanding

Assembly procedure for Shot Loading Platform

International Nuclear Information System (INIS)

Routh, R.D.

1995-01-01

This supporting document describes the assembly procedure for the Shot Loading Platform. The Shot Loading Platform is used by multiple equipment removal projects to load shielding shot in the annular spaces of the equipment storage containers. The platform height is adjustable to accommodate different sizes of storage containers and transport assemblies

Teacher regulation of multiple computer-supported collaborating groups

NARCIS (Netherlands)

Van Leeuwen, Anouschka; Janssen, Jeroen; Erkens, Gijsbert; Brekelmans, Mieke

2015-01-01

Teachers regulating groups of students during computer-supported collaborative learning (CSCL) face the challenge of orchestrating their guidance at student, group, and class level. During CSCL, teachers can monitor all student activity and interact with multiple groups at the same time. Not much is

Neuroethologic differences in sleep deprivation induced by the single- and multiple-platform methods

Directory of Open Access Journals (Sweden)

R. Medeiros

1998-05-01

Full Text Available It has been proposed that the multiple-platform method (MP for desynchronized sleep (DS deprivation eliminates the stress induced by social isolation and by the restriction of locomotion in the single-platform (SP method. MP, however, induces a higher increase in plasma corticosterone and ACTH levels than SP. Since deprivation is of heuristic value to identify the functional role of this state of sleep, the objective of the present study was to determine the behavioral differences exhibited by rats during sleep deprivation induced by these two methods. All behavioral patterns exhibited by a group of 7 albino male Wistar rats submitted to 4 days of sleep deprivation by the MP method (15 platforms, spaced 150 mm apart and by 7 other rats submitted to sleep deprivation by the SP method were recorded in order to elaborate an ethogram. The behavioral patterns were quantitated in 10 replications by naive observers using other groups of 7 rats each submitted to the same deprivation schedule. Each quantification session lasted 35 min and the behavioral patterns presented by each rat over a period of 5 min were counted. The results obtained were: a rats submitted to the MP method changed platforms at a mean rate of 2.62 ± 1.17 platforms h-1 animal-1; b the number of episodes of noninteractive waking patterns for the MP animals was significantly higher than that for SP animals (1077 vs 768; c additional episodes of waking patterns (26.9 ± 18.9 episodes/session were promoted by social interaction in MP animals; d the cumulative number of sleep episodes observed in the MP test (311 was significantly lower (chi-square test, 1 d.f., P<0.05 than that observed in the SP test (534; e rats submitted to the MP test did not show the well-known increase in ambulatory activity observed after the end of the SP test; f comparison of 6 MP and 6 SP rats showed a significantly shorter latency to the onset of DS in MP rats (7.8 ± 4.3 and 29.0 ± 25.0 min, respectively

VibroCV: a computer vision-based vibroarthrography platform with possible application to Juvenile Idiopathic Arthritis.

Science.gov (United States)

Wiens, Andrew D; Prahalad, Sampath; Inan, Omer T

2016-08-01

Vibroarthrography, a method for interpreting the sounds emitted by a knee during movement, has been studied for several joint disorders since 1902. However, to our knowledge, the usefulness of this method for management of Juvenile Idiopathic Arthritis (JIA) has not been investigated. To study joint sounds as a possible new biomarker for pediatric cases of JIA we designed and built VibroCV, a platform to capture vibroarthrograms from four accelerometers; electromyograms (EMG) and inertial measurements from four wireless EMG modules; and joint angles from two Sony Eye cameras and six light-emitting diodes with commercially-available off-the-shelf parts and computer vision via OpenCV. This article explains the design of this turn-key platform in detail, and provides a sample recording captured from a pediatric subject.

Mapping flow distortion on oceanographic platforms using computational fluid dynamics

Directory of Open Access Journals (Sweden)

N. O'Sullivan

2013-10-01

Full Text Available Wind speed measurements over the ocean on ships or buoys are affected by flow distortion from the platform and by the anemometer itself. This can lead to errors in direct measurements and the derived parametrisations. Here we computational fluid dynamics (CFD to simulate the errors in wind speed measurements caused by flow distortion on the RV Celtic Explorer. Numerical measurements were obtained from the finite-volume CFD code OpenFOAM, which was used to simulate the velocity fields. This was done over a range of orientations in the test domain from −60 to +60° in increments of 10°. The simulation was also set up for a range of velocities, ranging from 5 to 25 m s−1 in increments of 0.5 m s−1. The numerical analysis showed close agreement to experimental measurements.

Parallel application of plasma equilibrium fitting based on inhomogeneous platforms

International Nuclear Information System (INIS)

Liao Min; Zhang Jinhua; Chen Liaoyuan; Li Yongge; Pan Wei; Pan Li

2008-01-01

An online analysis and online display platform EFIT, which is based on the equilibrium-fitting mode, is inducted in this paper. This application can realize large data transportation between inhomogeneous platforms by designing a communication mechanism using sockets. It spends approximately one minute to complete the equilibrium fitting reconstruction by using a finite state machine to describe the management node and several node computers of cluster system to fulfill the parallel computation, this satisfies the online display during the discharge interval. An effective communication model between inhomogeneous platforms is provided, which could transport the computing results from Linux platform to Windows platform for online analysis and display. (authors)

Semiempirical Quantum Chemical Calculations Accelerated on a Hybrid Multicore CPU-GPU Computing Platform.

Science.gov (United States)

Wu, Xin; Koslowski, Axel; Thiel, Walter

2012-07-10

In this work, we demonstrate that semiempirical quantum chemical calculations can be accelerated significantly by leveraging the graphics processing unit (GPU) as a coprocessor on a hybrid multicore CPU-GPU computing platform. Semiempirical calculations using the MNDO, AM1, PM3, OM1, OM2, and OM3 model Hamiltonians were systematically profiled for three types of test systems (fullerenes, water clusters, and solvated crambin) to identify the most time-consuming sections of the code. The corresponding routines were ported to the GPU and optimized employing both existing library functions and a GPU kernel that carries out a sequence of noniterative Jacobi transformations during pseudodiagonalization. The overall computation times for single-point energy calculations and geometry optimizations of large molecules were reduced by one order of magnitude for all methods, as compared to runs on a single CPU core.

Building an organic computing device with multiple interconnected brains

OpenAIRE

Pais-Vieira, Miguel; Chiuffa, Gabriela; Lebedev, Mikhail; Yadav, Amol; Nicolelis, Miguel A. L.

2015-01-01

Recently, we proposed that Brainets, i.e. networks formed by multiple animal brains, cooperating and exchanging information in real time through direct brain-to-brain interfaces, could provide the core of a new type of computing device: an organic computer. Here, we describe the first experimental demonstration of such a Brainet, built by interconnecting four adult rat brains. Brainets worked by concurrently recording the extracellular electrical activity generated by populations of cortical ...

Making Spatial Statistics Service Accessible On Cloud Platform

OpenAIRE

Mu, X.; Wu, J.; Li, T; Zhong, Y.; Gao, X.

2014-01-01

Web service can bring together applications running on diverse platforms, users can access and share various data, information and models more effectively and conveniently from certain web service platform. Cloud computing emerges as a paradigm of Internet computing in which dynamical, scalable and often virtualized resources are provided as services. With the rampant growth of massive data and restriction of net, traditional web services platforms have some prominent problems existi...

An evolving computational platform for biological mass spectrometry: workflows, statistics and data mining with MASSyPup64.

Science.gov (United States)

Winkler, Robert

2015-01-01

In biological mass spectrometry, crude instrumental data need to be converted into meaningful theoretical models. Several data processing and data evaluation steps are required to come to the final results. These operations are often difficult to reproduce, because of too specific computing platforms. This effect, known as 'workflow decay', can be diminished by using a standardized informatic infrastructure. Thus, we compiled an integrated platform, which contains ready-to-use tools and workflows for mass spectrometry data analysis. Apart from general unit operations, such as peak picking and identification of proteins and metabolites, we put a strong emphasis on the statistical validation of results and Data Mining. MASSyPup64 includes e.g., the OpenMS/TOPPAS framework, the Trans-Proteomic-Pipeline programs, the ProteoWizard tools, X!Tandem, Comet and SpiderMass. The statistical computing language R is installed with packages for MS data analyses, such as XCMS/metaXCMS and MetabR. The R package Rattle provides a user-friendly access to multiple Data Mining methods. Further, we added the non-conventional spreadsheet program teapot for editing large data sets and a command line tool for transposing large matrices. Individual programs, console commands and modules can be integrated using the Workflow Management System (WMS) taverna. We explain the useful combination of the tools by practical examples: (1) A workflow for protein identification and validation, with subsequent Association Analysis of peptides, (2) Cluster analysis and Data Mining in targeted Metabolomics, and (3) Raw data processing, Data Mining and identification of metabolites in untargeted Metabolomics. Association Analyses reveal relationships between variables across different sample sets. We present its application for finding co-occurring peptides, which can be used for target proteomics, the discovery of alternative biomarkers and protein-protein interactions. Data Mining derived models

Multiple network alignment on quantum computers

Science.gov (United States)

Daskin, Anmer; Grama, Ananth; Kais, Sabre

2014-12-01

Comparative analyses of graph-structured datasets underly diverse problems. Examples of these problems include identification of conserved functional components (biochemical interactions) across species, structural similarity of large biomolecules, and recurring patterns of interactions in social networks. A large class of such analyses methods quantify the topological similarity of nodes across networks. The resulting correspondence of nodes across networks, also called node alignment, can be used to identify invariant subgraphs across the input graphs. Given graphs as input, alignment algorithms use topological information to assign a similarity score to each -tuple of nodes, with elements (nodes) drawn from each of the input graphs. Nodes are considered similar if their neighbors are also similar. An alternate, equivalent view of these network alignment algorithms is to consider the Kronecker product of the input graphs and to identify high-ranked nodes in the Kronecker product graph. Conventional methods such as PageRank and HITS (Hypertext-Induced Topic Selection) can be used for this purpose. These methods typically require computation of the principal eigenvector of a suitably modified Kronecker product matrix of the input graphs. We adopt this alternate view of the problem to address the problem of multiple network alignment. Using the phase estimation algorithm, we show that the multiple network alignment problem can be efficiently solved on quantum computers. We characterize the accuracy and performance of our method and show that it can deliver exponential speedups over conventional (non-quantum) methods.

CloVR: A virtual machine for automated and portable sequence analysis from the desktop using cloud computing

Science.gov (United States)

2011-01-01

Background Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. Results We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. Conclusion The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing. PMID:21878105

Morphological indicators of growth stages in carbonates platform evolution: comparison between present-day and Miocene platforms of Northern Borneo, Malaysia.

Science.gov (United States)

Pierson, B.; Menier, D.; Ting, K. K.; Chalabi, A.

2012-04-01

Satellite images of present-day reefs and carbonate platforms of the Celebes Sea, east of Sabah, Malaysia, exhibit large-scale features indicative of the recent evolution of the platforms. These include: (1) multiple, sub-parallel reef rims at the windward margin, suggestive of back-stepping of the platform margin; (2) contraction of the platform, possibly as a result of recent sea level fluctuations; (3) colonization of the internal lagoons by polygonal reef structures and (4) fragmentation of the platforms and creation of deep channels separating platforms that used to be part of a single entity. These features are analogue to what has been observed on seismic attribute maps of Miocene carbonate platforms of Sarawak. An analysis of several growth stages of a large Miocene platform, referred to as the Megaplatform, shows that the platform evolves in function of syn-depositional tectonic movements and sea level fluctuations that result in back-stepping of the margin, illustrated by multiple reef rims, contraction of the platform, the development of polygonal structures currently interpreted as karstic in origin and fragmentation of the megaplatform in 3 sub-entities separated by deep channels that precedes the final demise of the whole platform. Comparing similar features on present-day to platforms and Miocene platforms leads to a better understanding of the growth history of Miocene platforms and to a refined predictability of reservoir and non-reservoir facies distribution.

Oceanographic profile temperature, salinity, oxygen measurements collected using bottle from multiple platforms in the Azov, Black Seas from 1924-1990 (NODC Accession 0002717)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Oceanographic profile temperature, salinity, oxygen measurements collected using bottle from multiple platforms in the Azov, Black Seas from 1924-1990

Hierarchical DSE for multi-ASIP platforms

DEFF Research Database (Denmark)

Micconi, Laura; Corvino, Rosilde; Gangadharan, Deepak

2013-01-01

This work proposes a hierarchical Design Space Exploration (DSE) for the design of multi-processor platforms targeted to specific applications with strict timing and area constraints. In particular, it considers platforms integrating multiple Application Specific Instruction Set Processors (ASIPs...

Computing all hybridization networks for multiple binary phylogenetic input trees.

Science.gov (United States)

Albrecht, Benjamin

2015-07-30

The computation of phylogenetic trees on the same set of species that are based on different orthologous genes can lead to incongruent trees. One possible explanation for this behavior are interspecific hybridization events recombining genes of different species. An important approach to analyze such events is the computation of hybridization networks. This work presents the first algorithm computing the hybridization number as well as a set of representative hybridization networks for multiple binary phylogenetic input trees on the same set of taxa. To improve its practical runtime, we show how this algorithm can be parallelized. Moreover, we demonstrate the efficiency of the software Hybroscale, containing an implementation of our algorithm, by comparing it to PIRNv2.0, which is so far the best available software computing the exact hybridization number for multiple binary phylogenetic trees on the same set of taxa. The algorithm is part of the software Hybroscale, which was developed specifically for the investigation of hybridization networks including their computation and visualization. Hybroscale is freely available(1) and runs on all three major operating systems. Our simulation study indicates that our approach is on average 100 times faster than PIRNv2.0. Moreover, we show how Hybroscale improves the interpretation of the reported hybridization networks by adding certain features to its graphical representation.

Evaluation of Network Reliability for Computer Networks with Multiple Sources

Directory of Open Access Journals (Sweden)

Yi-Kuei Lin

2012-01-01

Full Text Available Evaluating the reliability of a network with multiple sources to multiple sinks is a critical issue from the perspective of quality management. Due to the unrealistic definition of paths of network models in previous literature, existing models are not appropriate for real-world computer networks such as the Taiwan Advanced Research and Education Network (TWAREN. This paper proposes a modified stochastic-flow network model to evaluate the network reliability of a practical computer network with multiple sources where data is transmitted through several light paths (LPs. Network reliability is defined as being the probability of delivering a specified amount of data from the sources to the sink. It is taken as a performance index to measure the service level of TWAREN. This paper studies the network reliability of the international portion of TWAREN from two sources (Taipei and Hsinchu to one sink (New York that goes through a submarine and land surface cable between Taiwan and the United States.

Performance modeling and optimization of sparse matrix-vector multiplication on NVIDIA CUDA platform

NARCIS (Netherlands)

Xu, S.; Xue, W.; Lin, H.X.

2011-01-01

In this article, we discuss the performance modeling and optimization of Sparse Matrix-Vector Multiplication (SpMV) on NVIDIA GPUs using CUDA. SpMV has a very low computation-data ratio and its performance is mainly bound by the memory bandwidth. We propose optimization of SpMV based on ELLPACK from

Los Alamos radiation transport code system on desktop computing platforms

International Nuclear Information System (INIS)

Briesmeister, J.F.; Brinkley, F.W.; Clark, B.A.; West, J.T.

1990-01-01

The Los Alamos Radiation Transport Code System (LARTCS) consists of state-of-the-art Monte Carlo and discrete ordinates transport codes and data libraries. These codes were originally developed many years ago and have undergone continual improvement. With a large initial effort and continued vigilance, the codes are easily portable from one type of hardware to another. The performance of scientific work-stations (SWS) has evolved to the point that such platforms can be used routinely to perform sophisticated radiation transport calculations. As the personal computer (PC) performance approaches that of the SWS, the hardware options for desk-top radiation transport calculations expands considerably. The current status of the radiation transport codes within the LARTCS is described: MCNP, SABRINA, LAHET, ONEDANT, TWODANT, TWOHEX, and ONELD. Specifically, the authors discuss hardware systems on which the codes run and present code performance comparisons for various machines

Design and implementation of the modified signed digit multiplication routine on a ternary optical computer.

Science.gov (United States)

Xu, Qun; Wang, Xianchao; Xu, Chao

2017-06-01

Multiplication with traditional electronic computers is faced with a low calculating accuracy and a long computation time delay. To overcome these problems, the modified signed digit (MSD) multiplication routine is established based on the MSD system and the carry-free adder. Also, its parallel algorithm and optimization techniques are studied in detail. With the help of a ternary optical computer's characteristics, the structured data processor is designed especially for the multiplication routine. Several ternary optical operators are constructed to perform M transformations and summations in parallel, which has accelerated the iterative process of multiplication. In particular, the routine allocates data bits of the ternary optical processor based on digits of multiplication input, so the accuracy of the calculation results can always satisfy the users. Finally, the routine is verified by simulation experiments, and the results are in full compliance with the expectations. Compared with an electronic computer, the MSD multiplication routine is not only good at dealing with large-value data and high-precision arithmetic, but also maintains lower power consumption and fewer calculating delays.

Preparing for a Product Platform

DEFF Research Database (Denmark)

Fiil-Nielsen, Ole; Munk, Lone; Mortensen, Niels Henrik

2005-01-01

on commonalities and similarities in the product family, and variance should be based on customer demands. To relate these terms and to improve the basis on which decisions are made, we need a way of visualizing the hierarchy of the product family as well as the commonality and variance. This visualization method...... of the platform or ensuring that the platform can meet future demands will be very useful in the preparation process of a platform synthesis as well as in the updating or reengineering of an existing product development platform.......Experience in the industry as well as recent related scientific publications show the benefits of product development platforms. Companies use platforms to develop not a single but multiple products (i.e. a product family) simultaneously. When these product development projects are coordinated...

A computer program for determining multiplicities of powder reflexions

International Nuclear Information System (INIS)

Rouse, K.D.; Cooper, M.J.

1977-01-01

A computer program has been written which determines the multiplicity factors for a given set of X-ray or neutron powder diffraction reflexions for crystals of any space group. The value of the multiplicity for each reflexion is determined from a look-up table which is indexed by the symmetry type, determined directly from the space-group number, and the reflexion type, determined from the Miller indices. There are no restrictions on the choice of indices which are used to specify the reflexions. (Auth.)

A resilient and secure software platform and architecture for distributed spacecraft

Science.gov (United States)

Otte, William R.; Dubey, Abhishek; Karsai, Gabor

2014-06-01

A distributed spacecraft is a cluster of independent satellite modules flying in formation that communicate via ad-hoc wireless networks. This system in space is a cloud platform that facilitates sharing sensors and other computing and communication resources across multiple applications, potentially developed and maintained by different organizations. Effectively, such architecture can realize the functions of monolithic satellites at a reduced cost and with improved adaptivity and robustness. Openness of these architectures pose special challenges because the distributed software platform has to support applications from different security domains and organizations, and where information flows have to be carefully managed and compartmentalized. If the platform is used as a robust shared resource its management, configuration, and resilience becomes a challenge in itself. We have designed and prototyped a distributed software platform for such architectures. The core element of the platform is a new operating system whose services were designed to restrict access to the network and the file system, and to enforce resource management constraints for all non-privileged processes Mixed-criticality applications operating at different security labels are deployed and controlled by a privileged management process that is also pre-configuring all information flows. This paper describes the design and objective of this layer.

An integrated IaaS and PaaS architecture for scientific computing

OpenAIRE

Donvito, Giacinto; Blanquer, Ignacio

2015-01-01

Scientific applications often require multiple computing resources deployed on a coordinated way. The deployment of multiple resources require installing and configuring special software applications which should be updated when changes in the virtual infrastructure take place. When working on hybrid and federated cloud environments, restrictions on the hypervisor or cloud management platform must be minimised to facilitate geographic-wide brokering and cross-site deployments. Moreover, prese...

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.

A General Cross-Layer Cloud Scheduling Framework for Multiple IoT Computer Tasks.

Science.gov (United States)

Wu, Guanlin; Bao, Weidong; Zhu, Xiaomin; Zhang, Xiongtao

2018-05-23

The diversity of IoT services and applications brings enormous challenges to improving the performance of multiple computer tasks' scheduling in cross-layer cloud computing systems. Unfortunately, the commonly-employed frameworks fail to adapt to the new patterns on the cross-layer cloud. To solve this issue, we design a new computer task scheduling framework for multiple IoT services in cross-layer cloud computing systems. Specifically, we first analyze the features of the cross-layer cloud and computer tasks. Then, we design the scheduling framework based on the analysis and present detailed models to illustrate the procedures of using the framework. With the proposed framework, the IoT services deployed in cross-layer cloud computing systems can dynamically select suitable algorithms and use resources more effectively to finish computer tasks with different objectives. Finally, the algorithms are given based on the framework, and extensive experiments are also given to validate its effectiveness, as well as its superiority.

Performance of Cloud Computing Centers with Multiple Priority Classes

NARCIS (Netherlands)

Ellens, W.; Zivkovic, Miroslav; Akkerboom, J.; Litjens, R.; van den Berg, Hans Leo

In this paper we consider the general problem of resource provisioning within cloud computing. We analyze the problem of how to allocate resources to different clients such that the service level agreements (SLAs) for all of these clients are met. A model with multiple service request classes

MULGRES: a computer program for stepwise multiple regression analysis

Science.gov (United States)

A. Jeff Martin

1971-01-01

MULGRES is a computer program source deck that is designed for multiple regression analysis employing the technique of stepwise deletion in the search for most significant variables. The features of the program, along with inputs and outputs, are briefly described, with a note on machine compatibility.

Cloud Robotics Platforms

Directory of Open Access Journals (Sweden)

Busra Koken

2015-01-01

Full Text Available Cloud robotics is a rapidly evolving field that allows robots to offload computation-intensive and storage-intensive jobs into the cloud. Robots are limited in terms of computational capacity, memory and storage. Cloud provides unlimited computation power, memory, storage and especially collaboration opportunity. Cloud-enabled robots are divided into two categories as standalone and networked robots. This article surveys cloud robotic platforms, standalone and networked robotic works such as grasping, simultaneous localization and mapping (SLAM and monitoring.

Enabling IoT ecosystems through platform interoperability

OpenAIRE

Bröring, Arne; Schmid, Stefan; Schindhelm, Corina-Kim; Khelil, Abdelmajid; Kabisch, Sebastian; Kramer, Denis; Le Phuoc, Danh; Mitic, Jelena; Anicic, Darko; Teniente López, Ernest

2017-01-01

Today, the Internet of Things (IoT) comprises vertically oriented platforms for things. Developers who want to use them need to negotiate access individually and adapt to the platform-specific API and information models. Having to perform these actions for each platform often outweighs the possible gains from adapting applications to multiple platforms. This fragmentation of the IoT and the missing interoperability result in high entry barriers for developers and prevent the emergence of broa...

Complementors as Connectors: Open Innovation in Digital Product Platforms

NARCIS (Netherlands)

Hilbolling, Susan; Berends, Hans; Deken, F.; Tuertscher, Philipp

2018-01-01

Through open, standardized interfaces, autonomous third parties can develop complementary products and services for digital product platforms, but, at the same time, these third parties also establish connections that span multiple platforms - beyond the control of the platform owner. This paper

Distributed Processing of Sentinel-2 Products using the BIGEARTH Platform

Science.gov (United States)

Bacu, Victor; Stefanut, Teodor; Nandra, Constantin; Mihon, Danut; Gorgan, Dorian

2017-04-01

The constellation of observational satellites orbiting around Earth is constantly increasing, providing more data that need to be processed in order to extract meaningful information and knowledge from it. Sentinel-2 satellites, part of the Copernicus Earth Observation program, aim to be used in agriculture, forestry and many other land management applications. ESA's SNAP toolbox can be used to process data gathered by Sentinel-2 satellites but is limited to the resources provided by a stand-alone computer. In this paper we present a cloud based software platform that makes use of this toolbox together with other remote sensing software applications to process Sentinel-2 products. The BIGEARTH software platform [1] offers an integrated solution for processing Earth Observation data coming from different sources (such as satellites or on-site sensors). The flow of processing is defined as a chain of tasks based on the WorDeL description language [2]. Each task could rely on a different software technology (such as Grass GIS and ESA's SNAP) in order to process the input data. One important feature of the BIGEARTH platform comes from this possibility of interconnection and integration, throughout the same flow of processing, of the various well known software technologies. All this integration is transparent from the user perspective. The proposed platform extends the SNAP capabilities by enabling specialists to easily scale the processing over distributed architectures, according to their specific needs and resources. The software platform [3] can be used in multiple configurations. In the basic one the software platform runs as a standalone application inside a virtual machine. Obviously in this case the computational resources are limited but it will give an overview of the functionalities of the software platform, and also the possibility to define the flow of processing and later on to execute it on a more complex infrastructure. The most complex and robust

Arctic phytoplankton and zooplankton abundance, temperature and salinity measurements collected from multiple platforms from 1903-02-22 to 1970-09-30 (NODC Accession 0069178)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Arctic phytoplankton and zooplankton abundance, temperature and salinity measurements collected from multiple platforms from 1903-02-22 to 1970-09-30 by Zoological...

Vertical Wave Impacts on Offshore Wind Turbine Inspection Platforms

DEFF Research Database (Denmark)

Bredmose, Henrik; Jacobsen, Niels Gjøl

2011-01-01

Breaking wave impacts on a monopile at 20 m depth are computed with a VOF (Volume Of Fluid) method. The impacting waves are generated by the second-order focused wave group technique, to obtain waves that break at the position of the monopile. The subsequent impact from the vertical run-up flow...... on a horizontal inspection platform is computed for five different platform levels. The computational results show details of monopile impact such as slamming pressures from the overturning wave front and the formation of run-up flow. The results show that vertical platform impacts can occur at 20 m water depth....... The dependence of the vertical platform load to the platform level is discussed. Attention is given to the significant downward force that occur after the upward force associated with the vertical impact. The effect of the numerical resolution on the results is assessed. The position of wave overturning is found...

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

Science.gov (United States)

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2016-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

Cloud Based Applications and Platforms (Presentation)

Energy Technology Data Exchange (ETDEWEB)

Brodt-Giles, D.

2014-05-15

Presentation to the Cloud Computing East 2014 Conference, where we are highlighting our cloud computing strategy, describing the platforms on the cloud (including Smartgrid.gov), and defining our process for implementing cloud based applications.

Temperature profiles from MBT casts from a World-Wide distribution from MULTIPLE PLATFORMS from 1948-04-08 to 1968-12-14 (NODC Accession 9300131)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profile data were collected from MBT casts from a World-Wide distribution. Data were collected from MULTIPLE PLATFORMS from 08 April 1948 to 14 Decmeber...

Computer optimization of cutting yield from multiple ripped boards

Science.gov (United States)

A.R. Stern; K.A. McDonald

1978-01-01

RIPYLD is a computer program that optimizes the cutting yield from multiple-ripped boards. Decisions are based on automatically collected defect information, cutting bill requirements, and sawing variables. The yield of clear cuttings from a board is calculated for every possible permutation of specified rip widths and both the maximum and minimum percent yield...

Identification of platform levels

DEFF Research Database (Denmark)

Mortensen, Niels Henrik

2005-01-01

reduction, ability to launch a wider product portfolio without increasing resources and reduction of complexity within the whole company. To support the multiple product development process, platform based product development has in many companies such as Philips, VW, Ford etc. proven to be a very effective...... product development in one step and therefore the objective of this paper is to identify levels of platform based product development. The structure of this paper is as follows. First the applied terminology for platforms will be briefly explained and then characteristics between single and multi product...... development will be examined. Based on the identification of the above characteristics five platform levels are described. The research presented in this paper is a result of MSc, Ph.D projects at the Technical University of Denmark and consultancy projects within the organisation of Institute of Product...

Temperature profiles from XBT casts from a World-Wide distribution from MULTIPLE PLATFORMS from 1979-06-03 to 1988-05-27 (NODC Accession 8800182)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Temperature profiles were collected from XBT casts from a World-Wide distribution. Data were collected from MULTIPLE PLATFORMS from 03 June 1979 to 27 May 1988. Data...

Using e-Learning Platforms for Mastery Learning in Developmental Mathematics Courses

Science.gov (United States)

Boggs, Stacey; Shore, Mark; Shore, JoAnna

2004-01-01

Many colleges and universities have adopted e-learning platforms to utilize computers as an instructional tool in developmental (i.e., beginning and intermediate algebra) mathematics courses. An e-learning platform is a computer program used to enhance course instruction via computers and the Internet. Allegany College of Maryland is currently…

Power Allocation in Multiple Access Networks: Implementation Aspects via Verhulst and Perron-Frobenius Models

Directory of Open Access Journals (Sweden)

Fábio Engel de Camargo

2012-11-01

Full Text Available In this work, the Verhulst model and the Perron-Frobenius theorem are applied on the power control problem which is a concern in multiple access communication networks due to the multiple access interference. This paper deals with the performance versus complexity tradeoff of both power control algorithm (PCA, as well as highlights the computational cost aspects regarding the implementability of distributed PCA (DPCA version for both algorithms. As a proof-of-concept the DPCA implementation is carried out deploying a commercial point-floating DSP platform. Numerical results in terms of DSP cycles and computational time as well indicate a feasibility of implementing the PCA-Verhulst model in 2G and 3G cellular systems; b high computational cost for the PCA-Perron-Frobenius model.

Cloud@Home: A New Enhanced Computing Paradigm

Science.gov (United States)

Distefano, Salvatore; Cunsolo, Vincenzo D.; Puliafito, Antonio; Scarpa, Marco

Cloud computing is a distributed computing paradigm that mixes aspects of Grid computing, ("… hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities" (Foster, 2002)) Internet Computing ("…a computing platform geographically distributed across the Internet" (Milenkovic et al., 2003)), Utility computing ("a collection of technologies and business practices that enables computing to be delivered seamlessly and reliably across multiple computers, ... available as needed and billed according to usage, much like water and electricity are today" (Ross & Westerman, 2004)) Autonomic computing ("computing systems that can manage themselves given high-level objectives from administrators" (Kephart & Chess, 2003)), Edge computing ("… provides a generic template facility for any type of application to spread its execution across a dedicated grid, balancing the load …" Davis, Parikh, & Weihl, 2004) and Green computing (a new frontier of Ethical computing1 starting from the assumption that in next future energy costs will be related to the environment pollution).

An Efficient Neural-Network-Based Microseismic Monitoring Platform for Hydraulic Fracture on an Edge Computing Architecture

Directory of Open Access Journals (Sweden)

Xiaopu Zhang

2018-06-01

Full Text Available Microseismic monitoring is one of the most critical technologies for hydraulic fracturing in oil and gas production. To detect events in an accurate and efficient way, there are two major challenges. One challenge is how to achieve high accuracy due to a poor signal-to-noise ratio (SNR. The other one is concerned with real-time data transmission. Taking these challenges into consideration, an edge-computing-based platform, namely Edge-to-Center LearnReduce, is presented in this work. The platform consists of a data center with many edge components. At the data center, a neural network model combined with convolutional neural network (CNN and long short-term memory (LSTM is designed and this model is trained by using previously obtained data. Once the model is fully trained, it is sent to edge components for events detection and data reduction. At each edge component, a probabilistic inference is added to the neural network model to improve its accuracy. Finally, the reduced data is delivered to the data center. Based on experiment results, a high detection accuracy (over 96% with less transmitted data (about 90% was achieved by using the proposed approach on a microseismic monitoring system. These results show that the platform can simultaneously improve the accuracy and efficiency of microseismic monitoring.

An Efficient Neural-Network-Based Microseismic Monitoring Platform for Hydraulic Fracture on an Edge Computing Architecture.

Science.gov (United States)

Zhang, Xiaopu; Lin, Jun; Chen, Zubin; Sun, Feng; Zhu, Xi; Fang, Gengfa

2018-06-05

Microseismic monitoring is one of the most critical technologies for hydraulic fracturing in oil and gas production. To detect events in an accurate and efficient way, there are two major challenges. One challenge is how to achieve high accuracy due to a poor signal-to-noise ratio (SNR). The other one is concerned with real-time data transmission. Taking these challenges into consideration, an edge-computing-based platform, namely Edge-to-Center LearnReduce, is presented in this work. The platform consists of a data center with many edge components. At the data center, a neural network model combined with convolutional neural network (CNN) and long short-term memory (LSTM) is designed and this model is trained by using previously obtained data. Once the model is fully trained, it is sent to edge components for events detection and data reduction. At each edge component, a probabilistic inference is added to the neural network model to improve its accuracy. Finally, the reduced data is delivered to the data center. Based on experiment results, a high detection accuracy (over 96%) with less transmitted data (about 90%) was achieved by using the proposed approach on a microseismic monitoring system. These results show that the platform can simultaneously improve the accuracy and efficiency of microseismic monitoring.

Designing platform independent mobile apps and services

CERN Document Server

Heckman, Rocky

2016-01-01

This book explains how to help create an innovative and future proof architecture for mobile apps by introducing practical approaches to increase the value and flexibility of their service layers and reduce their delivery time. Designing Platform Independent Mobile Apps and Services begins by describing the mobile computing landscape and previous attempts at cross platform development. Platform independent mobile technologies and development strategies are described in chapter two and three. Communication protocols, details of a recommended five layer architecture, service layers, and the data abstraction layer are also introduced in these chapters. Cross platform languages and multi-client development tools for the User Interface (UI) layer, as well as message processing patterns and message routing of the Service Int rface (SI) layer are explained in chapter four and five. Ways to design the service layer for mobile computing, using Command Query Responsibility Segregation (CQRS) and the Data Abstraction La...

Evaluation of secure capability-based access control in the M2M local cloud platform

DEFF Research Database (Denmark)

Anggorojati, Bayu; Prasad, Neeli R.; Prasad, Ramjee

2016-01-01

delegation. Recently, the capability based access control has been considered as method to manage access in the Internet of Things (IoT) or M2M domain. In this paper, the implementation and evaluation of a proposed secure capability based access control in the M2M local cloud platform is presented......Managing access to and protecting resources is one of the important aspect in managing security, especially in a distributed computing system such as Machine-to-Machine (M2M). One such platform known as the M2M local cloud platform, referring to BETaaS architecture [1], which conceptually consists...... of multiple distributed M2M gateways, creating new challenges in the access control. Some existing access control systems lack in scalability and flexibility to manage access from users or entity that belong to different authorization domains, or fails to provide fine grained and flexible access right...

Evaluation of myocardial ischemia by multiple detector computed tomography

Energy Technology Data Exchange (ETDEWEB)

Fernandes, Fabio Vieira, E-mail: rccury@me.com [Hospital do Coracao (HCor), Sao Paulo, SP (Brazil); Cury, Roberto Caldeira [Hospital Samaritano, Sao Paulo, SP (Brazil)

2015-01-15

For years, cardiovascular diseases have been the leading cause of death worldwide, bringing on important social and economic consequences. Given this scenario, the search for a method capable of diagnosing coronary artery diseases in an early and accurate way is increasingly higher. The coronary computed tomography angiogram is already widely established for the stratification of coronary artery diseases, and, more recently, the computed tomography myocardial perfusion imaging has been providing relevant information by correlating ischemia and the coronary anatomy. The objective of this review is to describe the evaluation of myocardial ischemia by multiple detector computed tomography. This study will resort to controlled clinical trials that show the possibility of a single method to identify the atherosclerotic load, presence of coronary artery luminal narrowing and possible myocardial ischemia, by means of a fast, practical and reliable method validated by a multicenter study. (author)

Genomics With Cloud Computing

OpenAIRE

Sukhamrit Kaur; Sandeep Kaur

2015-01-01

Abstract Genomics is study of genome which provides large amount of data for which large storage and computation power is needed. These issues are solved by cloud computing that provides various cloud platforms for genomics. These platforms provides many services to user like easy access to data easy sharing and transfer providing storage in hundreds of terabytes more computational power. Some cloud platforms are Google genomics DNAnexus and Globus genomics. Various features of cloud computin...

A novel collaborative e-learning platform for medical students - ALERT STUDENT.

Science.gov (United States)

Taveira-Gomes, Tiago; Saffarzadeh, Areo; Severo, Milton; Guimarães, M Jorge; Ferreira, Maria Amélia

2014-07-14

The increasing complexity of medical curricula would benefit from adaptive computer supported collaborative learning systems that support study management using instructional design and learning object principles. However, to our knowledge, there are scarce reports regarding applications developed to meet this goal and encompass the complete medical curriculum. The aim of ths study was to develop and assess the usability of an adaptive computer supported collaborative learning system for medical students to manage study sessions. A study platform named ALERT STUDENT was built as a free web application. Content chunks are represented as Flashcards that hold knowledge and open ended questions. These can be created in a collaborative fashion. Multiple Flashcards can be combined into custom stacks called Notebooks that can be accessed in study Groups that belong to the user institution. The system provides a Study Mode that features text markers, text notes, timers and color-coded content prioritization based on self-assessment of open ended questions presented in a Quiz Mode. Time spent studying and Perception of knowledge are displayed for each student and peers using charts. Computer supported collaborative learning is achieved by allowing for simultaneous creation of Notebooks and self-assessment questions by many users in a pre-defined Group. Past personal performance data is retrieved when studying new Notebooks containing previously studied Flashcards. Self-report surveys showed that students highly agreed that the system was useful and were willing to use it as a reference tool. The platform employs various instructional design and learning object principles in a computer supported collaborative learning platform for medical students that allows for study management. The application broadens student insight over learning results and supports informed decisions based on past learning performance. It serves as a potential educational model for the medical

Efficient computation of the joint sample frequency spectra for multiple populations.

Science.gov (United States)

Kamm, John A; Terhorst, Jonathan; Song, Yun S

2017-01-01

A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity.

[Orange Platform].

Science.gov (United States)

Toba, Kenji

2017-07-01

The Organized Registration for the Assessment of dementia on Nationwide General consortium toward Effective treatment in Japan (ORANGE platform) is a recently established nationwide clinical registry for dementia. This platform consists of multiple registries of patients with dementia stratified by the following clinical stages: preclinical, mild cognitive impairment, early-stage, and advanced-stage dementia. Patients will be examined in a super-longitudinal fashion, and their lifestyle, social background, genetic risk factors, and required care process will be assessed. This project is also notable because the care registry includes information on the successful, comprehensive management of patients with dementia. Therefore, this multicenter prospective cohort study will contribute participants to all clinical trials for Alzheimer's disease as well as improve the understanding of individuals with dementia.

Windows Azure Platform

CERN Document Server

Redkar, Tejaswi

2010-01-01

The Azure Services Platform is a brand-new cloud-computing technology from Microsoft. It is composed of four core components-Windows Azure, .NET Services, SQL Services, and Live Services-each with a unique role in the functioning of your cloud service. It is the goal of this book to show you how to use these components, both separately and together, to build flawless cloud services. At its heart Windows Azure Platform is a down-to-earth, code-centric book. This book aims to show you precisely how the components are employed and to demonstrate the techniques and best practices you need to know

Temperature profile data from XBT casts from MULTIPLE PLATFORMS from a World-Wide distribution from 02 January 1990 to 31 December 1995 (NODC Accession 0001268)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — XBT data were collected from MULTIPLE PLATFORMS from a World-Wide distribution from 02 January 1990 to 31 December 1995. Data were submitted by the UK Hydrographic...

ENVIRONMENT: a computational platform to stochastically simulate reacting and self-reproducing lipid compartments

Science.gov (United States)

Mavelli, Fabio; Ruiz-Mirazo, Kepa

2010-09-01

'ENVIRONMENT' is a computational platform that has been developed in the last few years with the aim to simulate stochastically the dynamics and stability of chemically reacting protocellular systems. Here we present and describe some of its main features, showing how the stochastic kinetics approach can be applied to study the time evolution of reaction networks in heterogeneous conditions, particularly when supramolecular lipid structures (micelles, vesicles, etc) coexist with aqueous domains. These conditions are of special relevance to understand the origins of cellular, self-reproducing compartments, in the context of prebiotic chemistry and evolution. We contrast our simulation results with real lab experiments, with the aim to bring together theoretical and experimental research on protocell and minimal artificial cell systems.

Computational and mathematical methods in brain atlasing.

Science.gov (United States)

Nowinski, Wieslaw L

2017-12-01

Brain atlases have a wide range of use from education to research to clinical applications. Mathematical methods as well as computational methods and tools play a major role in the process of brain atlas building and developing atlas-based applications. Computational methods and tools cover three areas: dedicated editors for brain model creation, brain navigators supporting multiple platforms, and atlas-assisted specific applications. Mathematical methods in atlas building and developing atlas-aided applications deal with problems in image segmentation, geometric body modelling, physical modelling, atlas-to-scan registration, visualisation, interaction and virtual reality. Here I overview computational and mathematical methods in atlas building and developing atlas-assisted applications, and share my contribution to and experience in this field.

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.

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.

Integrated Markov-neural reliability computation method: A case for multiple automated guided vehicle system

International Nuclear Information System (INIS)

Fazlollahtabar, Hamed; Saidi-Mehrabad, Mohammad; Balakrishnan, Jaydeep

2015-01-01

This paper proposes an integrated Markovian and back propagation neural network approaches to compute reliability of a system. While states of failure occurrences are significant elements for accurate reliability computation, Markovian based reliability assessment method is designed. Due to drawbacks shown by Markovian model for steady state reliability computations and neural network for initial training pattern, integration being called Markov-neural is developed and evaluated. To show efficiency of the proposed approach comparative analyses are performed. Also, for managerial implication purpose an application case for multiple automated guided vehicles (AGVs) in manufacturing networks is conducted. - Highlights: • Integrated Markovian and back propagation neural network approach to compute reliability. • Markovian based reliability assessment method. • Managerial implication is shown in an application case for multiple automated guided vehicles (AGVs) in manufacturing networks

Heterogeneous computing with OpenCL

CERN Document Server

2013-01-01

Heterogeneous Computing with OpenCL teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. Designed to work on multiple platforms and with wide industry support, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, this book will give you hands-on OpenCL experience to address a range of fundamental parallel algorithms. The authors explore memory spaces, optimization techniques, graphics interoperability, extensions, and debugging and profiling. Intended to support a parallel programming course, Heterogeneous Computing with OpenCL includes detailed examples throughout, plus additional online exercises and other supporting materials.

Robotic vehicle with multiple tracked mobility platforms

Science.gov (United States)

Salton, Jonathan R [Albuquerque, NM; Buttz, James H [Albuquerque, NM; Garretson, Justin [Albuquerque, NM; Hayward, David R [Wetmore, CO; Hobart, Clinton G [Albuquerque, NM; Deuel, Jr., Jamieson K.

2012-07-24

A robotic vehicle having two or more tracked mobility platforms that are mechanically linked together with a two-dimensional coupling, thereby forming a composite vehicle of increased mobility. The robotic vehicle is operative in hazardous environments and can be capable of semi-submersible operation. The robotic vehicle is capable of remote controlled operation via radio frequency and/or fiber optic communication link to a remote operator control unit. The tracks have a plurality of track-edge scallop cut-outs that allow the tracks to easily grab onto and roll across railroad tracks, especially when crossing the railroad tracks at an oblique angle.

Efficient Sensor Integration on Platforms (NeXOS)

Science.gov (United States)

Memè, S.; Delory, E.; Del Rio, J.; Jirka, S.; Toma, D. M.; Martinez, E.; Frommhold, L.; Barrera, C.; Pearlman, J.

2016-12-01

In-situ ocean observing platforms provide power and information transmission capability to sensors. Ocean observing platforms can be mobile, such as ships, autonomous underwater vehicles, drifters and profilers, or fixed, such as buoys, moorings and cabled observatories. The process of integrating sensors on platforms can imply substantial engineering time and resources. Constraints range from stringent mechanical constraints to proprietary communication and control firmware. In NeXOS, the implementation of a PUCK plug and play capability is being done with applications to multiple sensors and platforms. This is complemented with a sensor web enablement that addresses the flow of information from sensor to user. Open standards are being tested in order to assess their costs and benefits in existing and future observing systems. Part of the testing implied open-source coding and hardware prototyping of specific control devices in particular for closed commercial platforms where firmware upgrading is not straightforward or possible without prior agreements or service fees. Some platform manufacturers such as European companies ALSEAMAR[1] and NKE Instruments [2] are currently upgrading their control and communication firmware as part of their activities in NeXOS. The sensor development companies Sensorlab[3] SMID[4] and TRIOS [5]upgraded their firmware with this plug and play functionality. Other industrial players in Europe and the US have been sent NeXOS sensors emulators to test the new protocol on their platforms. We are currently demonstrating that with little effort, it is also possible to have such middleware implemented on very low-cost compact computers such as the open Raspberry Pi[6], and have a full end-to-end interoperable communication path from sensor to user with sensor plug and play capability. The result is an increase in sensor integration cost-efficiency and the demonstration will be used to highlight the benefit to users and ocean observatory

Porting of serial molecular dynamics code on MIMD platforms

International Nuclear Information System (INIS)

Celino, M.

1995-05-01

A molecular Dynamics (MD) code, utilized for the study of atomistic models of metallic systems has been parallelized for MIMD (Multiple Instructions Multiple Data) parallel platforms by means of the Parallel Virtual Machine (PVM) message passing library. Since the parallelization implies modifications of the sequential algorithms, these are described from the point of view of the Statistical Mechanics theory. Furthermore, techniques and parallelization strategies utilized and the MD parallel code are described in detail. Benchmarks on several MIMD platforms (IBM SP1 and SP2, Cray T3D, Cluster of workstations) allow performances evaluation of the code versus the different characteristics of the parallel platforms

Parallel Task Processing on a Multicore Platform in a PC-based Control System for Parallel Kinematics

Directory of Open Access Journals (Sweden)

Harald Michalik

2009-02-01

Full Text Available Multicore platforms are such that have one physical processor chip with multiple cores interconnected via a chip level bus. Because they deliver a greater computing power through concurrency, offer greater system density multicore platforms provide best qualifications to address the performance bottleneck encountered in PC-based control systems for parallel kinematic robots with heavy CPU-load. Heavy load control tasks are generated by new control approaches that include features like singularity prediction, structure control algorithms, vision data integration and similar tasks. In this paper we introduce the parallel task scheduling extension of a communication architecture specially tailored for the development of PC-based control of parallel kinematics. The Sche-duling is specially designed for the processing on a multicore platform. It breaks down the serial task processing of the robot control cycle and extends it with parallel task processing paths in order to enhance the overall control performance.

OpenVX-based Python Framework for real-time cross platform acceleration of embedded computer vision applications

Directory of Open Access Journals (Sweden)

Ori Heimlich

2016-11-01

Full Text Available Embedded real-time vision applications are being rapidly deployed in a large realm of consumer electronics, ranging from automotive safety to surveillance systems. However, the relatively limited computational power of embedded platforms is considered as a bottleneck for many vision applications, necessitating optimization. OpenVX is a standardized interface, released in late 2014, in an attempt to provide both system and kernel level optimization to vision applications. With OpenVX, Vision processing are modeled with coarse-grained data flow graphs, which can be optimized and accelerated by the platform implementer. Current full implementations of OpenVX are given in the programming language C, which does not support advanced programming paradigms such as object-oriented, imperative and functional programming, nor does it have runtime or type-checking. Here we present a python-based full Implementation of OpenVX, which eliminates much of the discrepancies between the object-oriented paradigm used by many modern applications and the native C implementations. Our open-source implementation can be used for rapid development of OpenVX applications in embedded platforms. Demonstration includes static and real-time image acquisition and processing using a Raspberry Pi and a GoPro camera. Code is given as supplementary information. Code project and linked deployable virtual machine are located on GitHub: https://github.com/NBEL-lab/PythonOpenVX.

Integration of the TNXYZ computer program inside the platform Salome

International Nuclear Information System (INIS)

Chaparro V, F. J.

2014-01-01

The present work shows the procedure carried out to integrate the code TNXYZ as a calculation tool at the graphical simulation platform Salome. The TNXYZ code propose a numerical solution of the neutron transport equation, in several groups of energy, steady-state and three-dimensional geometry. In order to discretized the variables of the transport equation, the code uses the method of discrete ordinates for the angular variable, and a nodal method for the spatial dependence. The Salome platform is a graphical environment designed for building, editing and simulating mechanical models mainly focused on the industry and unlike other software, in order to form a complete scheme of pre and post processing of information, to integrate and control an external source code. Before the integration the in the Salome platform TNXYZ code was upgraded. TNXYZ was programmed in the 90s using Fortran 77 compiler; for this reason the code was adapted to the characteristics of the current Fortran compilers; in addition, with the intention of extracting partial results over the process sequence, the original structure of the program underwent a modularization process, i.e. the main program was divided into sections where the code performs major operations. This procedure is controlled by the information module (YACS) on Salome platform, and it could be useful for a subsequent coupling with thermal-hydraulics codes. Finally, with the help of the Monte Carlo code Serpent several study cases were defined in order to check the process of integration; the verification process consisted in performing a comparison of the results obtained with the code executed as stand-alone and after modernized, integrated and controlled by the Salome platform. (Author)

An Open-Source Based ITS Platform

DEFF Research Database (Denmark)

Andersen, Ove; Krogh, Benjamin Bjerre; Torp, Kristian

2013-01-01

In this paper, a complete platform used to compute travel times from GPS data is described. Two approaches to computing travel time are proposed one based on points and one based on trips. Overall both approaches give reasonable results compared to existing manual estimated travel times. However......, the trip-based approach requires more GPS data and of a higher quality than the point-based approach. The platform has been completely implemented using open-source software. The main conclusion is that large quantity of GPS data can be managed, with a limited budget and that GPS data is a good source...... for estimating travel times, if enough data is available....

Design of platform for removing screws from LCD display shields

Science.gov (United States)

Tu, Zimei; Qin, Qin; Dou, Jianfang; Zhu, Dongdong

2017-11-01

Removing the screws on the sides of a shield is a necessary process in disassembling a computer LCD display. To solve this issue, a platform has been designed for removing the screws on display shields. This platform uses virtual instrument technology with LabVIEW as the development environment to design the mechanical structure with the technologies of motion control, human-computer interaction and target recognition. This platform removes the screws from the sides of the shield of an LCD display mechanically thus to guarantee follow-up separation and recycle.

Matrix-vector multiplication using digital partitioning for more accurate optical computing

Science.gov (United States)

Gary, C. K.

1992-01-01

Digital partitioning offers a flexible means of increasing the accuracy of an optical matrix-vector processor. This algorithm can be implemented with the same architecture required for a purely analog processor, which gives optical matrix-vector processors the ability to perform high-accuracy calculations at speeds comparable with or greater than electronic computers as well as the ability to perform analog operations at a much greater speed. Digital partitioning is compared with digital multiplication by analog convolution, residue number systems, and redundant number representation in terms of the size and the speed required for an equivalent throughput as well as in terms of the hardware requirements. Digital partitioning and digital multiplication by analog convolution are found to be the most efficient alogrithms if coding time and hardware are considered, and the architecture for digital partitioning permits the use of analog computations to provide the greatest throughput for a single processor.

Users and Programmers Guide for HPC Platforms in CIEMAT

International Nuclear Information System (INIS)

Munoz Roldan, A.

2003-01-01

This Technical Report presents a description of the High Performance Computing platforms available to researchers in CIEMAT and dedicated mainly to scientific computing. It targets to users and programmers and tries to help in the processes of developing new code and porting code across platforms. A brief review is also presented about historical evolution in the field of HPC, ie, the programming paradigms and underlying architectures. (Author) 32 refs

Operational flash flood forecasting platform based on grid technology

Science.gov (United States)

Thierion, V.; Ayral, P.-A.; Angelini, V.; Sauvagnargues-Lesage, S.; Nativi, S.; Payrastre, O.

2009-04-01

effort in term of grid technology development. This paper presents an operational flash flood forecasting platform which have been developed in the framework of CYCLOPS European project providing one of virtual organizations of EGEE project. This platform has been designed to enable multi-simulations processes to ease forecasting operations of several supervised watersheds on Grand Delta (SPC-GD) territory. Grid technology infrastructure, in providing multiple remote computing elements enables the processing of multiple rainfall scenarios, derived to the original meteorological forecasting transmitted by Meteo-France, and their respective hydrological simulations. First results show that from one forecasting scenario, this new presented approach can permit simulations of more than 200 different scenarios to support forecasters in their aforesaid mission and appears as an efficient hydrological decision-making tool. Although, this system seems operational, model validity has to be confirmed. So, further researches are necessary to improve models core to be more efficient in term of hydrological aspects. Finally, this platform could be an efficient tool for developing others modelling aspects as calibration or data assimilation in real time processing.

A Conceptual Architecture for Adaptive Human-Computer Interface of a PT Operation Platform Based on Context-Awareness

Directory of Open Access Journals (Sweden)

Qing Xue

2014-01-01

Full Text Available We present a conceptual architecture for adaptive human-computer interface of a PT operation platform based on context-awareness. This architecture will form the basis of design for such an interface. This paper describes components, key technologies, and working principles of the architecture. The critical contents covered context information modeling, processing, relationship establishing between contexts and interface design knowledge by use of adaptive knowledge reasoning, and visualization implementing of adaptive interface with the aid of interface tools technology.

Performance Measurement of Complex Event Platforms

Directory of Open Access Journals (Sweden)

Eva Zámečníková

2016-12-01

Full Text Available The aim of this paper is to find and compare existing solutions of complex event processing platforms (CEP. CEP platforms generally serve for processing and/or predicting of high frequency data. We intend to use CEP platform for processing of complex time series and integrate a solution for newly proposed method of decision making. The decision making process will be described by formal grammar. As there are lots of CEP solutions we will take the following characteristics under consideration - the processing in real time, possibility of processing of high volume data from multiple sources, platform independence, platform allowing integration with user solution and open license. At first we will talk about existing CEP tools and their specific way of use in praxis. Then we will mention the design of method for formalization of business rules used for decision making. Afterwards, we focus on two platforms which seem to be the best fit for integration of our solution and we will list the main pros and cons of each approach. Next part is devoted to benchmark platforms for CEP. Final part is devoted to experimental measurements of platform with integrated method for decision support.

Towards a Market Entry Framework for Digital Payment Platforms

DEFF Research Database (Denmark)

Kazan, Erol; Damsgaard, Jan

2016-01-01

This study presents a framework to understand and explain the design and configuration of digital payment platforms and how these platforms create conditions for market entries. By embracing the theoretical lens of platform envelopment, we employed a multiple and comparative-case study...... in a European setting by using our framework as an analytical lens to assess market-entry conditions. We found that digital payment platforms have acquired market entry capabilities, which is achieved through strategic platform design (i.e., platform development and service distribution) and technology design...... (i.e., issuing evolutionary and revolutionary payment instruments). The studied cases reveal that digital platforms leverage payment services as a mean to bridge and converge core and adjacent platform markets. In so doing, platform envelopment strengthens firms’ market position in their respective...

Simultaneous detection of multiple HPV DNA via bottom-well microfluidic chip within an infra-red PCR platform.

Science.gov (United States)

Liu, Wenjia; Warden, Antony; Sun, Jiahui; Shen, Guangxia; Ding, Xianting

2018-03-01

Portable Polymerase Chain Reaction (PCR) devices combined with microfluidic chips or lateral flow stripes have shown great potential in the field of point-of-need testing (PoNT) as they only require a small volume of patient sample and are capable of presenting results in a short time. However, the detection for multiple targets in this field leaves much to be desired. Herein, we introduce a novel PCR platform by integrating a bottom-well microfluidic chip with an infra-red (IR) excited temperature control method and fluorescence co-detection of three PCR products. Microfluidic chips are utilized to partition different samples into individual bottom-wells. The oil phase in the main channel contains multi-walled carbon nanotubes which were used as a heat transfer medium that absorbs energy from the IR-light-emitting diode (LED) and transfers heat to the water phase below. Cyclical rapid heating and cooling necessary for PCR are achieved by alternative power switching of the IR-LED and Universal Serial Bus (USB) mini-fan with a pulse width modulation scheme. This design of the IR-LED PCR platform is economic, compact, and fully portable, making it a promising application in the field of PoNT. The bottom-well microfluidic chip and IR-LED PCR platform were combined to fulfill a three-stage thermal cycling PCR for 40 cycles within 90 min for Human Papilloma Virus (HPV) detection. The PCR fluorescent signal was successfully captured at the end of each cycle. The technique introduced here has broad applications in nucleic acid amplification and PoNT devices.

A Collaborative Digital Pathology System for Multi-Touch Mobile and Desktop Computing Platforms

KAUST Repository

Jeong, W.

2013-06-13

Collaborative slide image viewing systems are becoming increasingly important in pathology applications such as telepathology and E-learning. Despite rapid advances in computing and imaging technology, current digital pathology systems have limited performance with respect to remote viewing of whole slide images on desktop or mobile computing devices. In this paper we present a novel digital pathology client-server system that supports collaborative viewing of multi-plane whole slide images over standard networks using multi-touch-enabled clients. Our system is built upon a standard HTTP web server and a MySQL database to allow multiple clients to exchange image and metadata concurrently. We introduce a domain-specific image-stack compression method that leverages real-time hardware decoding on mobile devices. It adaptively encodes image stacks in a decorrelated colour space to achieve extremely low bitrates (0.8 bpp) with very low loss of image quality. We evaluate the image quality of our compression method and the performance of our system for diagnosis with an in-depth user study. Collaborative slide image viewing systems are becoming increasingly important in pathology applications such as telepathology and E-learning. Despite rapid advances in computing and imaging technology, current digital pathology systems have limited performance with respect to remote viewing of whole slide images on desktop or mobile computing devices. In this paper we present a novel digital pathology client-server systems that supports collaborative viewing of multi-plane whole slide images over standard networks using multi-touch enabled clients. Our system is built upon a standard HTTP web server and a MySQL database to allow multiple clients to exchange image and metadata concurrently. © 2013 The Eurographics Association and John Wiley & Sons Ltd.

A Collaborative Digital Pathology System for Multi-Touch Mobile and Desktop Computing Platforms

KAUST Repository

Jeong, W.; Schneider, J.; Hansen, A.; Lee, M.; Turney, S. G.; Faulkner-Jones, B. E.; Hecht, J. L.; Najarian, R.; Yee, E.; Lichtman, J. W.; Pfister, H.

2013-01-01

Collaborative slide image viewing systems are becoming increasingly important in pathology applications such as telepathology and E-learning. Despite rapid advances in computing and imaging technology, current digital pathology systems have limited performance with respect to remote viewing of whole slide images on desktop or mobile computing devices. In this paper we present a novel digital pathology client-server system that supports collaborative viewing of multi-plane whole slide images over standard networks using multi-touch-enabled clients. Our system is built upon a standard HTTP web server and a MySQL database to allow multiple clients to exchange image and metadata concurrently. We introduce a domain-specific image-stack compression method that leverages real-time hardware decoding on mobile devices. It adaptively encodes image stacks in a decorrelated colour space to achieve extremely low bitrates (0.8 bpp) with very low loss of image quality. We evaluate the image quality of our compression method and the performance of our system for diagnosis with an in-depth user study. Collaborative slide image viewing systems are becoming increasingly important in pathology applications such as telepathology and E-learning. Despite rapid advances in computing and imaging technology, current digital pathology systems have limited performance with respect to remote viewing of whole slide images on desktop or mobile computing devices. In this paper we present a novel digital pathology client-server systems that supports collaborative viewing of multi-plane whole slide images over standard networks using multi-touch enabled clients. Our system is built upon a standard HTTP web server and a MySQL database to allow multiple clients to exchange image and metadata concurrently. © 2013 The Eurographics Association and John Wiley & Sons Ltd.

A computational procedure for finding multiple solutions of convective heat transfer equations

International Nuclear Information System (INIS)

Mishra, S; DebRoy, T

2005-01-01

In recent years numerical solutions of the convective heat transfer equations have provided significant insight into the complex materials processing operations. However, these computational methods suffer from two major shortcomings. First, these procedures are designed to calculate temperature fields and cooling rates as output and the unidirectional structure of these solutions preclude specification of these variables as input even when their desired values are known. Second, and more important, these procedures cannot determine multiple pathways or multiple sets of input variables to achieve a particular output from the convective heat transfer equations. Here we propose a new method that overcomes the aforementioned shortcomings of the commonly used solutions of the convective heat transfer equations. The procedure combines the conventional numerical solution methods with a real number based genetic algorithm (GA) to achieve bi-directionality, i.e. the ability to calculate the required input variables to achieve a specific output such as temperature field or cooling rate. More important, the ability of the GA to find a population of solutions enables this procedure to search for and find multiple sets of input variables, all of which can lead to the desired specific output. The proposed computational procedure has been applied to convective heat transfer in a liquid layer locally heated on its free surface by an electric arc, where various sets of input variables are computed to achieve a specific fusion zone geometry defined by an equilibrium temperature. Good agreement is achieved between the model predictions and the independent experimental results, indicating significant promise for the application of this procedure in finding multiple solutions of convective heat transfer equations

On efficiency of fire simulation realization: parallelization with greater number of computational meshes

Science.gov (United States)

Valasek, Lukas; Glasa, Jan

2017-12-01

Current fire simulation systems are capable to utilize advantages of high-performance computer (HPC) platforms available and to model fires efficiently in parallel. In this paper, efficiency of a corridor fire simulation on a HPC computer cluster is discussed. The parallel MPI version of Fire Dynamics Simulator is used for testing efficiency of selected strategies of allocation of computational resources of the cluster using a greater number of computational cores. Simulation results indicate that if the number of cores used is not equal to a multiple of the total number of cluster node cores there are allocation strategies which provide more efficient calculations.

National Community Solar Platform

Energy Technology Data Exchange (ETDEWEB)

Rupert, Bart [Clean Energy Collective, Louisville, CO (United States)

2016-06-30

This project was created to provide a National Community Solar Platform (NCSP) portal known as Community Solar Hub, that is available to any entity or individual who wants to develop community solar. This has been done by providing a comprehensive portal to make CEC’s solutions, and other proven community solar solutions, externally available for everyone to access – making the process easy through proven platforms to protect subscribers, developers and utilities. The successful completion of this project provides these tools via a web platform and integration APIs, a wide spectrum of community solar projects included in the platform, multiple groups of customers (utilities, EPCs, and advocates) using the platform to develop community solar, and open access to anyone interested in community solar. CEC’s Incubator project includes web-based informational resources, integrated systems for project information and billing systems, and engagement with customers and users by community solar experts. The combined effort externalizes much of Clean Energy Collective’s industry-leading expertise, allowing third parties to develop community solar without duplicating expensive start-up efforts. The availability of this platform creates community solar projects that are cheaper to build and cheaper to participate in, furthering the goals of DOE’s SunShot Initiative. Final SF 425 Final SF 428 Final DOE F 2050.11 Final Report Narrative

Monitoring system including an electronic sensor platform and an interrogation transceiver

Science.gov (United States)

Kinzel, Robert L.; Sheets, Larry R.

2003-09-23

A wireless monitoring system suitable for a wide range of remote data collection applications. The system includes at least one Electronic Sensor Platform (ESP), an Interrogator Transceiver (IT) and a general purpose host computer. The ESP functions as a remote data collector from a number of digital and analog sensors located therein. The host computer provides for data logging, testing, demonstration, installation checkout, and troubleshooting of the system. The IT transmits signals from one or more ESP's to the host computer to the ESP's. The IT host computer may be powered by a common power supply, and each ESP is individually powered by a battery. This monitoring system has an extremely low power consumption which allows remote operation of the ESP for long periods; provides authenticated message traffic over a wireless network; utilizes state-of-health and tamper sensors to ensure that the ESP is secure and undamaged; has robust housing of the ESP suitable for use in radiation environments; and is low in cost. With one base station (host computer and interrogator transceiver), multiple ESP's may be controlled at a single monitoring site.

CoreFlow: a computational platform for integration, analysis and modeling of complex biological data.

Science.gov (United States)

Pasculescu, Adrian; Schoof, Erwin M; Creixell, Pau; Zheng, Yong; Olhovsky, Marina; Tian, Ruijun; So, Jonathan; Vanderlaan, Rachel D; Pawson, Tony; Linding, Rune; Colwill, Karen

2014-04-04

A major challenge in mass spectrometry and other large-scale applications is how to handle, integrate, and model the data that is produced. Given the speed at which technology advances and the need to keep pace with biological experiments, we designed a computational platform, CoreFlow, which provides programmers with a framework to manage data in real-time. It allows users to upload data into a relational database (MySQL), and to create custom scripts in high-level languages such as R, Python, or Perl for processing, correcting and modeling this data. CoreFlow organizes these scripts into project-specific pipelines, tracks interdependencies between related tasks, and enables the generation of summary reports as well as publication-quality images. As a result, the gap between experimental and computational components of a typical large-scale biology project is reduced, decreasing the time between data generation, analysis and manuscript writing. CoreFlow is being released to the scientific community as an open-sourced software package complete with proteomics-specific examples, which include corrections for incomplete isotopic labeling of peptides (SILAC) or arginine-to-proline conversion, and modeling of multiple/selected reaction monitoring (MRM/SRM) results. CoreFlow was purposely designed as an environment for programmers to rapidly perform data analysis. These analyses are assembled into project-specific workflows that are readily shared with biologists to guide the next stages of experimentation. Its simple yet powerful interface provides a structure where scripts can be written and tested virtually simultaneously to shorten the life cycle of code development for a particular task. The scripts are exposed at every step so that a user can quickly see the relationships between the data, the assumptions that have been made, and the manipulations that have been performed. Since the scripts use commonly available programming languages, they can easily be

BioAnnote: a software platform for annotating biomedical documents with application in medical learning environments.

Science.gov (United States)

López-Fernández, H; Reboiro-Jato, M; Glez-Peña, D; Aparicio, F; Gachet, D; Buenaga, M; Fdez-Riverola, F

2013-07-01

Automatic term annotation from biomedical documents and external information linking are becoming a necessary prerequisite in modern computer-aided medical learning systems. In this context, this paper presents BioAnnote, a flexible and extensible open-source platform for automatically annotating biomedical resources. Apart from other valuable features, the software platform includes (i) a rich client enabling users to annotate multiple documents in a user friendly environment, (ii) an extensible and embeddable annotation meta-server allowing for the annotation of documents with local or remote vocabularies and (iii) a simple client/server protocol which facilitates the use of our meta-server from any other third-party application. In addition, BioAnnote implements a powerful scripting engine able to perform advanced batch annotations. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

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

Adiabatic Quantum Computing

Science.gov (United States)

Landahl, Andrew

2012-10-01

Quantum computers promise to exploit counterintuitive quantum physics principles like superposition, entanglement, and uncertainty to solve problems using fundamentally fewer steps than any conventional computer ever could. The mere possibility of such a device has sharpened our understanding of quantum coherent information, just as lasers did for our understanding of coherent light. The chief obstacle to developing quantum computer technology is decoherence--one of the fastest phenomena in all of physics. In principle, decoherence can be overcome by using clever entangled redundancies in a process called fault-tolerant quantum error correction. However, the quality and scale of technology required to realize this solution appears distant. An exciting alternative is a proposal called ``adiabatic'' quantum computing (AQC), in which adiabatic quantum physics keeps the computer in its lowest-energy configuration throughout its operation, rendering it immune to many decoherence sources. The Adiabatic Quantum Architectures In Ultracold Systems (AQUARIUS) Grand Challenge Project at Sandia seeks to demonstrate this robustness in the laboratory and point a path forward for future hardware development. We are building devices in AQUARIUS that realize the AQC architecture on up to three quantum bits (``qubits'') in two platforms: Cs atoms laser-cooled to below 5 microkelvin and Si quantum dots cryo-cooled to below 100 millikelvin. We are also expanding theoretical frontiers by developing methods for scalable universal AQC in these platforms. We have successfully demonstrated operational qubits in both platforms and have even run modest one-qubit calculations using our Cs device. In the course of reaching our primary proof-of-principle demonstrations, we have developed multiple spinoff technologies including nanofabricated diffractive optical elements that define optical-tweezer trap arrays and atomic-scale Si lithography commensurate with placing individual donor atoms with

Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing

Directory of Open Access Journals (Sweden)

Fan Zhang

2016-04-01

Full Text Available With the development of synthetic aperture radar (SAR technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO. However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.

Science.gov (United States)

Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

2016-04-07

With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

Genomics With Cloud Computing

Directory of Open Access Journals (Sweden)

Sukhamrit Kaur

2015-04-01

Full Text Available Abstract Genomics is study of genome which provides large amount of data for which large storage and computation power is needed. These issues are solved by cloud computing that provides various cloud platforms for genomics. These platforms provides many services to user like easy access to data easy sharing and transfer providing storage in hundreds of terabytes more computational power. Some cloud platforms are Google genomics DNAnexus and Globus genomics. Various features of cloud computing to genomics are like easy access and sharing of data security of data less cost to pay for resources but still there are some demerits like large time needed to transfer data less network bandwidth.

Hybrid Cloud Computing Environment for EarthCube and Geoscience Community

Science.gov (United States)

Yang, C. P.; Qin, H.

2016-12-01

The NSF EarthCube Integration and Test Environment (ECITE) has built a hybrid cloud computing environment to provides cloud resources from private cloud environments by using cloud system software - OpenStack and Eucalyptus, and also manages public cloud - Amazon Web Service that allow resource synchronizing and bursting between private and public cloud. On ECITE hybrid cloud platform, EarthCube and geoscience community can deploy and manage the applications by using base virtual machine images or customized virtual machines, analyze big datasets by using virtual clusters, and real-time monitor the virtual resource usage on the cloud. Currently, a number of EarthCube projects have deployed or started migrating their projects to this platform, such as CHORDS, BCube, CINERGI, OntoSoft, and some other EarthCube building blocks. To accomplish the deployment or migration, administrator of ECITE hybrid cloud platform prepares the specific needs (e.g. images, port numbers, usable cloud capacity, etc.) of each project in advance base on the communications between ECITE and participant projects, and then the scientists or IT technicians in those projects launch one or multiple virtual machines, access the virtual machine(s) to set up computing environment if need be, and migrate their codes, documents or data without caring about the heterogeneity in structure and operations among different cloud platforms.

HPC - Platforms Penta Chart

Energy Technology Data Exchange (ETDEWEB)

Trujillo, Angelina Michelle [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2015-10-08

Strategy, Planning, Acquiring- very large scale computing platforms come and go and planning for immensely scalable machines often precedes actual procurement by 3 years. Procurement can be another year or more. Integration- After Acquisition, machines must be integrated into the computing environments at LANL. Connection to scalable storage via large scale storage networking, assuring correct and secure operations. Management and Utilization – Ongoing operations, maintenance, and trouble shooting of the hardware and systems software at massive scale is required.

Fusion virtual laboratory: The experiments' collaboration platform in Japan

Energy Technology Data Exchange (ETDEWEB)

Nakanishi, H., E-mail: nakanisi@nifs.ac.jp [National Institute for Fusion Science, Toki, Gifu 509-5292 (Japan); Kojima, M.; Takahashi, C.; Ohsuna, M.; Imazu, S.; Nonomura, M. [National Institute for Fusion Science, Toki, Gifu 509-5292 (Japan); Hasegawa, M. [RIAM, Kyushu University, Kasuga, Fukuoka 816-8560 (Japan); Yoshikawa, M. [PRC, University of Tsukuba, Tsukuba, Ibaraki 305-8577 (Japan); Nagayama, Y.; Kawahata, K. [National Institute for Fusion Science, Toki, Gifu 509-5292 (Japan)

2012-12-15

'Fusion virtual laboratory (FVL)' is the experiments' collaboration platform covering multiple fusion projects in Japan. Major Japanese fusion laboratories and universities are mutually connected through the dedicated virtual private network, named SNET, on SINET4. It has 3 different categories; (i) LHD remote participation, (ii) bilateral experiments' collaboration, and (iii) remote use of supercomputer. By extending the LABCOM data system developed at LHD, FVL supports (i) and (ii) so that it can deal with not only LHD data but also the data of two remote experiments: QUEST at Kyushu University and GAMMA10 at University of Tsukuba. FVL has applied the latest 'cloud' technology for both data acquisition and storage architecture. It can provide us high availability and performance scalability of the whole system. With a well optimized TCP data transferring method, the unified data access platform for both experimental data and numerical computation results could become realistic on FVL. The FVL project will continue demonstrating the ITER-era international collaboration schemes and the necessary technology.

Business and IT Capabilities for Cloud Platform Success

DEFF Research Database (Denmark)

Hahn, Christopher; Huntgeburth, Jan; Winkler, Till J.

2016-01-01

The growing proliferation of cloud platform ecosystems demands a deeper understanding of the capabilities that help existing and emerging platform providers to be successful by creating and appropriating value. This multiple case study of four cloud platform providers (three large, one SME......) instantiates Rai and Tang’s (2014) framework of dyadic IT and network IT capabilities for a cloud platform context and extends it by exploring previously undertheorized cloud platform business capabilities. We further build on this extended framework by employing a configurational perspective to elucidate...... the complementary role of the three proposed business capabilities (incentives and rules, ecosystem marketing and sales, partner development and support) for relevant value creation and appropriation mechanisms. In addition to providing a capability framework catered to the cloud platform context, our findings...

Murasaki: a fast, parallelizable algorithm to find anchors from multiple genomes.

Directory of Open Access Journals (Sweden)

Kris Popendorf

Full Text Available BACKGROUND: With the number of available genome sequences increasing rapidly, the magnitude of sequence data required for multiple-genome analyses is a challenging problem. When large-scale rearrangements break the collinearity of gene orders among genomes, genome comparison algorithms must first identify sets of short well-conserved sequences present in each genome, termed anchors. Previously, anchor identification among multiple genomes has been achieved using pairwise alignment tools like BLASTZ through progressive alignment tools like TBA, but the computational requirements for sequence comparisons of multiple genomes quickly becomes a limiting factor as the number and scale of genomes grows. METHODOLOGY/PRINCIPAL FINDINGS: Our algorithm, named Murasaki, makes it possible to identify anchors within multiple large sequences on the scale of several hundred megabases in few minutes using a single CPU. Two advanced features of Murasaki are (1 adaptive hash function generation, which enables efficient use of arbitrary mismatch patterns (spaced seeds and therefore the comparison of multiple mammalian genomes in a practical amount of computation time, and (2 parallelizable execution that decreases the required wall-clock and CPU times. Murasaki can perform a sensitive anchoring of eight mammalian genomes (human, chimp, rhesus, orangutan, mouse, rat, dog, and cow in 21 hours CPU time (42 minutes wall time. This is the first single-pass in-core anchoring of multiple mammalian genomes. We evaluated Murasaki by comparing it with the genome alignment programs BLASTZ and TBA. We show that Murasaki can anchor multiple genomes in near linear time, compared to the quadratic time requirements of BLASTZ and TBA, while improving overall accuracy. CONCLUSIONS/SIGNIFICANCE: Murasaki provides an open source platform to take advantage of long patterns, cluster computing, and novel hash algorithms to produce accurate anchors across multiple genomes with

Global Software Development with Cloud Platforms

Science.gov (United States)

Yara, Pavan; Ramachandran, Ramaseshan; Balasubramanian, Gayathri; Muthuswamy, Karthik; Chandrasekar, Divya

Offshore and outsourced distributed software development models and processes are facing challenges, previously unknown, with respect to computing capacity, bandwidth, storage, security, complexity, reliability, and business uncertainty. Clouds promise to address these challenges by adopting recent advances in virtualization, parallel and distributed systems, utility computing, and software services. In this paper, we envision a cloud-based platform that addresses some of these core problems. We outline a generic cloud architecture, its design and our first implementation results for three cloud forms - a compute cloud, a storage cloud and a cloud-based software service- in the context of global distributed software development (GSD). Our ”compute cloud” provides computational services such as continuous code integration and a compile server farm, ”storage cloud” offers storage (block or file-based) services with an on-line virtual storage service, whereas the on-line virtual labs represent a useful cloud service. We note some of the use cases for clouds in GSD, the lessons learned with our prototypes and identify challenges that must be conquered before realizing the full business benefits. We believe that in the future, software practitioners will focus more on these cloud computing platforms and see clouds as a means to supporting a ecosystem of clients, developers and other key stakeholders.

UAV Flight Control Based on RTX System Simulation Platform

Directory of Open Access Journals (Sweden)

Xiaojun Duan

2014-03-01

Full Text Available This paper proposes RTX and Matlab UAV flight control system simulation platform based on the advantages and disadvantages of Windows and real-time system RTX. In the simulation platform, we set the RTW toolbox configuration and modify grt_main.c in order to make simulation platform endowed with online parameter adjustment, fault injection. Meanwhile, we develop the interface of the system simulation platform by CVI, thus it makes effective and has good prospects in application. In order to improve the real-time performance of simulation system, the current computer of real-time simulation mostly use real-time operating system to solve simulation model, as well as dual- framework containing in Host and target machine. The system is complex, high cost, and generally used for the control and half of practical system simulation. For the control system designers, they expect to design control law at a computer with Windows-based environment and conduct real-time simulation. This paper proposes simulation platform for UAV flight control system based on RTX and Matlab for this demand.

ESPRIT-like algorithm for computational-efficient angle estimation in bistatic multiple-input multiple-output radar

Science.gov (United States)

Gong, Jian; Lou, Shuntian; Guo, Yiduo

2016-04-01

An estimation of signal parameters via a rotational invariance techniques-like (ESPRIT-like) algorithm is proposed to estimate the direction of arrival and direction of departure for bistatic multiple-input multiple-output (MIMO) radar. The properties of a noncircular signal and Euler's formula are first exploited to establish a real-valued bistatic MIMO radar array data, which is composed of sine and cosine data. Then the receiving/transmitting selective matrices are constructed to obtain the receiving/transmitting rotational invariance factors. Since the rotational invariance factor is a cosine function, symmetrical mirror angle ambiguity may occur. Finally, a maximum likelihood function is used to avoid the estimation ambiguities. Compared with the existing ESPRIT, the proposed algorithm can save about 75% of computational load owing to the real-valued ESPRIT algorithm. Simulation results confirm the effectiveness of the ESPRIT-like algorithm.

Evaluation of E-learning Platforms: a Case Study

Directory of Open Access Journals (Sweden)

Cristina POP

2012-01-01

Full Text Available In the recent past, a great number of e-learning platforms have been introduced on the market showing different characteristics and services. These platforms can be evaluated using multiple criteria and methods. This paper proposes a list of selected quality criteria for describing, characterizing and selecting e-learning platform. These criteria were designed based on e-learning standards. I also propose a mathematical model to determine the probability that a student uses an e-learning platform based on the factors (criteria that determine the quality of the platform and the socio-demographic variables of the student. The case study presented is an application of the model and the input data, intermediate calculations and final results were processed using SAS (Statistical Analysis Software.

Matrix multiplication operations with data pre-conditioning in a high performance computing architecture

Science.gov (United States)

Eichenberger, Alexandre E; Gschwind, Michael K; Gunnels, John A

2013-11-05

Mechanisms for performing matrix multiplication operations with data pre-conditioning in a high performance computing architecture are provided. A vector load operation is performed to load a first vector operand of the matrix multiplication operation to a first target vector register. A load and splat operation is performed to load an element of a second vector operand and replicating the element to each of a plurality of elements of a second target vector register. A multiply add operation is performed on elements of the first target vector register and elements of the second target vector register to generate a partial product of the matrix multiplication operation. The partial product of the matrix multiplication operation is accumulated with other partial products of the matrix multiplication operation.

Temperature, salinity, oxygen, silicate, phosphate, nitrite, and pH data collected in Okhotsk Sea by multiple platforms from 1985-03-20 to 1989-09-07 (NODC Accession 0075740)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Historical temperature, salinity, oxygen, silicate, phosphate, nitrite, and pH data collected in the Okhotsk Sea by multiple Soviet Union platforms in March 1985 and...

Research on acceleration method of reactor physics based on FPGA platforms

International Nuclear Information System (INIS)

Li, C.; Yu, G.; Wang, K.

2013-01-01

The physical designs of the new concept reactors which have complex structure, various materials and neutronic energy spectrum, have greatly improved the requirements to the calculation methods and the corresponding computing hardware. Along with the widely used parallel algorithm, heterogeneous platforms architecture has been introduced into numerical computations in reactor physics. Because of the natural parallel characteristics, the CPU-FPGA architecture is often used to accelerate numerical computation. This paper studies the application and features of this kind of heterogeneous platforms used in numerical calculation of reactor physics through practical examples. After the designed neutron diffusion module based on CPU-FPGA architecture achieves a 11.2 speed up factor, it is proved to be feasible to apply this kind of heterogeneous platform into reactor physics. (authors)

Off-line mapping of multi-rate dependent task sets to many-core platforms

DEFF Research Database (Denmark)

Puffitsch, Wolfgang; Noulard, Eric; Pagetti, Claire

2015-01-01

This paper presents an approach to execute safety-critical applications on multi- and many-core processors in a predictable manner. We investigate three concrete platforms: the Intel Single-chip Cloud Computer, the Texas Instruments TMS320C6678 and the Tilera TILEmpower-Gx36. We define an execution...... model to safely execute dependent periodic task sets on these platforms. The four rules of the execution model entail that an off-line mapping of the application to the platform must be computed. The paper details our approach to automatically compute a valid mapping. Furthermore, we evaluate our...

Platform Architecture for Decentralized Positioning Systems

Directory of Open Access Journals (Sweden)

Zakaria Kasmi

2017-04-01

Full Text Available A platform architecture for positioning systems is essential for the realization of a flexible localization system, which interacts with other systems and supports various positioning technologies and algorithms. The decentralized processing of a position enables pushing the application-level knowledge into a mobile station and avoids the communication with a central unit such as a server or a base station. In addition, the calculation of the position on low-cost and resource-constrained devices presents a challenge due to the limited computing, storage capacity, as well as power supply. Therefore, we propose a platform architecture that enables the design of a system with the reusability of the components, extensibility (e.g., with other positioning technologies and interoperability. Furthermore, the position is computed on a low-cost device such as a microcontroller, which simultaneously performs additional tasks such as data collecting or preprocessing based on an operating system. The platform architecture is designed, implemented and evaluated on the basis of two positioning systems: a field strength system and a time of arrival-based positioning system.

Consolidation of cloud computing in ATLAS

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00224309; The ATLAS collaboration; Cordeiro, Cristovao; Hover, John; Kouba, Tomas; Love, Peter; Mcnab, Andrew; Schovancova, Jaroslava; Sobie, Randall; Giordano, Domenico

2017-01-01

Throughout the first half of LHC Run 2, ATLAS cloud computing has undergone a period of consolidation, characterized by building upon previously established systems, with the aim of reducing operational effort, improving robustness, and reaching higher scale. This paper describes the current state of ATLAS cloud computing. Cloud activities are converging on a common contextualization approach for virtual machines, and cloud resources are sharing monitoring and service discovery components. We describe the integration of Vacuum resources, streamlined usage of the Simulation at Point 1 cloud for offline processing, extreme scaling on Amazon compute resources, and procurement of commercial cloud capacity in Europe. Finally, building on the previously established monitoring infrastructure, we have deployed a real-time monitoring and alerting platform which coalesces data from multiple sources, provides flexible visualization via customizable dashboards, and issues alerts and carries out corrective actions in resp...

Extending the BEAGLE library to a multi-FPGA platform.

Science.gov (United States)

Jin, Zheming; Bakos, Jason D

2013-01-19

Maximum Likelihood (ML)-based phylogenetic inference using Felsenstein's pruning algorithm is a standard method for estimating the evolutionary relationships amongst a set of species based on DNA sequence data, and is used in popular applications such as RAxML, PHYLIP, GARLI, BEAST, and MrBayes. The Phylogenetic Likelihood Function (PLF) and its associated scaling and normalization steps comprise the computational kernel for these tools. These computations are data intensive but contain fine grain parallelism that can be exploited by coprocessor architectures such as FPGAs and GPUs. A general purpose API called BEAGLE has recently been developed that includes optimized implementations of Felsenstein's pruning algorithm for various data parallel architectures. In this paper, we extend the BEAGLE API to a multiple Field Programmable Gate Array (FPGA)-based platform called the Convey HC-1. The core calculation of our implementation, which includes both the phylogenetic likelihood function (PLF) and the tree likelihood calculation, has an arithmetic intensity of 130 floating-point operations per 64 bytes of I/O, or 2.03 ops/byte. Its performance can thus be calculated as a function of the host platform's peak memory bandwidth and the implementation's memory efficiency, as 2.03 × peak bandwidth × memory efficiency. Our FPGA-based platform has a peak bandwidth of 76.8 GB/s and our implementation achieves a memory efficiency of approximately 50%, which gives an average throughput of 78 Gflops. This represents a ~40X speedup when compared with BEAGLE's CPU implementation on a dual Xeon 5520 and 3X speedup versus BEAGLE's GPU implementation on a Tesla T10 GPU for very large data sizes. The power consumption is 92 W, yielding a power efficiency of 1.7 Gflops per Watt. The use of data parallel architectures to achieve high performance for likelihood-based phylogenetic inference requires high memory bandwidth and a design methodology that emphasizes high memory

Multiple exciton generation in chiral carbon nanotubes: Density functional theory based computation

Science.gov (United States)

Kryjevski, Andrei; Mihaylov, Deyan; Kilina, Svetlana; Kilin, Dmitri

2017-10-01

We use a Boltzmann transport equation (BE) to study time evolution of a photo-excited state in a nanoparticle including phonon-mediated exciton relaxation and the multiple exciton generation (MEG) processes, such as exciton-to-biexciton multiplication and biexciton-to-exciton recombination. BE collision integrals are computed using Kadanoff-Baym-Keldysh many-body perturbation theory based on density functional theory simulations, including exciton effects. We compute internal quantum efficiency (QE), which is the number of excitons generated from an absorbed photon in the course of the relaxation. We apply this approach to chiral single-wall carbon nanotubes (SWCNTs), such as (6,2) and (6,5). We predict efficient MEG in the (6,2) and (6,5) SWCNTs within the solar spectrum range starting at the 2Eg energy threshold and with QE reaching ˜1.6 at about 3Eg, where Eg is the electronic gap.

The Impact of Cloud Computing Technologies in E-learning

Directory of Open Access Journals (Sweden)

Hosam Farouk El-Sofany

2013-01-01

Full Text Available Cloud computing is a new computing model which is based on the grid computing, distributed computing, parallel computing and virtualization technologies define the shape of a new technology. It is the core technology of the next generation of network computing platform, especially in the field of education, cloud computing is the basic environment and platform of the future E-learning. It provides secure data storage, convenient internet services and strong computing power. This article mainly focuses on the research of the application of cloud computing in E-learning environment. The research study shows that the cloud platform is valued for both students and instructors to achieve the course objective. The paper presents the nature, benefits and cloud computing services, as a platform for e-learning environment.

A software radio platform based on ARM and FPGA

Directory of Open Access Journals (Sweden)

Yang Xin.

2016-01-01

Full Text Available The rapid rise in computational performance offered by computer systems has greatly increased the number of practical software radio applications. A scheme presented in this paper is a software radio platform based on ARM and FPGA. FPGA works as the coprocessor together with the ARM, which serves as the core processor. ARM is used for digital signal processing and real-time data transmission, and FPGA is used for synchronous timing control and serial-parallel conversion. A SPI driver for real-time data transmission between ARM and FPGA under ARM-Linux system is provided. By adopting modular design, the software radio platform is capable of implementing wireless communication functions and satisfies the requirements of real-time signal processing platform for high security and broad applicability.

Cloud Based Earth Observation Data Exploitation Platforms

Science.gov (United States)

Romeo, A.; Pinto, S.; Loekken, S.; Marin, A.

2017-12-01

In the last few years data produced daily by several private and public Earth Observation (EO) satellites reached the order of tens of Terabytes, representing for scientists and commercial application developers both a big opportunity for their exploitation and a challenge for their management. New IT technologies, such as Big Data and cloud computing, enable the creation of web-accessible data exploitation platforms, which offer to scientists and application developers the means to access and use EO data in a quick and cost effective way. RHEA Group is particularly active in this sector, supporting the European Space Agency (ESA) in the Exploitation Platforms (EP) initiative, developing technology to build multi cloud platforms for the processing and analysis of Earth Observation data, and collaborating with larger European initiatives such as the European Plate Observing System (EPOS) and the European Open Science Cloud (EOSC). An EP is a virtual workspace, providing a user community with access to (i) large volume of data, (ii) algorithm development and integration environment, (iii) processing software and services (e.g. toolboxes, visualization routines), (iv) computing resources, (v) collaboration tools (e.g. forums, wiki, etc.). When an EP is dedicated to a specific Theme, it becomes a Thematic Exploitation Platform (TEP). Currently, ESA has seven TEPs in a pre-operational phase dedicated to geo-hazards monitoring and prevention, costal zones, forestry areas, hydrology, polar regions, urban areas and food security. On the technology development side, solutions like the multi cloud EO data processing platform provides the technology to integrate ICT resources and EO data from different vendors in a single platform. In particular it offers (i) Multi-cloud data discovery, (ii) Multi-cloud data management and access and (iii) Multi-cloud application deployment. This platform has been demonstrated with the EGI Federated Cloud, Innovation Platform Testbed Poland

KeyWare: an open wireless distributed computing environment

Science.gov (United States)

Shpantzer, Isaac; Schoenfeld, Larry; Grindahl, Merv; Kelman, Vladimir

1995-12-01

Deployment of distributed applications in the wireless domain lack equivalent tools, methodologies, architectures, and network management that exist in LAN based applications. A wireless distributed computing environment (KeyWareTM) based on intelligent agents within a multiple client multiple server scheme was developed to resolve this problem. KeyWare renders concurrent application services to wireline and wireless client nodes encapsulated in multiple paradigms such as message delivery, database access, e-mail, and file transfer. These services and paradigms are optimized to cope with temporal and spatial radio coverage, high latency, limited throughput and transmission costs. A unified network management paradigm for both wireless and wireline facilitates seamless extensions of LAN- based management tools to include wireless nodes. A set of object oriented tools and methodologies enables direct asynchronous invocation of agent-based services supplemented by tool-sets matched to supported KeyWare paradigms. The open architecture embodiment of KeyWare enables a wide selection of client node computing platforms, operating systems, transport protocols, radio modems and infrastructures while maintaining application portability.

IMPROVEMENT OF THE SUPPORTING STRUCTURE OF PLATFORM CAR FOR HIGHER EFFICIENCY OF CONTAINER TRANSPORTATIONS

Directory of Open Access Journals (Sweden)

A. O. Lovska

2017-02-01

Full Text Available Purpose. The article is aimed to improve supporting structures of the platform car to increase the efficiency of container transportations. Methodology. In order to achieve the objective, the strength investigations of the universal platform car of the model 13-401 were conducted, strength reserves of the supporting elements were defined, and more optimal profiles of basic longitudinal beams of the frame in terms of the minimum material capacity were proposed. Decision correctness was confirmed by the strength calculation of the platform car supporting structure at basic loading operational modes and fatigue taking into account the research database of 107 cycles. It has been proposed to equip a platform car with swing fitting stops for fastening containers on the frame, which allows transportation of 20ft and 40ft containers. In order to improve container transportation efficiency along international transport corridors running through Ukraine, a platform car of articulated type has been designed on the base of the improved platform car structure. The mathematical simulation of dynamic loads of the platform car with containers (two 1CC containers at operational loading modes has been carried out, the maximum accelerations influencing the support structure have been defined, and their multiple values have been considered in computer simulation of the strength of the platform car of articulated type. Findings. The support structure of the platform car of articulated type on the basis of the standard platform car has been developed. Refined values of dynamic loads influencing supporting structure the platform car of articulated type with containers at operational loading modes have been obtained; the maximum equivalent stresses in the platform car support structure have been defined. Originality and practical value. A mathematical model of displacements for a platform car of articulated type with containers at operational loading modes of

A Platform for Scalable Satellite and Geospatial Data Analysis

Science.gov (United States)

Beneke, C. M.; Skillman, S.; Warren, M. S.; Kelton, T.; Brumby, S. P.; Chartrand, R.; Mathis, M.

2017-12-01

At Descartes Labs, we use the commercial cloud to run global-scale machine learning applications over satellite imagery. We have processed over 5 Petabytes of public and commercial satellite imagery, including the full Landsat and Sentinel archives. By combining open-source tools with a FUSE-based filesystem for cloud storage, we have enabled a scalable compute platform that has demonstrated reading over 200 GB/s of satellite imagery into cloud compute nodes. In one application, we generated global 15m Landsat-8, 20m Sentinel-1, and 10m Sentinel-2 composites from 15 trillion pixels, using over 10,000 CPUs. We recently created a public open-source Python client library that can be used to query and access preprocessed public satellite imagery from within our platform, and made this platform available to researchers for non-commercial projects. In this session, we will describe how you can use the Descartes Labs Platform for rapid prototyping and scaling of geospatial analyses and demonstrate examples in land cover classification.

Building National eHealth Platforms

DEFF Research Database (Denmark)

Vassilakopoulou, Polyxeni; Grisot, Miria; Jensen, Tina Blegind

2017-01-01

, the coordination of work among multiple contributors, and, the handling of technical heterogeneity within the pre-existing and continuous evolving eHealth landscape. Inclusiveness is related both to the character of public platforms as “common goods”, and, to growth ambitions for public eHealth. The aim...

Monitoring system of multiple fire fighting based on computer vision

Science.gov (United States)

Li, Jinlong; Wang, Li; Gao, Xiaorong; Wang, Zeyong; Zhao, Quanke

2010-10-01

With the high demand of fire control in spacious buildings, computer vision is playing a more and more important role. This paper presents a new monitoring system of multiple fire fighting based on computer vision and color detection. This system can adjust to the fire position and then extinguish the fire by itself. In this paper, the system structure, working principle, fire orientation, hydrant's angle adjusting and system calibration are described in detail; also the design of relevant hardware and software is introduced. At the same time, the principle and process of color detection and image processing are given as well. The system runs well in the test, and it has high reliability, low cost, and easy nodeexpanding, which has a bright prospect of application and popularization.

Comparison of two lecture delivery platforms in a hybrid distance education program.

Science.gov (United States)

Ried, L Douglas; Byers, Katherine

2009-08-28

To compare students' preferences for and academic performance using 2 different distance education course content delivery platforms. A randomized, crossover research design was used to compare traditional video with a 4-panel platform among learners on multiple campuses within 1 college of pharmacy.(1) The outcomes were students' preferences for delivery platform and examination scores. Rasch analysis was used to assess unidimensionality and the difficulty of examination items. Hierarchical logistic and multiple regression models were used to assess students' preferences and academic performance. The logistic model predicting preference for the 4-panel or traditional platform was not significant, but African-Americans and Hispanics were more likely to prefer the 4-panel platform than Caucasian and Asian students. The delivery platform did not impact students' academic performance. Students who did well on the semester's previous 2 examinations scored higher on the questions related to schizophrenia. Students with higher Pharmacy College Admission Test (PCAT) scores performed better on the bipolar questions than students who preferred the traditional video platform. The additional faculty time, effort, and cost invested in presenting the class material in a 4-panel platform, and the students' extra time and effort spent viewing the 4-panel platform did not produce a comparable benefit in student preference and performance.

An algebraic substructuring using multiple shifts for eigenvalue computations

International Nuclear Information System (INIS)

Ko, Jin Hwan; Jung, Sung Nam; Byun, Do Young; Bai, Zhaojun

2008-01-01

Algebraic substructuring (AS) is a state-of-the-art method in eigenvalue computations, especially for large-sized problems, but originally it was designed to calculate only the smallest eigenvalues. Recently, an updated version of AS has been introduced to calculate the interior eigenvalues over a specified range by using a shift concept that is referred to as the shifted AS. In this work, we propose a combined method of both AS and the shifted AS by using multiple shifts for solving a considerable number of eigensolutions in a large-sized problem, which is an emerging computational issue of noise or vibration analysis in vehicle design. In addition, we investigated the accuracy of the shifted AS by presenting an error criterion. The proposed method has been applied to the FE model of an automobile body. The combined method yielded a higher efficiency without loss of accuracy in comparison to the original AS

Comparison of Resource Platform Selection Approaches for Scientific Workflows

Energy Technology Data Exchange (ETDEWEB)

Simmhan, Yogesh; Ramakrishnan, Lavanya

2010-03-05

Cloud computing is increasingly considered as an additional computational resource platform for scientific workflows. The cloud offers opportunity to scale-out applications from desktops and local cluster resources. At the same time, it can eliminate the challenges of restricted software environments and queue delays in shared high performance computing environments. Choosing from these diverse resource platforms for a workflow execution poses a challenge for many scientists. Scientists are often faced with deciding resource platform selection trade-offs with limited information on the actual workflows. While many workflow planning methods have explored task scheduling onto different resources, these methods often require fine-scale characterization of the workflow that is onerous for a scientist. In this position paper, we describe our early exploratory work into using blackbox characteristics to do a cost-benefit analysis across of using cloud platforms. We use only very limited high-level information on the workflow length, width, and data sizes. The length and width are indicative of the workflow duration and parallelism. The data size characterizes the IO requirements. We compare the effectiveness of this approach to other resource selection models using two exemplar scientific workflows scheduled on desktops, local clusters, HPC centers, and clouds. Early results suggest that the blackbox model often makes the same resource selections as a more fine-grained whitebox model. We believe the simplicity of the blackbox model can help inform a scientist on the applicability of cloud computing resources even before porting an existing workflow.

A Big Data Platform for Storing, Accessing, Mining and Learning Geospatial Data

Science.gov (United States)

Yang, C. P.; Bambacus, M.; Duffy, D.; Little, M. M.

2017-12-01

Big Data is becoming a norm in geoscience domains. A platform that is capable to effiently manage, access, analyze, mine, and learn the big data for new information and knowledge is desired. This paper introduces our latest effort on developing such a platform based on our past years' experiences on cloud and high performance computing, analyzing big data, comparing big data containers, and mining big geospatial data for new information. The platform includes four layers: a) the bottom layer includes a computing infrastructure with proper network, computer, and storage systems; b) the 2nd layer is a cloud computing layer based on virtualization to provide on demand computing services for upper layers; c) the 3rd layer is big data containers that are customized for dealing with different types of data and functionalities; d) the 4th layer is a big data presentation layer that supports the effient management, access, analyses, mining and learning of big geospatial data.

Distributed Factorization Computation on Multiple Volunteered Mobile Resource to Break RSA Key

Science.gov (United States)

Jaya, I.; Hardi, S. M.; Tarigan, J. T.; Zamzami, E. M.; Sihombing, P.

2017-01-01

Similar to common asymmeric encryption, RSA can be cracked by usmg a series mathematical calculation. The private key used to decrypt the massage can be computed using the public key. However, finding the private key may require a massive amount of calculation. In this paper, we propose a method to perform a distributed computing to calculate RSA’s private key. The proposed method uses multiple volunteered mobile devices to contribute during the calculation process. Our objective is to demonstrate how the use of volunteered computing on mobile devices may be a feasible option to reduce the time required to break a weak RSA encryption and observe the behavior and running time of the application on mobile devices.

Creating a platform for collaborative genomic research

Directory of Open Access Journals (Sweden)

Mark Smithson

2017-04-01

The developed genomics informatics platform provides a step-change in this type of genetic research, accelerating reproducible collaborative research across multiple disparate organisations and data sources, of varying type and complexity.

Semi-physical Simulation Platform of a Parafoil Nonlinear Dynamic System

International Nuclear Information System (INIS)

Gao Hai-Tao; Yang Sheng-Bo; Zhu Er-Lin; Sun Qing-Lin; Chen Zeng-Qiang; Kang Xiao-Feng

2013-01-01

Focusing on the problems in the process of simulation and experiment on a parafoil nonlinear dynamic system, such as limited methods, high cost and low efficiency we present a semi-physical simulation platform. It is designed by connecting parts of physical objects to a computer, and remedies the defect that a computer simulation is divorced from a real environment absolutely. The main components of the platform and its functions, as well as simulation flows, are introduced. The feasibility and validity are verified through a simulation experiment. The experimental results show that the platform has significance for improving the quality of the parafoil fixed-point airdrop system, shortening the development cycle and saving cost

eTRIKS platform: Conception and operation of a highly scalable cloud-based platform for translational research and applications development.

Science.gov (United States)

Bussery, Justin; Denis, Leslie-Alexandre; Guillon, Benjamin; Liu, Pengfeï; Marchetti, Gino; Rahal, Ghita

2018-04-01

We describe the genesis, design and evolution of a computing platform designed and built to improve the success rate of biomedical translational research. The eTRIKS project platform was developed with the aim of building a platform that can securely host heterogeneous types of data and provide an optimal environment to run tranSMART analytical applications. Many types of data can now be hosted, including multi-OMICS data, preclinical laboratory data and clinical information, including longitudinal data sets. During the last two years, the platform has matured into a robust translational research knowledge management system that is able to host other data mining applications and support the development of new analytical tools. Copyright © 2018 Elsevier Ltd. All rights reserved.

The community FabLab platform: applications and implications in biomedical engineering.

Science.gov (United States)

Stephenson, Makeda K; Dow, Douglas E

2014-01-01

Skill development in science, technology, engineering and math (STEM) education present one of the most formidable challenges of modern society. The Community FabLab platform presents a viable solution. Each FabLab contains a suite of modern computer numerical control (CNC) equipment, electronics and computing hardware and design, programming, computer aided design (CAD) and computer aided machining (CAM) software. FabLabs are community and educational resources and open to the public. Development of STEM based workforce skills such as digital fabrication and advanced manufacturing can be enhanced using this platform. Particularly notable is the potential of the FabLab platform in STEM education. The active learning environment engages and supports a diversity of learners, while the iterative learning that is supported by the FabLab rapid prototyping platform facilitates depth of understanding, creativity, innovation and mastery. The product and project based learning that occurs in FabLabs develops in the student a personal sense of accomplishment, self-awareness, command of the material and technology. This helps build the interest and confidence necessary to excel in STEM and throughout life. Finally the introduction and use of relevant technologies at every stage of the education process ensures technical familiarity and a broad knowledge base needed for work in STEM based fields. Biomedical engineering education strives to cultivate broad technical adeptness, creativity, interdisciplinary thought, and an ability to form deep conceptual understanding of complex systems. The FabLab platform is well designed to enhance biomedical engineering education.

Development of embedded real-time and high-speed vision platform

Science.gov (United States)

Ouyang, Zhenxing; Dong, Yimin; Yang, Hua

2015-12-01

Currently, high-speed vision platforms are widely used in many applications, such as robotics and automation industry. However, a personal computer (PC) whose over-large size is not suitable and applicable in compact systems is an indispensable component for human-computer interaction in traditional high-speed vision platforms. Therefore, this paper develops an embedded real-time and high-speed vision platform, ER-HVP Vision which is able to work completely out of PC. In this new platform, an embedded CPU-based board is designed as substitution for PC and a DSP and FPGA board is developed for implementing image parallel algorithms in FPGA and image sequential algorithms in DSP. Hence, the capability of ER-HVP Vision with size of 320mm x 250mm x 87mm can be presented in more compact condition. Experimental results are also given to indicate that the real-time detection and counting of the moving target at a frame rate of 200 fps at 512 x 512 pixels under the operation of this newly developed vision platform are feasible.

CoreFlow: A computational platform for integration, analysis and modeling of complex biological data

DEFF Research Database (Denmark)

Pasculescu, Adrian; Schoof, Erwin; Creixell, Pau

2014-01-01

between data generation, analysis and manuscript writing. CoreFlow is being released to the scientific community as an open-sourced software package complete with proteomics-specific examples, which include corrections for incomplete isotopic labeling of peptides (SILAC) or arginine-to-proline conversion......A major challenge in mass spectrometry and other large-scale applications is how to handle, integrate, and model the data that is produced. Given the speed at which technology advances and the need to keep pace with biological experiments, we designed a computational platform, CoreFlow, which...... provides programmers with a framework to manage data in real-time. It allows users to upload data into a relational database (MySQL), and to create custom scripts in high-level languages such as R, Python, or Perl for processing, correcting and modeling this data. CoreFlow organizes these scripts...

Analysis of scalability of high-performance 3D image processing platform for virtual colonoscopy.

Science.gov (United States)

Yoshida, Hiroyuki; Wu, Yin; Cai, Wenli

2014-03-19

One of the key challenges in three-dimensional (3D) medical imaging is to enable the fast turn-around time, which is often required for interactive or real-time response. This inevitably requires not only high computational power but also high memory bandwidth due to the massive amount of data that need to be processed. For this purpose, we previously developed a software platform for high-performance 3D medical image processing, called HPC 3D-MIP platform, which employs increasingly available and affordable commodity computing systems such as the multicore, cluster, and cloud computing systems. To achieve scalable high-performance computing, the platform employed size-adaptive, distributable block volumes as a core data structure for efficient parallelization of a wide range of 3D-MIP algorithms, supported task scheduling for efficient load distribution and balancing, and consisted of a layered parallel software libraries that allow image processing applications to share the common functionalities. We evaluated the performance of the HPC 3D-MIP platform by applying it to computationally intensive processes in virtual colonoscopy. Experimental results showed a 12-fold performance improvement on a workstation with 12-core CPUs over the original sequential implementation of the processes, indicating the efficiency of the platform. Analysis of performance scalability based on the Amdahl's law for symmetric multicore chips showed the potential of a high performance scalability of the HPC 3D-MIP platform when a larger number of cores is available.

Consolidation of cloud computing in ATLAS

Science.gov (United States)

Taylor, Ryan P.; Domingues Cordeiro, Cristovao Jose; Giordano, Domenico; Hover, John; Kouba, Tomas; Love, Peter; McNab, Andrew; Schovancova, Jaroslava; Sobie, Randall; ATLAS Collaboration

2017-10-01

Throughout the first half of LHC Run 2, ATLAS cloud computing has undergone a period of consolidation, characterized by building upon previously established systems, with the aim of reducing operational effort, improving robustness, and reaching higher scale. This paper describes the current state of ATLAS cloud computing. Cloud activities are converging on a common contextualization approach for virtual machines, and cloud resources are sharing monitoring and service discovery components. We describe the integration of Vacuum resources, streamlined usage of the Simulation at Point 1 cloud for offline processing, extreme scaling on Amazon compute resources, and procurement of commercial cloud capacity in Europe. Finally, building on the previously established monitoring infrastructure, we have deployed a real-time monitoring and alerting platform which coalesces data from multiple sources, provides flexible visualization via customizable dashboards, and issues alerts and carries out corrective actions in response to problems.

A multilevel control approach for a modular structured space platform

Science.gov (United States)

Chichester, F. D.; Borelli, M. T.

1981-01-01

A three axis mathematical representation of a modular assembled space platform consisting of interconnected discrete masses, including a deployable truss module, was derived for digital computer simulation. The platform attitude control system as developed to provide multilevel control utilizing the Gauss-Seidel second level formulation along with an extended form of linear quadratic regulator techniques. The objectives of the multilevel control are to decouple the space platform's spatial axes and to accommodate the modification of the platform's configuration for each of the decoupled axes.

Engagement, bonding, and identity across multiple platforms: Avaaz on Facebook, YouTube, and MySpace

Directory of Open Access Journals (Sweden)

Anastasia Kavada

2012-03-01

Full Text Available This article explores the role of social media platforms in transnational activism by examining the case of Avaaz.org, an international advocacy organization aiming to bring people-powered politics to global decision-making. Focusing on the Avaaz website, its channel on YouTube, its page on Facebook and its profile page on MySpace, the article investigates the affordances of these platforms for identity-building, bonding, and engagement. The empirical data is derived from features analysis of the selected web platforms, as well as textual analysis of the comments posted by users. The findings show that while social media platforms make individual voices more visible, their design helps Avaaz to maintain a coherent collective voice. In terms of bonding, platforms allow individual activists to communicate with the organization and to spread its message to their existing social networks, but opportunities for private interpersonal communication with other Avaaz supporters are limited.

A computer program for multiple decrement life table analyses.

Science.gov (United States)

Poole, W K; Cooley, P C

1977-06-01

Life table analysis has traditionally been the tool of choice in analyzing distribution of "survival" times when a parametric form for the survival curve could not be reasonably assumed. Chiang, in two papers [1,2] formalized the theory of life table analyses in a Markov chain framework and derived maximum likelihood estimates of the relevant parameters for the analyses. He also discussed how the techniques could be generalized to consider competing risks and follow-up studies. Although various computer programs exist for doing different types of life table analysis [3] to date, there has not been a generally available, well documented computer program to carry out multiple decrement analyses, either by Chiang's or any other method. This paper describes such a program developed by Research Triangle Institute. A user's manual is available at printing costs which supplements the contents of this paper with a discussion of the formula used in the program listing.

Experience using EPICS on PC platforms

International Nuclear Information System (INIS)

Hill, J.O.; Kasemire, K.U.

1997-03-01

The Experimental Physics and Industrial Control System (EPICS) has been widely adopted in the accelerator community. Although EPICS is available on many platforms, the majority of implementations have used UNIX workstations as clients, and VME- or VXI-based processors for distributed input output controllers. Recently, a significant portion of EPICS has been ported to personal computer (PC) hardware platforms running Microsoft's operating systems, and also Wind River System's real time vxWorks operating system. This development should significantly reduce the cost of deploying EPICS systems, and the prospect of using EPICS together with the many high quality commercial components available for PC platforms is also encouraging. A hybrid system using both PC and traditional platforms is currently being implemented at LANL for LEDA, the low energy demonstration accelerator under construction as part of the Accelerator Production of Tritium (APT) project. To illustrate these developments the authors compare their recent experience deploying a PC-based EPICS system with experience deploying similar systems based on traditional (UNIX-hosted) EPICS hardware and software platforms

Computation of subsonic flow around airfoil systems with multiple separation

Science.gov (United States)

Jacob, K.

1982-01-01

A numerical method for computing the subsonic flow around multi-element airfoil systems was developed, allowing for flow separation at one or more elements. Besides multiple rear separation also sort bubbles on the upper surface and cove bubbles can approximately be taken into account. Also, compressibility effects for pure subsonic flow are approximately accounted for. After presentation the method is applied to several examples and improved in some details. Finally, the present limitations and desirable extensions are discussed.

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.

FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.

Science.gov (United States)

Bednar, David; Beerens, Koen; Sebestova, Eva; Bendl, Jaroslav; Khare, Sagar; Chaloupkova, Radka; Prokop, Zbynek; Brezovsky, Jan; Baker, David; Damborsky, Jiri

2015-11-01

There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.

FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.

Directory of Open Access Journals (Sweden)

David Bednar

2015-11-01

Full Text Available There is great interest in increasing proteins' stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt's reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔTm = 24°C and 21°C by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications.

Neural Computations in a Dynamical System with Multiple Time Scales.

Science.gov (United States)

Mi, Yuanyuan; Lin, Xiaohan; Wu, Si

2016-01-01

Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.

A Cross-Platform Tactile Capabilities Interface for Humanoid Robots

Directory of Open Access Journals (Sweden)

Jie eMa

2016-04-01

Full Text Available This article presents the core elements of a cross-platform tactile capabilities interface (TCI for humanoid arms. The aim of the interface is to reduce the cost of developing humanoid robot capabilities by supporting reuse through cross-platform deployment. The article presents a comparative analysis of existing robot middleware frameworks, as well as the technical details of the TCI framework that builds on the the existing YARP platform. The TCI framework currently includes robot arm actuators with robot skin sensors. It presents such hardware in a platform independent manner, making it possible to write robot control software that can be executed on different robots through the TCI frameworks. The TCI framework supports multiple humanoid platforms and this article also presents a case study of a cross-platform implementation of a set of tactile protective withdrawal reflexes that have been realised on both the Nao and iCub humanoid robot platforms using the same high-level source code.

Development of the operational information processing platform

International Nuclear Information System (INIS)

Shin, Hyun Kook; Park, Jeong Seok; Baek, Seung Min; Kim, Young Jin; Joo, Jae Yoon; Lee, Sang Mok; Jeong, Young Woo; Seo, Ho Jun; Kim, Do Youn; Lee, Tae Hoon

1996-02-01

The Operational Information Processing Platform(OIPP) is platform system which was designed to provide the development and operation environments for plant operation and plant monitoring. It is based on the Plant Computer Systems (PCS) of Yonggwang 3 and 4, Ulchin 3 and 4, and Yonggwang 5 and 6 Nuclear Power Plants (NPP). The UNIX based workstation, real time kernel and graphics design tool are selected and installed through the reviewing the function of PCS. In order to construct the development environment for open system architecture and distributed computer system, open computer system architecture was adapted both in hardware and software. For verification of system design and evaluation of technical methodologies, the PCS running under the OIPP is being designed and implemented. In this system, the man-machine interface and system functions are being designed and implemented to evaluate the differences between the UCN 3, 4 PCS and OIPP. 15 tabs., 32 figs., 11 refs. (Author)

Tensions between Individual Use and Network Adoption of Social Media Platforms

DEFF Research Database (Denmark)

Srinivasan, Nikhil; Damsgaard, Jan

2013-01-01

Social media have diffused into the everyday lives of many but still pose challenges to individuals regarding use of these platforms. This paper explores the multiple manners in which social media platforms gets employed by individuals based on an examination of 4 vignettes generated...... by interviewing individuals within a university context. An analysis of the vignettes and individual use behaviors highlights the tension between network-based adoption of social media platforms and the constraints that the network places on individual use of the platform....

The Effect of In-Service Training of Computer Science Teachers on Scratch Programming Language Skills Using an Electronic Learning Platform on Programming Skills and the Attitudes towards Teaching Programming

Science.gov (United States)

Alkaria, Ahmed; Alhassan, Riyadh

2017-01-01

This study was conducted to examine the effect of in-service training of computer science teachers in Scratch language using an electronic learning platform on acquiring programming skills and attitudes towards teaching programming. The sample of this study consisted of 40 middle school computer science teachers. They were assigned into two…

Development of a Computational Steering Framework for High Performance Computing Environments on Blue Gene/P Systems

KAUST Repository

Danani, Bob K.

2012-07-01

Computational steering has revolutionized the traditional workflow in high performance computing (HPC) applications. The standard workflow that consists of preparation of an application’s input, running of a simulation, and visualization of simulation results in a post-processing step is now transformed into a real-time interactive workflow that significantly reduces development and testing time. Computational steering provides the capability to direct or re-direct the progress of a simulation application at run-time. It allows modification of application-defined control parameters at run-time using various user-steering applications. In this project, we propose a computational steering framework for HPC environments that provides an innovative solution and easy-to-use platform, which allows users to connect and interact with running application(s) in real-time. This framework uses RealityGrid as the underlying steering library and adds several enhancements to the library to enable steering support for Blue Gene systems. Included in the scope of this project is the development of a scalable and efficient steering relay server that supports many-to-many connectivity between multiple steered applications and multiple steering clients. Steered applications can range from intermediate simulation and physical modeling applications to complex computational fluid dynamics (CFD) applications or advanced visualization applications. The Blue Gene supercomputer presents special challenges for remote access because the compute nodes reside on private networks. This thesis presents an implemented solution and demonstrates it on representative applications. Thorough implementation details and application enablement steps are also presented in this thesis to encourage direct usage of this framework.

Using the Eclipse Parallel Tools Platform to Assist Earth Science Model Development and Optimization on High Performance Computers

Science.gov (United States)

Alameda, J. C.

2011-12-01

Development and optimization of computational science models, particularly on high performance computers, and with the advent of ubiquitous multicore processor systems, practically on every system, has been accomplished with basic software tools, typically, command-line based compilers, debuggers, performance tools that have not changed substantially from the days of serial and early vector computers. However, model complexity, including the complexity added by modern message passing libraries such as MPI, and the need for hybrid code models (such as openMP and MPI) to be able to take full advantage of high performance computers with an increasing core count per shared memory node, has made development and optimization of such codes an increasingly arduous task. Additional architectural developments, such as many-core processors, only complicate the situation further. In this paper, we describe how our NSF-funded project, "SI2-SSI: A Productive and Accessible Development Workbench for HPC Applications Using the Eclipse Parallel Tools Platform" (WHPC) seeks to improve the Eclipse Parallel Tools Platform, an environment designed to support scientific code development targeted at a diverse set of high performance computing systems. Our WHPC project to improve Eclipse PTP takes an application-centric view to improve PTP. We are using a set of scientific applications, each with a variety of challenges, and using PTP to drive further improvements to both the scientific application, as well as to understand shortcomings in Eclipse PTP from an application developer perspective, to drive our list of improvements we seek to make. We are also partnering with performance tool providers, to drive higher quality performance tool integration. We have partnered with the Cactus group at Louisiana State University to improve Eclipse's ability to work with computational frameworks and extremely complex build systems, as well as to develop educational materials to incorporate into

Cloud Computing: An Overview

Directory of Open Access Journals (Sweden)

Libor Sarga

2012-10-01

Full Text Available As cloud computing is gaining acclaim as a cost-effective alternative to acquiring processing resources for corporations, scientific applications and individuals, various challenges are rapidly coming to the fore. While academia struggles to procure a concise definition, corporations are more interested in competitive advantages it may generate and individuals view it as a way of speeding up data access times or a convenient backup solution. Properties of the cloud architecture largely preclude usage of existing practices while achieving end-users’ and companies’ compliance requires considering multiple infrastructural as well as commercial factors, such as sustainability in case of cloud-side interruptions, identity management and off-site corporate data handling policies. The article overviews recent attempts at formal definitions of cloud computing, summarizes and critically evaluates proposed delimitations, and specifies challenges associated with its further proliferation. Based on the conclusions, future directions in the field of cloud computing are also briefly hypothesized to include deeper focus on community clouds and bolstering innovative cloud-enabled platforms and devices such as tablets, smart phones, as well as entertainment applications.

Evaluating Unmanned Aerial Platforms for Cultural Heritage Large Scale Mapping

Science.gov (United States)

Georgopoulos, A.; Oikonomou, C.; Adamopoulos, E.; Stathopoulou, E. K.

2016-06-01

When it comes to large scale mapping of limited areas especially for cultural heritage sites, things become critical. Optical and non-optical sensors are developed to such sizes and weights that can be lifted by such platforms, like e.g. LiDAR units. At the same time there is an increase in emphasis on solutions that enable users to get access to 3D information faster and cheaper. Considering the multitude of platforms, cameras and the advancement of algorithms in conjunction with the increase of available computing power this challenge should and indeed is further investigated. In this paper a short review of the UAS technologies today is attempted. A discussion follows as to their applicability and advantages, depending on their specifications, which vary immensely. The on-board cameras available are also compared and evaluated for large scale mapping. Furthermore a thorough analysis, review and experimentation with different software implementations of Structure from Motion and Multiple View Stereo algorithms, able to process such dense and mostly unordered sequence of digital images is also conducted and presented. As test data set, we use a rich optical and thermal data set from both fixed wing and multi-rotor platforms over an archaeological excavation with adverse height variations and using different cameras. Dense 3D point clouds, digital terrain models and orthophotos have been produced and evaluated for their radiometric as well as metric qualities.

Computing platform to aid in decision making on energy management projects of the ELETROBRAS; Plataforma computacional para auxilio na tomada de decisao em projetos de gestao energetica da ELETROBRAS

Energy Technology Data Exchange (ETDEWEB)

Assis, T.B.; Rosa, R.B.V.; Pinto, D.P.; Casagrande, C.G. [Universidade Federal de Juiz de Fora, MG (Brazil). Lab. de Eficiencia Energetica], Emails: tbassis@yahoo.com.br, tatobrasil@yahoo.com.br, casagrandejf@yahoo.com.br, danilo.pinto@ufjf.edu.br; Martins, C.C.; Cantarino, M. [Centrais Eletricas Brasileiras S.A. (ELETROBRAS), Rio de Janeiro, RJ (Brazil). Div. de Eficiencia Energetica em Edificacoes], Emails: cmartin@eletrobras.com, marcelo.cantarino@eletrobras.com

2009-07-01

A new tool developed by the Laboratory of Computational Efficiency Energy (LEENER), of the Federal University of Juiz de Fora (UFJF): the SP{sup 3} platform - Planning System of the Public Buildings is presented. This platform, when completed, will help Centrais Eletricas S.A. (ELETROBRAS) in meeting the demand of energetic efficiency projects for public buildings, standardizing data in order to accelerate the approval process and monitoring of a larger number of projects. This article discusses the stages of the platform development, the management methodology used, the goals and outcomes examined with the members of the PROCEL that working on this project.

MASPECTRAS: a platform for management and analysis of proteomics LC-MS/MS data

Directory of Open Access Journals (Sweden)

Rader Robert

2007-06-01

Full Text Available Abstract Background The advancements of proteomics technologies have led to a rapid increase in the number, size and rate at which datasets are generated. Managing and extracting valuable information from such datasets requires the use of data management platforms and computational approaches. Results We have developed the MAss SPECTRometry Analysis System (MASPECTRAS, a platform for management and analysis of proteomics LC-MS/MS data. MASPECTRAS is based on the Proteome Experimental Data Repository (PEDRo relational database schema and follows the guidelines of the Proteomics Standards Initiative (PSI. Analysis modules include: 1 import and parsing of the results from the search engines SEQUEST, Mascot, Spectrum Mill, X! Tandem, and OMSSA; 2 peptide validation, 3 clustering of proteins based on Markov Clustering and multiple alignments; and 4 quantification using the Automated Statistical Analysis of Protein Abundance Ratios algorithm (ASAPRatio. The system provides customizable data retrieval and visualization tools, as well as export to PRoteomics IDEntifications public repository (PRIDE. MASPECTRAS is freely available at http://genome.tugraz.at/maspectras Conclusion Given the unique features and the flexibility due to the use of standard software technology, our platform represents significant advance and could be of great interest to the proteomics community.

Migration of the Almaraz NPP integrated operation management system to a new computer platform

International Nuclear Information System (INIS)

Gonzalez Crego, E.; Martin Lopez-Suevos, C.

1996-01-01

In all power plants, it becomes necessary, with the passage of time, to migrate the initial operation management systems to adapt them to current technologies. That is a good time to improve the inclusion of data in the corporative database and standardize the system interfaces and operation, whilst maintaining data system operability. This article contains Almaraz experience in migrating its Integrated Operation Management System to an advanced computer platform based on open systems (UNIX), communications network (ETHERNET) and database (ORACLE). To this effect, clear objectives and strict standards were established to facilitate the work. The most noteworthy results obtained are: Better quality of information and structure in the corporative database Standardised user interface in all applications. Joint migration of applications for Maintenance, Components and Spare parts, Warehouses and Purchases. Integration of new applications into the system. Introduction of the navigator, which allows movement around the database using all available applications. (Author)

Earth system modelling on system-level heterogeneous architectures: EMAC (version 2.42) on the Dynamical Exascale Entry Platform (DEEP)

Science.gov (United States)

Christou, Michalis; Christoudias, Theodoros; Morillo, Julián; Alvarez, Damian; Merx, Hendrik

2016-09-01

We examine an alternative approach to heterogeneous cluster-computing in the many-core era for Earth system models, using the European Centre for Medium-Range Weather Forecasts Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model as a pilot application on the Dynamical Exascale Entry Platform (DEEP). A set of autonomous coprocessors interconnected together, called Booster, complements a conventional HPC Cluster and increases its computing performance, offering extra flexibility to expose multiple levels of parallelism and achieve better scalability. The EMAC model atmospheric chemistry code (Module Efficiently Calculating the Chemistry of the Atmosphere (MECCA)) was taskified with an offload mechanism implemented using OmpSs directives. The model was ported to the MareNostrum 3 supercomputer to allow testing with Intel Xeon Phi accelerators on a production-size machine. The changes proposed in this paper are expected to contribute to the eventual adoption of Cluster-Booster division and Many Integrated Core (MIC) accelerated architectures in presently available implementations of Earth system models, towards exploiting the potential of a fully Exascale-capable platform.

Virtualization and cloud computing in dentistry.

Science.gov (United States)

Chow, Frank; Muftu, Ali; Shorter, Richard

2014-01-01

The use of virtualization and cloud computing has changed the way we use computers. Virtualization is a method of placing software called a hypervisor on the hardware of a computer or a host operating system. It allows a guest operating system to run on top of the physical computer with a virtual machine (i.e., virtual computer). Virtualization allows multiple virtual computers to run on top of one physical computer and to share its hardware resources, such as printers, scanners, and modems. This increases the efficient use of the computer by decreasing costs (e.g., hardware, electricity administration, and management) since only one physical computer is needed and running. This virtualization platform is the basis for cloud computing. It has expanded into areas of server and storage virtualization. One of the commonly used dental storage systems is cloud storage. Patient information is encrypted as required by the Health Insurance Portability and Accountability Act (HIPAA) and stored on off-site private cloud services for a monthly service fee. As computer costs continue to increase, so too will the need for more storage and processing power. Virtual and cloud computing will be a method for dentists to minimize costs and maximize computer efficiency in the near future. This article will provide some useful information on current uses of cloud computing.

Integrating medicinal chemistry, organic/combinatorial chemistry, and computational chemistry for the discovery of selective estrogen receptor modulators with Forecaster, a novel platform for drug discovery.

Science.gov (United States)

Therrien, Eric; Englebienne, Pablo; Arrowsmith, Andrew G; Mendoza-Sanchez, Rodrigo; Corbeil, Christopher R; Weill, Nathanael; Campagna-Slater, Valérie; Moitessier, Nicolas

2012-01-23

As part of a large medicinal chemistry program, we wish to develop novel selective estrogen receptor modulators (SERMs) as potential breast cancer treatments using a combination of experimental and computational approaches. However, one of the remaining difficulties nowadays is to fully integrate computational (i.e., virtual, theoretical) and medicinal (i.e., experimental, intuitive) chemistry to take advantage of the full potential of both. For this purpose, we have developed a Web-based platform, Forecaster, and a number of programs (e.g., Prepare, React, Select) with the aim of combining computational chemistry and medicinal chemistry expertise to facilitate drug discovery and development and more specifically to integrate synthesis into computer-aided drug design. In our quest for potent SERMs, this platform was used to build virtual combinatorial libraries, filter and extract a highly diverse library from the NCI database, and dock them to the estrogen receptor (ER), with all of these steps being fully automated by computational chemists for use by medicinal chemists. As a result, virtual screening of a diverse library seeded with active compounds followed by a search for analogs yielded an enrichment factor of 129, with 98% of the seeded active compounds recovered, while the screening of a designed virtual combinatorial library including known actives yielded an area under the receiver operating characteristic (AU-ROC) of 0.78. The lead optimization proved less successful, further demonstrating the challenge to simulate structure activity relationship studies.

A novel tablet computer platform for advanced language mapping during awake craniotomy procedures.

Science.gov (United States)

Morrison, Melanie A; Tam, Fred; Garavaglia, Marco M; Golestanirad, Laleh; Hare, Gregory M T; Cusimano, Michael D; Schweizer, Tom A; Das, Sunit; Graham, Simon J

2016-04-01

A computerized platform has been developed to enhance behavioral testing during intraoperative language mapping in awake craniotomy procedures. The system is uniquely compatible with the environmental demands of both the operating room and preoperative functional MRI (fMRI), thus providing standardized testing toward improving spatial agreement between the 2 brain mapping techniques. Details of the platform architecture, its advantages over traditional testing methods, and its use for language mapping are described. Four illustrative cases demonstrate the efficacy of using the testing platform to administer sophisticated language paradigms, and the spatial agreement between intraoperative mapping and preoperative fMRI results. The testing platform substantially improved the ability of the surgeon to detect and characterize language deficits. Use of a written word generation task to assess language production helped confirm areas of speech apraxia and speech arrest that were inadequately characterized or missed with the use of traditional paradigms, respectively. Preoperative fMRI of the analogous writing task was also assistive, displaying excellent spatial agreement with intraoperative mapping in all 4 cases. Sole use of traditional testing paradigms can be limiting during awake craniotomy procedures. Comprehensive assessment of language function will require additional use of more sophisticated and ecologically valid testing paradigms. The platform presented here provides a means to do so.

Big Data in Cloud Computing: A Resource Management Perspective

Directory of Open Access Journals (Sweden)

Saeed Ullah

2018-01-01

Full Text Available The modern day advancement is increasingly digitizing our lives which has led to a rapid growth of data. Such multidimensional datasets are precious due to the potential of unearthing new knowledge and developing decision-making insights from them. Analyzing this huge amount of data from multiple sources can help organizations to plan for the future and anticipate changing market trends and customer requirements. While the Hadoop framework is a popular platform for processing larger datasets, there are a number of other computing infrastructures, available to use in various application domains. The primary focus of the study is how to classify major big data resource management systems in the context of cloud computing environment. We identify some key features which characterize big data frameworks as well as their associated challenges and issues. We use various evaluation metrics from different aspects to identify usage scenarios of these platforms. The study came up with some interesting findings which are in contradiction with the available literature on the Internet.

Distributed hash table theory, platforms and applications

CERN Document Server

Zhang, Hao; Xie, Haiyong; Yu, Nenghai

2013-01-01

This SpringerBrief summarizes the development of Distributed Hash Table in both academic and industrial fields. It covers the main theory, platforms and applications of this key part in distributed systems and applications, especially in large-scale distributed environments. The authors teach the principles of several popular DHT platforms that can solve practical problems such as load balance, multiple replicas, consistency and latency. They also propose DHT-based applications including multicast, anycast, distributed file systems, search, storage, content delivery network, file sharing and c

A survey on platforms for big data analytics.

Science.gov (United States)

Singh, Dilpreet; Reddy, Chandan K

The primary purpose of this paper is to provide an in-depth analysis of different platforms available for performing big data analytics. This paper surveys different hardware platforms available for big data analytics and assesses the advantages and drawbacks of each of these platforms based on various metrics such as scalability, data I/O rate, fault tolerance, real-time processing, data size supported and iterative task support. In addition to the hardware, a detailed description of the software frameworks used within each of these platforms is also discussed along with their strengths and drawbacks. Some of the critical characteristics described here can potentially aid the readers in making an informed decision about the right choice of platforms depending on their computational needs. Using a star ratings table, a rigorous qualitative comparison between different platforms is also discussed for each of the six characteristics that are critical for the algorithms of big data analytics. In order to provide more insights into the effectiveness of each of the platform in the context of big data analytics, specific implementation level details of the widely used k-means clustering algorithm on various platforms are also described in the form pseudocode.

Multiple single-board-computer system for the KEK positron generator control

International Nuclear Information System (INIS)

Nakahara, Kazuo; Abe, Isamu; Enomoto, Atsushi; Otake, Yuji; Urano, Takao

1986-01-01

The KEK positron generator is controlled by means of a distributed microprocessor network. The control system is composed of three kinds of equipment: device controllers for the linac equipment, operation management stations and a communication network. Individual linac equipment has its own microprocessor-based controller. A multiple single board computer (SBC) system is used for communication control and for equipment surveillance; it has a database containing communication and linac equipment status information. The linac operation management that should be the most soft part in the control system, is separated from the multiple SBC system and is carried out by work-stations. The principle that every processor executes only one task is maintained throughout the control system. This made the software architecture very simple. (orig.)

Cloud Service Platform: Hospital Information eXchange(HIX)

OpenAIRE

Fang Zhiyuan; Wei Li

2013-01-01

Health Information eXchange (HIX) is a part of Happiness Cloud Service Platform of Happiness Guangdong in Guangdong Province of China based on innovation of cloud-based business model. This article illustrates the hospital health care business services system based on cloud computing. major business functions of HIX includes integrated mobile medical information services, and mobile health information services. Key cloud service platform capabilities include appointment of HIX registration, d...

Run-time mappig of multiple communicating tasks on MPSoC platforms.

NARCIS (Netherlands)

Singh, A.K.; Jigang, W.; Kumar, A.; Srikanthan, Th.

2010-01-01

Multi-task supported processing elements (PEs) are required in a Multiprocessor System-on-Chip platform for better scalability, power consumption etc. Efficient utilization of PEs needs intelligent mapping of tasks onto them. The job becomes more challenging when the workload of tasks is dynamic.

a Web-Based Interactive Platform for Co-Clustering Spatio-Temporal Data

Science.gov (United States)

Wu, X.; Poorthuis, A.; Zurita-Milla, R.; Kraak, M.-J.

2017-09-01

Since current studies on clustering analysis mainly focus on exploring spatial or temporal patterns separately, a co-clustering algorithm is utilized in this study to enable the concurrent analysis of spatio-temporal patterns. To allow users to adopt and adapt the algorithm for their own analysis, it is integrated within the server side of an interactive web-based platform. The client side of the platform, running within any modern browser, is a graphical user interface (GUI) with multiple linked visualizations that facilitates the understanding, exploration and interpretation of the raw dataset and co-clustering results. Users can also upload their own datasets and adjust clustering parameters within the platform. To illustrate the use of this platform, an annual temperature dataset from 28 weather stations over 20 years in the Netherlands is used. After the dataset is loaded, it is visualized in a set of linked visualizations: a geographical map, a timeline and a heatmap. This aids the user in understanding the nature of their dataset and the appropriate selection of co-clustering parameters. Once the dataset is processed by the co-clustering algorithm, the results are visualized in the small multiples, a heatmap and a timeline to provide various views for better understanding and also further interpretation. Since the visualization and analysis are integrated in a seamless platform, the user can explore different sets of co-clustering parameters and instantly view the results in order to do iterative, exploratory data analysis. As such, this interactive web-based platform allows users to analyze spatio-temporal data using the co-clustering method and also helps the understanding of the results using multiple linked visualizations.

Extracting Synthetic Multi-Cluster Platform Configurations from Grid'5000 for Driving Simulation Experiments

OpenAIRE

Suter , Frédéric; Casanova , Henri

2007-01-01

This report presents a collection of synthetic but realistic distributed computing platform configurations. These configurations are intended for simulation experiments in the study of parallel applications on multi-cluster platforms.

Solving the Problem of Comparing Whole Bacterial Genomes across Different Sequencing Platforms

DEFF Research Database (Denmark)

Kaas, Rolf Sommer; Leekitcharoenphon, Pimlapas; Aarestrup, Frank Møller

2014-01-01

technology because each technology has a systematic bias making integration of data generated from different platforms difficult. We developed two different procedures for identifying variable sites and inferring phylogenies in WGS data across multiple platforms. The methods were evaluated on three bacterial...

Primary intestinal lymphangiectasia: Multiple detector computed tomography findings after direct lymphangiography.

Science.gov (United States)

Sun, Xiaoli; Shen, Wenbin; Chen, Xiaobai; Wen, Tingguo; Duan, Yongli; Wang, Rengui

2017-10-01

To analyse the findings of multiple detector computed tomography (MDCT) after direct lymphangiography in primary intestinal lymphangiectasia (PIL). Fifty-five patients with PIL were retrospectively reviewed. All patients underwent MDCT after direct lymphangiography. The pathologies of 16 patients were confirmed by surgery and the remaining 39 patients were confirmed by gastroendoscopy and/or capsule endoscopy. After direct lymphangiography, MDCT found intra- and extraintestinal as well as lymphatic vessel abnormalities. Among the intra- and extraintestinal disorders, 49 patients had varying degrees of intestinal dilatation, 46 had small bowel wall thickening, 9 had pleural and pericardial effusions, 21 had ascites, 41 had mesenteric oedema, 20 had mesenteric nodules and 9 had abdominal lymphatic cysts. Features of lymphatic vessel abnormalities included intestinal trunk reflux (43.6%, n = 24), lumbar trunk reflux (89.1%, n = 49), pleural and pulmonary lymph reflux (14.5%, n = 8), pericardial and mediastinal lymph reflux (16.4%, n = 9), mediastinal and pulmonary lymph reflux (18.2%, n = 10), and thoracic duct outlet obstruction (90.9%, n = 50). Multiple detector computed tomography after direct lymphangiography provides a safe and accurate examination method and is an excellent tool for the diagnosis of PIL. © 2017 The Royal Australian and New Zealand College of Radiologists.

Silicon CMOS architecture for a spin-based quantum computer.

Science.gov (United States)

Veldhorst, M; Eenink, H G J; Yang, C H; Dzurak, A S

2017-12-15

Recent advances in quantum error correction codes for fault-tolerant quantum computing and physical realizations of high-fidelity qubits in multiple platforms give promise for the construction of a quantum computer based on millions of interacting qubits. However, the classical-quantum interface remains a nascent field of exploration. Here, we propose an architecture for a silicon-based quantum computer processor based on complementary metal-oxide-semiconductor (CMOS) technology. We show how a transistor-based control circuit together with charge-storage electrodes can be used to operate a dense and scalable two-dimensional qubit system. The qubits are defined by the spin state of a single electron confined in quantum dots, coupled via exchange interactions, controlled using a microwave cavity, and measured via gate-based dispersive readout. We implement a spin qubit surface code, showing the prospects for universal quantum computation. We discuss the challenges and focus areas that need to be addressed, providing a path for large-scale quantum computing.

The Changing Role of Data Stewardship in Creating Trustworthy, Interdisciplinary High Performance Data Platforms for the Future.

Science.gov (United States)

Richards, C. J.; Evans, B. J. K.; Wyborn, L. A.; Wang, J.; Trenham, C. E.; Druken, K. A.

2016-12-01

The Australian National Computational Infrastructure (NCI) has ingested over 10PB of national and international environmental, Earth systems science and geophysics reference data onto a single platform to advance high performance data (HPD) techniques that enable interdisciplinary Data-intensive Science. Improved Data Stewardship is critical to evolve both data and data services that support the increasing need for programmatic usability and that prioritises interoperability rather than just traditional data download or portal access. A data platform designed for programmatic access requires quality checked collections that better utilise interoperable data formats and standards. Achieving this involves strategies to meet both the technical and `social' challenges. Aggregating datasets used by different communities and organisations requires satisfying multiple use cases for the broader research community, whilst addressing existing BAU requirements. For NCI, this requires working with data stewards to manage the process of replicating data to the common platform, community representatives and developers to confirm their requirements, and with international peers to better enable globally integrated data communities. It is particularly important to engage with representatives from each community who can work collaboratively to a common goal, as well as capture their community needs, apply quality assurance, determine any barriers to change and to understand priorities. This is critical when managing the aggregation of data collections from multiple producers with different levels of stewardship maturity, technologies and standards, and where organisational barriers can impact the transformation to interoperable and performant data access. To facilitate the management, development and operation of the HPD platform, NCI coordinates technical and domain committees made up of user representatives, data stewards and informatics experts to provide a forum to discuss

KYPO – A Platform for Cyber Defence Exercises

OpenAIRE

Čeleda Pavel; Čegan Jakub; Vykopal Jan; Tovarňák Daniel

2015-01-01

Correct and timely responses to cyber attacks are crucial for the effective implementation of cyber defence strategies and policies. The number of threats and ingenuity of attackers is ever growing, as is the need for more advanced detection tools, techniques and skilled cyber security professionals. KYPO – Cyber Exercise & Research Platform is focused on modelling and simulating complex computer systems and networks in a virtualized and separated environment. The platform enables realist...

Mobile Prototyping Platforms for Remote Engineering Applications

Directory of Open Access Journals (Sweden)

Karsten Henke

2009-08-01

Full Text Available This paper describes a low-cost mobile communication platform as a universal rapid-prototyping system, which is based on the Quadrocopter concept. At the Integrated Hardware and Software Systems Group at the Ilmenau University of Technology these mobile platforms are used to motivate bachelor and master students to study Computer Engineering sciences. This could be done by increasing their interest in technical issues, using this platform as integral part of a new ad-hoc lab to demonstrate different aspects in the area of Mobile Communication as well as universal rapid prototyping nodes to investigate different mechanisms for self-organized mobile communication systems within the International Graduate School on Mobile Communications. Beside the three fields of application, the paper describes the current architecture concept of the mobile prototyping platform as well as the chosen control mechanism and the assigned sensor systems to fulfill all the required tasks.

An algorithm to compute a rule for division problems with multiple references

Directory of Open Access Journals (Sweden)

Sánchez Sánchez, Francisca J.

2012-01-01

Full Text Available In this paper we consider an extension of the classic division problem with claims: Thedivision problem with multiple references. Hinojosa et al. (2012 provide a solution for this type of pro-blems. The aim of this work is to extend their results by proposing an algorithm that calculates allocationsbased on these results. All computational details are provided in the paper.

A wireless computational platform for distributed computing based traffic monitoring involving mixed Eulerian-Lagrangian sensing

KAUST Repository

Jiang, Jiming; Claudel, Christian G.

2013-01-01

.4GHz 802.15.4 ISM compliant radio module, and can be interfaced with fixed traffic sensors, or receive data from vehicle transponders. The platform is specially designed and optimized to be integrated in a solar-powered wireless sensor network in which

SU-D-206-01: Employing a Novel Consensus Optimization Strategy to Achieve Iterative Cone Beam CT Reconstruction On a Multi-GPU Platform

International Nuclear Information System (INIS)

Li, B; Tian, Z; Jiang, S; Jia, X; Zhou, L

2016-01-01

Purpose: While compressed sensing-based cone-beam CT (CBCT) iterative reconstruction techniques have demonstrated tremendous capability of reconstructing high-quality images from undersampled noisy data, its long computation time still hinders wide application in routine clinic. The purpose of this study is to develop a reconstruction framework that employs modern consensus optimization techniques to achieve CBCT reconstruction on a multi-GPU platform for improved computational efficiency. Methods: Total projection data were evenly distributed to multiple GPUs. Each GPU performed reconstruction using its own projection data with a conventional total variation regularization approach to ensure image quality. In addition, the solutions from GPUs were subject to a consistency constraint that they should be identical. We solved the optimization problem with all the constraints considered rigorously using an alternating direction method of multipliers (ADMM) algorithm. The reconstruction framework was implemented using OpenCL on a platform with two Nvidia GTX590 GPU cards, each with two GPUs. We studied the performance of our method and demonstrated its advantages through a simulation case with a NCAT phantom and an experimental case with a Catphan phantom. Result: Compared with the CBCT images reconstructed using conventional FDK method with full projection datasets, our proposed method achieved comparable image quality with about one third projection numbers. The computation time on the multi-GPU platform was ∼55 s and ∼ 35 s in the two cases respectively, achieving a speedup factor of ∼ 3.0 compared with single GPU reconstruction. Conclusion: We have developed a consensus ADMM-based CBCT reconstruction method which enabled performing reconstruction on a multi-GPU platform. The achieved efficiency made this method clinically attractive.

SU-D-206-01: Employing a Novel Consensus Optimization Strategy to Achieve Iterative Cone Beam CT Reconstruction On a Multi-GPU Platform

Energy Technology Data Exchange (ETDEWEB)

Li, B [University of Texas Southwestern Medical Center, Dallas, TX (United States); Southern Medical University, Guangzhou, Guangdong (China); Tian, Z; Jiang, S; Jia, X [University of Texas Southwestern Medical Center, Dallas, TX (United States); Zhou, L [Southern Medical University, Guangzhou, Guangdong (China)

2016-06-15

Purpose: While compressed sensing-based cone-beam CT (CBCT) iterative reconstruction techniques have demonstrated tremendous capability of reconstructing high-quality images from undersampled noisy data, its long computation time still hinders wide application in routine clinic. The purpose of this study is to develop a reconstruction framework that employs modern consensus optimization techniques to achieve CBCT reconstruction on a multi-GPU platform for improved computational efficiency. Methods: Total projection data were evenly distributed to multiple GPUs. Each GPU performed reconstruction using its own projection data with a conventional total variation regularization approach to ensure image quality. In addition, the solutions from GPUs were subject to a consistency constraint that they should be identical. We solved the optimization problem with all the constraints considered rigorously using an alternating direction method of multipliers (ADMM) algorithm. The reconstruction framework was implemented using OpenCL on a platform with two Nvidia GTX590 GPU cards, each with two GPUs. We studied the performance of our method and demonstrated its advantages through a simulation case with a NCAT phantom and an experimental case with a Catphan phantom. Result: Compared with the CBCT images reconstructed using conventional FDK method with full projection datasets, our proposed method achieved comparable image quality with about one third projection numbers. The computation time on the multi-GPU platform was ∼55 s and ∼ 35 s in the two cases respectively, achieving a speedup factor of ∼ 3.0 compared with single GPU reconstruction. Conclusion: We have developed a consensus ADMM-based CBCT reconstruction method which enabled performing reconstruction on a multi-GPU platform. The achieved efficiency made this method clinically attractive.

Consolidation of Cloud Computing in ATLAS

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00224309; The ATLAS collaboration; Cordeiro, Cristovao; Di Girolamo, Alessandro; Hover, John; Kouba, Tomas; Love, Peter; Mcnab, Andrew; Schovancova, Jaroslava; Sobie, Randall

2016-01-01

Throughout the first year of LHC Run 2, ATLAS Cloud Computing has undergone a period of consolidation, characterized by building upon previously established systems, with the aim of reducing operational effort, improving robustness, and reaching higher scale. This paper describes the current state of ATLAS Cloud Computing. Cloud activities are converging on a common contextualization approach for virtual machines, and cloud resources are sharing monitoring and service discovery components. We describe the integration of Vac resources, streamlined usage of the High Level Trigger cloud for simulation and reconstruction, extreme scaling on Amazon EC2, and procurement of commercial cloud capacity in Europe. Building on the previously established monitoring infrastructure, we have deployed a real-time monitoring and alerting platform which coalesces data from multiple sources, provides flexible visualization via customizable dashboards, and issues alerts and carries out corrective actions in response to problems. ...

Porting of a serial molecular dynamics code on MIMD platforms

Energy Technology Data Exchange (ETDEWEB)

Celino, M. [ENEA Centro Ricerche Casaccia, S. Maria di Galeria, RM (Italy). HPCN Project

1999-07-01

A molecular dynamics (MD) code, utilized for the study of atomistic models of metallic systems has been parallelized for MIMD (multiple instructions multiple data) parallel platforms by means of the parallel virtual machine (PVM) message passing library. Since the parallelization implies modifications of the sequential algorithms, these are described from the point of view of the statistical mechanical theory. Furthermore, techniques and parallelization strategies utilized and the MD parallel code are described in detail. Benchmarks on several MIMD platforms (IBM SP1, SP2, Cray T3D, cluster of workstations) allow performances evaluation of the code versus the different characteristics of the parallel platforms. [Italian] Un codice seriale di dinamica molecolare (MD) utilizzato per lo studio di modelli atomici di materiali metallici e' stato parallelizzato per piattaforme parallele MIMD (multiple instructions multiple data) utilizzando librerie del parallel virtual machine (PVM). Poiche' l'operazione di parallelizzazione ha implicato la modifica degli algoritmi seriali del codice, questi vengono descritti ripercorrendo i concetti fondamentali della meccanica statistica. Inoltre sono presentate le tecniche e le strategie di parallelizzazione utilizzate descrivendo in dettaglio il codice parallelo di MD: Risultati di benchmark su diverse piattaforme MIMD (IBM SP1, SP2, Cray T3D, cluster of workstations) permettono di analizzare le performances del codice in funzione delle differenti caratteristiche delle piattaforme parallele.

ATLAS Analytics and Machine Learning Platforms

CERN Document Server

Vukotic, Ilija; The ATLAS collaboration; Legger, Federica; Gardner, Robert

2018-01-01

In 2015 ATLAS Distributed Computing started to migrate its monitoring systems away from Oracle DB and decided to adopt new big data platforms that are open source, horizontally scalable, and offer the flexibility of NoSQL systems. Three years later, the full software stack is in place, the system is considered in production and operating at near maximum capacity (in terms of storage capacity and tightly coupled analysis capability). The new model provides several tools for fast and easy to deploy monitoring and accounting. The main advantages are: ample ways to do complex analytics studies (using technologies such as java, pig, spark, python, jupyter), flexibility in reorganization of data flows, near real time and inline processing. The analytics studies improve our understanding of different computing systems and their interplay, thus enabling whole-system debugging and optimization. In addition, the platform provides services to alarm or warn on anomalous conditions, and several services closing feedback l...

Cloud Computing Fundamentals

Science.gov (United States)

Furht, Borko

In the introductory chapter we define the concept of cloud computing and cloud services, and we introduce layers and types of cloud computing. We discuss the differences between cloud computing and cloud services. New technologies that enabled cloud computing are presented next. We also discuss cloud computing features, standards, and security issues. We introduce the key cloud computing platforms, their vendors, and their offerings. We discuss cloud computing challenges and the future of cloud computing.

GPUs: An Emerging Platform for General-Purpose Computation

Science.gov (United States)

2007-08-01

programming; real-time cinematic quality graphics Peak stream (26) License required (limited time no- cost evaluation program) Commercially...folding.stanford.edu (accessed 30 March 2007). 2. Fan, Z.; Qiu, F.; Kaufman, A.; Yoakum-Stover, S. GPU Cluster for High Performance Computing. ACM/IEEE...accessed 30 March 2007). 8. Goodnight, N.; Wang, R.; Humphreys, G. Computation on Programmable Graphics Hardware. IEEE Computer Graphics and

ClustalXeed: a GUI-based grid computation version for high performance and terabyte size multiple sequence alignment

Directory of Open Access Journals (Sweden)

Kim Taeho

2010-09-01

Full Text Available Abstract Background There is an increasing demand to assemble and align large-scale biological sequence data sets. The commonly used multiple sequence alignment programs are still limited in their ability to handle very large amounts of sequences because the system lacks a scalable high-performance computing (HPC environment with a greatly extended data storage capacity. Results We designed ClustalXeed, a software system for multiple sequence alignment with incremental improvements over previous versions of the ClustalX and ClustalW-MPI software. The primary advantage of ClustalXeed over other multiple sequence alignment software is its ability to align a large family of protein or nucleic acid sequences. To solve the conventional memory-dependency problem, ClustalXeed uses both physical random access memory (RAM and a distributed file-allocation system for distance matrix construction and pair-align computation. The computation efficiency of disk-storage system was markedly improved by implementing an efficient load-balancing algorithm, called "idle node-seeking task algorithm" (INSTA. The new editing option and the graphical user interface (GUI provide ready access to a parallel-computing environment for users who seek fast and easy alignment of large DNA and protein sequence sets. Conclusions ClustalXeed can now compute a large volume of biological sequence data sets, which were not tractable in any other parallel or single MSA program. The main developments include: 1 the ability to tackle larger sequence alignment problems than possible with previous systems through markedly improved storage-handling capabilities. 2 Implementing an efficient task load-balancing algorithm, INSTA, which improves overall processing times for multiple sequence alignment with input sequences of non-uniform length. 3 Support for both single PC and distributed cluster systems.

A Versatile Integrated Ambient Ionization Source Platform

Science.gov (United States)

Ai, Wanpeng; Nie, Honggang; Song, Shiyao; Liu, Xiaoyun; Bai, Yu; Liu, Huwei

2018-04-01

The pursuit of high-throughput sample analysis from complex matrix demands development of multiple ionization techniques with complementary specialties. A versatile integrated ambient ionization source (iAmIS) platform is proposed in this work, based on the idea of integrating multiple functions, enhancing the efficiency of current ionization techniques, extending the applications, and decreasing the cost of the instrument. The design of the iAmIS platform combines flowing atmospheric pressure afterglow (FAPA) source/direct analysis in real time (DART), dielectric barrier discharge ionization (DBDI)/low-temperature plasma (LTP), desorption electrospray ionization (DESI), and laser desorption (LD) technique. All individual and combined ionization modes can be easily attained by modulating parameters. In particular, the FAPA/DART&DESI mode can realize the detection of polar and nonpolar compounds at the same time with two different ionization mechanisms: proton transfer and charge transfer. The introduction of LD contributes to the mass spectrometry imaging and the surface-assisted laser desorption (SALDI) under ambient condition. Compared with other individual or multi-mode ion source, the iAmIS platform provides the flexibility of choosing different ionization modes, broadens the scope of the analyte detection, and facilitates the analysis of complex samples. [Figure not available: see fulltext.

Data Mining Based on Cloud-Computing Technology

Directory of Open Access Journals (Sweden)

Ren Ying

2016-01-01

Full Text Available There are performance bottlenecks and scalability problems when traditional data-mining system is used in cloud computing. In this paper, we present a data-mining platform based on cloud computing. Compared with a traditional data mining system, this platform is highly scalable, has massive data processing capacities, is service-oriented, and has low hardware cost. This platform can support the design and applications of a wide range of distributed data-mining systems.

Multiple-Choice versus Constructed-Response Tests in the Assessment of Mathematics Computation Skills.

Science.gov (United States)

Gadalla, Tahany M.

The equivalence of multiple-choice (MC) and constructed response (discrete) (CR-D) response formats as applied to mathematics computation at grade levels two to six was tested. The difference between total scores from the two response formats was tested for statistical significance, and the factor structure of items in both response formats was…

Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

Science.gov (United States)

Lane, Peter C. R.; Gobet, Fernand

2013-03-01

Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.

NMRFx Processor: a cross-platform NMR data processing program

International Nuclear Information System (INIS)

Norris, Michael; Fetler, Bayard; Marchant, Jan; Johnson, Bruce A.

2016-01-01

NMRFx Processor is a new program for the processing of NMR data. Written in the Java programming language, NMRFx Processor is a cross-platform application and runs on Linux, Mac OS X and Windows operating systems. The application can be run in both a graphical user interface (GUI) mode and from the command line. Processing scripts are written in the Python programming language and executed so that the low-level Java commands are automatically run in parallel on computers with multiple cores or CPUs. Processing scripts can be generated automatically from the parameters of NMR experiments or interactively constructed in the GUI. A wide variety of processing operations are provided, including methods for processing of non-uniformly sampled datasets using iterative soft thresholding. The interactive GUI also enables the use of the program as an educational tool for teaching basic and advanced techniques in NMR data analysis.

NMRFx Processor: a cross-platform NMR data processing program

Energy Technology Data Exchange (ETDEWEB)

Norris, Michael; Fetler, Bayard [One Moon Scientific, Inc. (United States); Marchant, Jan [University of Maryland Baltimore County, Howard Hughes Medical Institute (United States); Johnson, Bruce A., E-mail: bruce.johnson@asrc.cuny.edu [One Moon Scientific, Inc. (United States)

2016-08-15

NMRFx Processor is a new program for the processing of NMR data. Written in the Java programming language, NMRFx Processor is a cross-platform application and runs on Linux, Mac OS X and Windows operating systems. The application can be run in both a graphical user interface (GUI) mode and from the command line. Processing scripts are written in the Python programming language and executed so that the low-level Java commands are automatically run in parallel on computers with multiple cores or CPUs. Processing scripts can be generated automatically from the parameters of NMR experiments or interactively constructed in the GUI. A wide variety of processing operations are provided, including methods for processing of non-uniformly sampled datasets using iterative soft thresholding. The interactive GUI also enables the use of the program as an educational tool for teaching basic and advanced techniques in NMR data analysis.

The computer-aided design of a servo system as a multiple-criteria decision problem

NARCIS (Netherlands)

Udink ten Cate, A.J.

1986-01-01

This paper treats the selection of controller gains of a servo system as a multiple-criteria decision problem. In contrast to the usual optimization-based approaches to computer-aided design, inequality constraints are included in the problem as unconstrained objectives. This considerably simplifies

Optical RISC computer

Science.gov (United States)

Guilfoyle, Peter S.; Stone, Richard V.; Hessenbruch, John M.; Zeise, Frederick F.

1993-07-01

A second generation digital optical computer (DOC II) has been developed which utilizes a RISC based operating system as its host. This 32 bit, high performance (12.8 GByte/sec), computing platform demonstrates a number of basic principals that are inherent to parallel free space optical interconnects such as speed (up to 1012 bit operations per second) and low power 1.2 fJ per bit). Although DOC II is a general purpose machine, special purpose applications have been developed and are currently being evaluated on the optical platform.

A Lévy HJM Multiple-Curve Model with Application to CVA Computation

DEFF Research Database (Denmark)

Crépey, Stéphane; Grbac, Zorana; Ngor, Nathalie

2015-01-01

, the calibration to OTM swaptions guaranteeing that the model correctly captures volatility smile effects and the calibration to co-terminal ATM swaptions ensuring an appropriate term structure of the volatility in the model. To account for counterparty risk and funding issues, we use the calibrated multiple......-curve model as an underlying model for CVA computation. We follow a reduced-form methodology through which the problem of pricing the counterparty risk and funding costs can be reduced to a pre-default Markovian BSDE, or an equivalent semi-linear PDE. As an illustration, we study the case of a basis swap...... and a related swaption, for which we compute the counterparty risk and funding adjustments...

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,…

Computation of large covariance matrices by SAMMY on graphical processing units and multicore CPUs

International Nuclear Information System (INIS)

Arbanas, G.; Dunn, M.E.; Wiarda, D.

2011-01-01

Computational power of Graphical Processing Units and multicore CPUs was harnessed by the nuclear data evaluation code SAMMY to speed up computations of large Resonance Parameter Covariance Matrices (RPCMs). This was accomplished by linking SAMMY to vendor-optimized implementations of the matrix-matrix multiplication subroutine of the Basic Linear Algebra Library to compute the most time-consuming step. The 235 U RPCM computed previously using a triple-nested loop was re-computed using the NVIDIA implementation of the subroutine on a single Tesla Fermi Graphical Processing Unit, and also using the Intel's Math Kernel Library implementation on two different multicore CPU systems. A multiplication of two matrices of dimensions 16,000×20,000 that had previously taken days, took approximately one minute on the GPU. Comparable performance was achieved on a dual six-core CPU system. The magnitude of the speed-up suggests that these, or similar, combinations of hardware and libraries may be useful for large matrix operations in SAMMY. Uniform interfaces of standard linear algebra libraries make them a promising candidate for a programming framework of a new generation of SAMMY for the emerging heterogeneous computing platforms. (author)

Computation of large covariance matrices by SAMMY on graphical processing units and multicore CPUs

Energy Technology Data Exchange (ETDEWEB)

Arbanas, G.; Dunn, M.E.; Wiarda, D., E-mail: arbanasg@ornl.gov, E-mail: dunnme@ornl.gov, E-mail: wiardada@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States)

2011-07-01

Computational power of Graphical Processing Units and multicore CPUs was harnessed by the nuclear data evaluation code SAMMY to speed up computations of large Resonance Parameter Covariance Matrices (RPCMs). This was accomplished by linking SAMMY to vendor-optimized implementations of the matrix-matrix multiplication subroutine of the Basic Linear Algebra Library to compute the most time-consuming step. The {sup 235}U RPCM computed previously using a triple-nested loop was re-computed using the NVIDIA implementation of the subroutine on a single Tesla Fermi Graphical Processing Unit, and also using the Intel's Math Kernel Library implementation on two different multicore CPU systems. A multiplication of two matrices of dimensions 16,000×20,000 that had previously taken days, took approximately one minute on the GPU. Comparable performance was achieved on a dual six-core CPU system. The magnitude of the speed-up suggests that these, or similar, combinations of hardware and libraries may be useful for large matrix operations in SAMMY. Uniform interfaces of standard linear algebra libraries make them a promising candidate for a programming framework of a new generation of SAMMY for the emerging heterogeneous computing platforms. (author)

[Porting Radiotherapy Software of Varian to Cloud Platform].

Science.gov (United States)

Zou, Lian; Zhang, Weisha; Liu, Xiangxiang; Xie, Zhao; Xie, Yaoqin

2017-09-30

To develop a low-cost private cloud platform of radiotherapy software. First, a private cloud platform which was based on OpenStack and the virtual GPU hardware was builded. Then on the private cloud platform, all the Varian radiotherapy software modules were installed to the virtual machine, and the corresponding function configuration was completed. Finally the software on the cloud was able to be accessed by virtual desktop client. The function test results of the cloud workstation show that a cloud workstation is equivalent to an isolated physical workstation, and any clients on the LAN can use the cloud workstation smoothly. The cloud platform transplantation in this study is economical and practical. The project not only improves the utilization rates of radiotherapy software, but also makes it possible that the cloud computing technology can expand its applications to the field of radiation oncology.

Technical Note: SCUDA: A software platform for cumulative dose assessment

Energy Technology Data Exchange (ETDEWEB)

Park, Seyoun; McNutt, Todd; Quon, Harry; Wong, John; Lee, Junghoon, E-mail: rshekhar@childrensnational.org, E-mail: junghoon@jhu.edu [Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland 21231 (United States); Plishker, William [IGI Technologies, Inc., College Park, Maryland 20742 (United States); Shekhar, Raj, E-mail: rshekhar@childrensnational.org, E-mail: junghoon@jhu.edu [IGI Technologies, Inc., College Park, Maryland 20742 and Sheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Health System, Washington, DC 20010 (United States)

2016-10-15

Purpose: Accurate tracking of anatomical changes and computation of actually delivered dose to the patient are critical for successful adaptive radiation therapy (ART). Additionally, efficient data management and fast processing are practically important for the adoption in clinic as ART involves a large amount of image and treatment data. The purpose of this study was to develop an accurate and efficient Software platform for CUmulative Dose Assessment (SCUDA) that can be seamlessly integrated into the clinical workflow. Methods: SCUDA consists of deformable image registration (DIR), segmentation, dose computation modules, and a graphical user interface. It is connected to our image PACS and radiotherapy informatics databases from which it automatically queries/retrieves patient images, radiotherapy plan, beam data, and daily treatment information, thus providing an efficient and unified workflow. For accurate registration of the planning CT and daily CBCTs, the authors iteratively correct CBCT intensities by matching local intensity histograms during the DIR process. Contours of the target tumor and critical structures are then propagated from the planning CT to daily CBCTs using the computed deformations. The actual delivered daily dose is computed using the registered CT and patient setup information by a superposition/convolution algorithm, and accumulated using the computed deformation fields. Both DIR and dose computation modules are accelerated by a graphics processing unit. Results: The cumulative dose computation process has been validated on 30 head and neck (HN) cancer cases, showing 3.5 ± 5.0 Gy (mean±STD) absolute mean dose differences between the planned and the actually delivered doses in the parotid glands. On average, DIR, dose computation, and segmentation take 20 s/fraction and 17 min for a 35-fraction treatment including additional computation for dose accumulation. Conclusions: The authors developed a unified software platform that provides

High-throughput landslide modelling using computational grids

Science.gov (United States)

Wallace, M.; Metson, S.; Holcombe, L.; Anderson, M.; Newbold, D.; Brook, N.

2012-04-01

Landslides are an increasing problem in developing countries. Multiple landslides can be triggered by heavy rainfall resulting in loss of life, homes and critical infrastructure. Through computer simulation of individual slopes it is possible to predict the causes, timing and magnitude of landslides and estimate the potential physical impact. Geographical scientists at the University of Bristol have developed software that integrates a physically-based slope hydrology and stability model (CHASM) with an econometric model (QUESTA) in order to predict landslide risk over time. These models allow multiple scenarios to be evaluated for each slope, accounting for data uncertainties, different engineering interventions, risk management approaches and rainfall patterns. Individual scenarios can be computationally intensive, however each scenario is independent and so multiple scenarios can be executed in parallel. As more simulations are carried out the overhead involved in managing input and output data becomes significant. This is a greater problem if multiple slopes are considered concurrently, as is required both for landslide research and for effective disaster planning at national levels. There are two critical factors in this context: generated data volumes can be in the order of tens of terabytes, and greater numbers of simulations result in long total runtimes. Users of such models, in both the research community and in developing countries, need to develop a means for handling the generation and submission of landside modelling experiments, and the storage and analysis of the resulting datasets. Additionally, governments in developing countries typically lack the necessary computing resources and infrastructure. Consequently, knowledge that could be gained by aggregating simulation results from many different scenarios across many different slopes remains hidden within the data. To address these data and workload management issues, University of Bristol particle

Data analytics in the ATLAS Distributed Computing

CERN Document Server

Vukotic, Ilija; The ATLAS collaboration; Bryant, Lincoln

2015-01-01

The ATLAS Data analytics effort is focused on creating systems which provide the ATLAS ADC with new capabilities for understanding distributed systems and overall operational performance. These capabilities include: warehousing information from multiple systems (the production and distributed analysis system - PanDA, the distributed data management system - Rucio, the file transfer system, various monitoring services etc. ); providing a platform to execute arbitrary data mining and machine learning algorithms over aggregated data; satisfy a variety of use cases for different user roles; host new third party analytics services on a scalable compute platform. We describe the implemented system where: data sources are existing RDBMS (Oracle) and Flume collectors; a Hadoop cluster is used to store the data; native Hadoop and Apache Pig scripts are used for data aggregation; and R for in-depth analytics. Part of the data is indexed in ElasticSearch so both simpler investigations and complex dashboards can be made ...

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.

The Core Interaction of Platforms: How Startups Connect Users and Producers

Directory of Open Access Journals (Sweden)

Heidi M. E. Korhonen

2017-09-01

Full Text Available The platform economy is disrupting innovation while presenting both opportunities and challenges for startups. Platforms support value creation between multiple participant groups, and this operationalization of an ecosystem’s value co-creation represents the “core interaction” of a platform. This article focuses on that core interaction and studies how startups connect producers and users in value-creating core interaction through digital platforms. The study is based on an analysis of 29 cases of platform startups interviewed at a leading European startup event. The studied startups were envisioning even millions of users and hundreds or thousands of producers co-creating value on their platforms. In such platform businesses, our results highlight the importance of attracting a large user pool, providing novel services to those users, offering a new market for producers, supporting the core interaction in various ways, and utilizing elements of the platform canvas – an adaptation of the business model canvas, which we have accommodated for platform-based business models – to accomplish these goals.

The Study of Multifunction External Fixator Based on Stewart Platform

Directory of Open Access Journals (Sweden)

Guo Yue

2015-01-01

Full Text Available The article develops the model of bone deformities, making 6-DOF Parallel Mechanism have widely applied to correction of deformities. The platform’s positional direct solution is the posture of the motion platform. Malformation can be measured by X-ray, based on the space coordinate transformation can find the final posture of the motion platform. Regarding the reverse solution to platform kinematics the paper gives a quick arithmetic program, six actuators to realize motion requirements. For the computer-assisted fracture reduction, we produced an application interface.

Essentials of cloud computing

CERN Document Server

Chandrasekaran, K

2014-01-01

ForewordPrefaceComputing ParadigmsLearning ObjectivesPreambleHigh-Performance ComputingParallel ComputingDistributed ComputingCluster ComputingGrid ComputingCloud ComputingBiocomputingMobile ComputingQuantum ComputingOptical ComputingNanocomputingNetwork ComputingSummaryReview PointsReview QuestionsFurther ReadingCloud Computing FundamentalsLearning ObjectivesPreambleMotivation for Cloud ComputingThe Need for Cloud ComputingDefining Cloud ComputingNIST Definition of Cloud ComputingCloud Computing Is a ServiceCloud Computing Is a Platform5-4-3 Principles of Cloud computingFive Essential Charact

A User-Centered Mobile Cloud Computing Platform for Improving Knowledge Management in Small-to-Medium Enterprises in the Chilean Construction Industry

Directory of Open Access Journals (Sweden)

Daniela Núñez

2018-03-01

Full Text Available Knowledge management (KM is a key element for the development of small-to-medium enterprises (SMEs in the construction industry. This is particularly relevant in Chile, where this industry is composed almost entirely of SMEs. Although various KM system proposals can be found in the literature, they are not suitable for SMEs, due to usability problems, budget constraints, and time and connectivity issues. Mobile Cloud Computing (MCC systems offer several advantages to construction SMEs, but they have not yet been exploited to address KM needs. Therefore, this research is aimed at the development of a MCC-based KM platform to manage lessons learned in different construction projects of SMEs, through an iterative and user-centered methodology. Usability and quality evaluations of the proposed platform show that MCC is a feasible and attractive option to address the KM issues in SMEs of the Chilean construction industry, since it is possible to consider both technical and usability requirements.

Combating Ebola with Repurposed Therapeutics Using the CANDO Platform

Directory of Open Access Journals (Sweden)

Gaurav Chopra

2016-11-01

Full Text Available Ebola virus disease (EVD is extremely virulent with an estimated mortality rate of up to 90%. However, the state-of-the-art treatment for EVD is limited to quarantine and supportive care. The 2014 Ebola epidemic in West Africa, the largest in history, is believed to have caused more than 11,000 fatalities. The countries worst affected are also among the poorest in the world. Given the complexities, time, and resources required for a novel drug development, finding efficient drug discovery pathways is going to be crucial in the fight against future outbreaks. We have developed a Computational Analysis of Novel Drug Opportunities (CANDO platform based on the hypothesis that drugs function by interacting with multiple protein targets to create a molecular interaction signature that can be exploited for rapid therapeutic repurposing and discovery. We used the CANDO platform to identify and rank FDA-approved drug candidates that bind and inhibit all proteins encoded by the genomes of five different Ebola virus strains. Top ranking drug candidates for EVD treatment generated by CANDO were compared to in vitro screening studies against Ebola virus-like particles (VLPs by Kouznetsova et al. and genetically engineered Ebola virus and cell viability studies by Johansen et al. to identify drug overlaps between the in virtuale and in vitro studies as putative treatments for future EVD outbreaks. Our results indicate that integrating computational docking predictions on a proteomic scale with results from in vitro screening studies may be used to select and prioritize compounds for further in vivo and clinical testing. This approach will significantly reduce the lead time, risk, cost, and resources required to determine efficacious therapies against future EVD outbreaks.

On Combining Multiple-Instance Learning and Active Learning for Computer-Aided Detection of Tuberculosis

NARCIS (Netherlands)

Melendez Rodriguez, J.C.; Ginneken, B. van; Maduskar, P.; Philipsen, R.H.H.M.; Ayles, H.; Sanchez, C.I.

2016-01-01

The major advantage of multiple-instance learning (MIL) applied to a computer-aided detection (CAD) system is that it allows optimizing the latter with case-level labels instead of accurate lesion outlines as traditionally required for a supervised approach. As shown in previous work, a MIL-based

Web Platform for Sharing Modeling Software in the Field of Nonlinear Optics

Directory of Open Access Journals (Sweden)

Dubenskaya Julia

2018-01-01

Full Text Available We describe the prototype of a Web platform intended for sharing software programs for computer modeling in the rapidly developing field of the nonlinear optics phenomena. The suggested platform is built on the top of the HUBZero open-source middleware. In addition to the basic HUBZero installation we added to our platform the capability to run Docker containers via an external application server and to send calculation programs to those containers for execution. The presented web platform provides a wide range of features and might be of benefit to nonlinear optics researchers.

Web Platform for Sharing Modeling Software in the Field of Nonlinear Optics

Science.gov (United States)

Dubenskaya, Julia; Kryukov, Alexander; Demichev, Andrey

2018-02-01

We describe the prototype of a Web platform intended for sharing software programs for computer modeling in the rapidly developing field of the nonlinear optics phenomena. The suggested platform is built on the top of the HUBZero open-source middleware. In addition to the basic HUBZero installation we added to our platform the capability to run Docker containers via an external application server and to send calculation programs to those containers for execution. The presented web platform provides a wide range of features and might be of benefit to nonlinear optics researchers.

XRCC1 and PCNA are loading platforms with distinct kinetic properties and different capacities to respond to multiple DNA lesions

Directory of Open Access Journals (Sweden)

Leonhardt Heinrich

2007-09-01

Full Text Available Abstract Background Genome integrity is constantly challenged and requires the coordinated recruitment of multiple enzyme activities to ensure efficient repair of DNA lesions. We investigated the dynamics of XRCC1 and PCNA that act as molecular loading platforms and play a central role in this coordination. Results Local DNA damage was introduced by laser microirradation and the recruitment of fluorescent XRCC1 and PCNA fusion proteins was monitored by live cell microscopy. We found an immediate and fast recruitment of XRCC1 preceding the slow and continuous recruitment of PCNA. Fluorescence bleaching experiments (FRAP and FLIP revealed a stable association of PCNA with DNA repair sites, contrasting the high turnover of XRCC1. When cells were repeatedly challenged with multiple DNA lesions we observed a gradual depletion of the nuclear pool of PCNA, while XRCC1 dynamically redistributed even to lesions inflicted last. Conclusion These results show that PCNA and XRCC1 have distinct kinetic properties with functional consequences for their capacity to respond to successive DNA damage events.

XRCC1 and PCNA are loading platforms with distinct kinetic properties and different capacities to respond to multiple DNA lesions

Science.gov (United States)

Mortusewicz, Oliver; Leonhardt, Heinrich

2007-01-01

Background Genome integrity is constantly challenged and requires the coordinated recruitment of multiple enzyme activities to ensure efficient repair of DNA lesions. We investigated the dynamics of XRCC1 and PCNA that act as molecular loading platforms and play a central role in this coordination. Results Local DNA damage was introduced by laser microirradation and the recruitment of fluorescent XRCC1 and PCNA fusion proteins was monitored by live cell microscopy. We found an immediate and fast recruitment of XRCC1 preceding the slow and continuous recruitment of PCNA. Fluorescence bleaching experiments (FRAP and FLIP) revealed a stable association of PCNA with DNA repair sites, contrasting the high turnover of XRCC1. When cells were repeatedly challenged with multiple DNA lesions we observed a gradual depletion of the nuclear pool of PCNA, while XRCC1 dynamically redistributed even to lesions inflicted last. Conclusion These results show that PCNA and XRCC1 have distinct kinetic properties with functional consequences for their capacity to respond to successive DNA damage events. PMID:17880707

Optimization of a Lattice Boltzmann Computation on State-of-the-Art Multicore Platforms

Energy Technology Data Exchange (ETDEWEB)

Williams, Samuel; Carter, Jonathan; Oliker, Leonid; Shalf, John; Yelick, Katherine

2009-04-10

We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of search-based performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to a lattice Boltzmann application (LBMHD) that historically has made poor use of scalar microprocessors due to its complex data structures and memory access patterns. We explore one of the broadest sets of multicore architectures in the HPC literature, including the Intel Xeon E5345 (Clovertown), AMD Opteron 2214 (Santa Rosa), AMD Opteron 2356 (Barcelona), Sun T5140 T2+ (Victoria Falls), as well as a QS20 IBM Cell Blade. Rather than hand-tuning LBMHD for each system, we develop a code generator that allows us to identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our auto-tuned LBMHD application achieves up to a 15x improvement compared with the original code at a given concurrency. Additionally, we present detailed analysis of each optimization, which reveal surprising hardware bottlenecks and software challenges for future multicore systems and applications.

Integrated reconfigurable multiple-input–multiple-output antenna system with an ultra-wideband sensing antenna for cognitive radio platforms

KAUST Repository

Hussain, Rifaqat; Sharawi, Mohammad S.

2015-01-01

. The developed model can be used as a complete antenna platform for cognitive radio applications. The antenna system is developed on a single substrate area of dimensions 65 × 120 mm². The proposed sensing antenna is used to cover a wide range

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.

Experiences with the ACPMAPS (Advanced Computer Program Multiple Array Processor System) 50 GFLOP system

International Nuclear Information System (INIS)

Fischler, M.

1992-10-01

The Fermilab Computer R ampersand D and Theory departments have for several years collaborated on a multi-GFLOP (recently upgraded to 50 GFLOP) system for lattice gauge calculations. The primary emphasis is on flexibility and ease of algorithm development. This system (ACPMAPS) has been in use for some time, allowing theorists to produce QCD results with relevance for the analysis of experimental data. We present general observations about benefits of such a scientist-oriented system, and summarize some of the advances recently made. We also discuss what was discovered about features needed in a useful algorithm exploration platform. These lessons can be applied to the design and evaluation of future massively parallel systems (commercial or otherwise)

Farm Management Support on Cloud Computing Platform: A System for Cropland Monitoring Using Multi-Source Remotely Sensed Data

Science.gov (United States)

Coburn, C. A.; Qin, Y.; Zhang, J.; Staenz, K.

2015-12-01

Food security is one of the most pressing issues facing humankind. Recent estimates predict that over one billion people don't have enough food to meet their basic nutritional needs. The ability of remote sensing tools to monitor and model crop production and predict crop yield is essential for providing governments and farmers with vital information to ensure food security. Google Earth Engine (GEE) is a cloud computing platform, which integrates storage and processing algorithms for massive remotely sensed imagery and vector data sets. By providing the capabilities of storing and analyzing the data sets, it provides an ideal platform for the development of advanced analytic tools for extracting key variables used in regional and national food security systems. With the high performance computing and storing capabilities of GEE, a cloud-computing based system for near real-time crop land monitoring was developed using multi-source remotely sensed data over large areas. The system is able to process and visualize the MODIS time series NDVI profile in conjunction with Landsat 8 image segmentation for crop monitoring. With multi-temporal Landsat 8 imagery, the crop fields are extracted using the image segmentation algorithm developed by Baatz et al.[1]. The MODIS time series NDVI data are modeled by TIMESAT [2], a software package developed for analyzing time series of satellite data. The seasonality of MODIS time series data, for example, the start date of the growing season, length of growing season, and NDVI peak at a field-level are obtained for evaluating the crop-growth conditions. The system fuses MODIS time series NDVI data and Landsat 8 imagery to provide information of near real-time crop-growth conditions through the visualization of MODIS NDVI time series and comparison of multi-year NDVI profiles. Stakeholders, i.e., farmers and government officers, are able to obtain crop-growth information at crop-field level online. This unique utilization of GEE in

Temperature, salinity, and nutrients data from CTD and bottle casts in the Arctic, North Atlantic and North Pacific Oceans from multiple platforms from 1963-04-30 to 1999-02-15 (NODC Accession 0000418)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — CTD, bottle, and other data were collected from the Arctic Ocean, North Atlantic Ocean, and North Pacific from multiple platforms from 30 April 1963 to 15 February...

Design and Implementation of Cloud Platform for Intelligent Logistics in the Trend of Intellectualization

Institute of Scientific and Technical Information of China (English)

Mengke Yang; Movahedipour Mahmood; Xiaoguang Zhou; Salam Shafaq; Latif Zahid

2017-01-01

Intellectualization has become a new trend for telecom industry, driven by in-telligent technology including cloud comput-ing, big data, and Internet of things. In order to satisfy the service demand of intelligent logistics, this paper designed an intelligent logistics platform containing the main ap-plications such as e-commerce, self-service transceiver, big data analysis, path location and distribution optimization. The intelligent logistics service platform has been built based on cloud computing to collect, store and han-dling multi-source heterogeneous mass data from sensors, RFID electronic tag, vehicle ter-minals and APP, so that the open-access cloud services including distribution, positioning, navigation, scheduling and other data services can be provided for the logistics distribution applications. And then the architecture of in-telligent logistics cloud platform containing software layer (SaaS), platform layer (PaaS) and infrastructure (IaaS) has been constructed accordance with the core technology relative high concurrent processing technique, hetero-geneous terminal data access, encapsulation and data mining. Therefore, intelligent logis-tics cloud platform can be carried out by the service mode for implementation to accelerate the construction of the symbiotic win-win logistics ecological system and the benign de-velopment of the ICT industry in the trend of intellectualization in China.

Multiple single-element transducer photoacoustic computed tomography system

Science.gov (United States)

Kalva, Sandeep Kumar; Hui, Zhe Zhi; Pramanik, Manojit

2018-02-01

Light absorption by the chromophores (hemoglobin, melanin, water etc.) present in any biological tissue results in local temperature rise. This rise in temperature results in generation of pressure waves due to the thermoelastic expansion of the tissue. In a circular scanning photoacoustic computed tomography (PACT) system, these pressure waves can be detected using a single-element ultrasound transducer (SUST) (while rotating in full 360° around the sample) or using a circular array transducer. SUST takes several minutes to acquire the PA data around the sample whereas the circular array transducer takes only a fraction of seconds. Hence, for real time imaging circular array transducers are preferred. However, these circular array transducers are custom made, expensive and not easily available in the market whereas SUSTs are cheap and readily available in the market. Using SUST for PACT systems is still cost effective. In order to reduce the scanning time to few seconds instead of using single SUST (rotating 360° ), multiple SUSTs can be used at the same time to acquire the PA data. This will reduce the scanning time by two-fold in case of two SUSTs (rotating 180° ) or by four-fold and eight-fold in case of four SUSTs (rotating 90° ) and eight SUSTs (rotating 45° ) respectively. Here we show that with multiple SUSTs, similar PA images (numerical and experimental phantom data) can be obtained as that of PA images obtained using single SUST.

GATECloud.net: a platform for large-scale, open-source text processing on the cloud.

Science.gov (United States)

Tablan, Valentin; Roberts, Ian; Cunningham, Hamish; Bontcheva, Kalina

2013-01-28

Cloud computing is increasingly being regarded as a key enabler of the 'democratization of science', because on-demand, highly scalable cloud computing facilities enable researchers anywhere to carry out data-intensive experiments. In the context of natural language processing (NLP), algorithms tend to be complex, which makes their parallelization and deployment on cloud platforms a non-trivial task. This study presents a new, unique, cloud-based platform for large-scale NLP research--GATECloud. net. It enables researchers to carry out data-intensive NLP experiments by harnessing the vast, on-demand compute power of the Amazon cloud. Important infrastructural issues are dealt with by the platform, completely transparently for the researcher: load balancing, efficient data upload and storage, deployment on the virtual machines, security and fault tolerance. We also include a cost-benefit analysis and usage evaluation.

G-DOC Plus - an integrative bioinformatics platform for precision medicine.

Science.gov (United States)

Bhuvaneshwar, Krithika; Belouali, Anas; Singh, Varun; Johnson, Robert M; Song, Lei; Alaoui, Adil; Harris, Michael A; Clarke, Robert; Weiner, Louis M; Gusev, Yuriy; Madhavan, Subha

2016-04-30

G-DOC Plus is a data integration and bioinformatics platform that uses cloud computing and other advanced computational tools to handle a variety of biomedical BIG DATA including gene expression arrays, NGS and medical images so that they can be analyzed in the full context of other omics and clinical information. G-DOC Plus currently holds data from over 10,000 patients selected from private and public resources including Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the recently added datasets from REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT), caArray studies of lung and colon cancer, ImmPort and the 1000 genomes data sets. The system allows researchers to explore clinical-omic data one sample at a time, as a cohort of samples; or at the level of population, providing the user with a comprehensive view of the data. G-DOC Plus tools have been leveraged in cancer and non-cancer studies for hypothesis generation and validation; biomarker discovery and multi-omics analysis, to explore somatic mutations and cancer MRI images; as well as for training and graduate education in bioinformatics, data and computational sciences. Several of these use cases are described in this paper to demonstrate its multifaceted usability. G-DOC Plus can be used to support a variety of user groups in multiple domains to enable hypothesis generation for precision medicine research. The long-term vision of G-DOC Plus is to extend this translational bioinformatics platform to stay current with emerging omics technologies and analysis methods to continue supporting novel hypothesis generation, analysis and validation for integrative biomedical research. By integrating several aspects of the disease and exposing various data elements, such as outpatient lab workup, pathology, radiology, current treatments, molecular signatures and expected outcomes over a web interface, G-DOC Plus will continue to strengthen precision medicine research. G-DOC Plus is available

Modal shapes optimization and feasibility analysis of NFAL platform

Directory of Open Access Journals (Sweden)

Bin WEI

2017-08-01

Full Text Available In order to avoid friction and scratching between the conveyor and the precision components when conveying object, an compact non-contact acoustic levitation prototype is designed, and the feasibility is theoretically and experimentally verified. The symmetry model is established through kinetic analysis with ANSYS. The modal and the coupled field computation at the central point of the transfer platform are simulated. The simulation results show that pure flexural or mixed flexural wave shapes appear with different wave numbers on the platform. Sweep frequency test is conducted on the compact platform prototype. The levitation experimental results confirm the feasibility of the ultrasound transfer process, the levitation frequency range and the mode of vibration. The theoretical and experimental results show that the optimal design of the modal and the carrying capacity of the driving platform is necessary according to different conditions. The research results provide a reference for the design of the mode and bandwidth of the ultrasonic levitation platform.

Cajun Maritime expands gas production platform with help from Liebherr crane

Energy Technology Data Exchange (ETDEWEB)

Anon.

2009-09-15

The South Marsh Island (SMI) Block 217 platform is a productive offshore natural gas handling hub in the Gulf of Mexico's Flatrock multiple reservoir deep-gas discovery. This one platform alone could increase natural gas production in the United States by 13 per cent. Louisiana-based Cajun Maritime LLC is the specialized marine subsidiary of the civil and mechanical contracting group Cajun Industries. The company focuses on maintaining a safe working environment at all times. The company purchased a new Liebherr LR 1300 lattice boom crawler crane for the Flatrock project because of its quality, lifting capacity and price. This article described the features of the crane that make it particularly suitable for offshore drilling, such as sealed bearings, big engine, high line pull, and the unique ability to move the main boom and luffing jib simultaneously while under load. The LR 1300 was used for several major installations, including pipelines, a new service crane and a water treatment deck platform. The safety features of the LR 1300 include a reeving winch which is used to install the lifting cables; the small diameter reeving winch cable is much easier to handle than the old method of hand pulling; and riggers are not required to walk the boom of the crane. The cab computer is useful in low overhead clearance work and completely removes the human error factor. The electronic hydraulic controls eliminate the risk of accidental load loss often associated with old-style friction cranes. 3 figs.

Context management platform for tourism applications.

Science.gov (United States)

Buján, David; Martín, David; Torices, Ortzi; López-de-Ipiña, Diego; Lamsfus, Carlos; Abaitua, Joseba; Alzua-Sorzabal, Aurkene

2013-06-24

The notion of context has been widely studied and there are several authors that have proposed different definitions of context. However, context has not been widely studied in the framework of human mobility and the notion of context has been imported directly from other computing fields without specifically addressing the tourism domain requirements. In order to store and manage context information a context data model and a context management platform are needed. Ontologies have been widely used in context modelling, but many of them are designed to be applied in general ubiquitous computing environments, do not contain specific concepts related to the tourism domain or some approaches do not contain enough concepts to represent context information related to the visitor on the move. That is why we propose a new approach to provide a better solution to model context data in tourism environments, adding more value to our solution reusing data about tourist resources from an Open Data repository and publishing it as Linked Data. We also propose the architecture for a context information management platform based on this context data model.

Towards OpenVL: Improving Real-Time Performance of Computer Vision Applications

Science.gov (United States)

Shen, Changsong; Little, James J.; Fels, Sidney

Meeting constraints for real-time performance is a main issue for computer vision, especially for embedded computer vision systems. This chapter presents our progress on our open vision library (OpenVL), a novel software architecture to address efficiency through facilitating hardware acceleration, reusability, and scalability for computer vision systems. A logical image understanding pipeline is introduced to allow parallel processing. We also discuss progress on our middleware—vision library utility toolkit (VLUT)—that enables applications to operate transparently over a heterogeneous collection of hardware implementations. OpenVL works as a state machine,with an event-driven mechanismto provide users with application-level interaction. Various explicit or implicit synchronization and communication methods are supported among distributed processes in the logical pipelines. The intent of OpenVL is to allow users to quickly and easily recover useful information from multiple scenes, in a cross-platform, cross-language manner across various software environments and hardware platforms. To validate the critical underlying concepts of OpenVL, a human tracking system and a local positioning system are implemented and described. The novel architecture separates the specification of algorithmic details from the underlying implementation, allowing for different components to be implemented on an embedded system without recompiling code.

GOLIAH: A Gaming Platform for Home-Based Intervention in Autism - Principles and Design.

Science.gov (United States)

Bono, Valentina; Narzisi, Antonio; Jouen, Anne-Lise; Tilmont, Elodie; Hommel, Stephane; Jamal, Wasifa; Xavier, Jean; Billeci, Lucia; Maharatna, Koushik; Wald, Mike; Chetouani, Mohamed; Cohen, David; Muratori, Filippo

2016-01-01

Children with Autism need intensive intervention and this is challenging in terms of manpower, costs, and time. Advances in Information Communication Technology and computer gaming may help in this respect by creating a nomadically deployable closed-loop intervention system involving the child and active participation of parents and therapists. An automated serious gaming platform enabling intensive intervention in nomadic settings has been developed by mapping two pivotal skills in autism spectrum disorder: Imitation and Joint Attention (JA). Eleven games - seven Imitations and four JA - were derived from the Early Start Denver Model. The games involved application of visual and audio stimuli with multiple difficulty levels and a wide variety of tasks and actions pertaining to the Imitation and JA. The platform runs on mobile devices and allows the therapist to (1) characterize the child's initial difficulties/strengths, ensuring tailored and adapted intervention by choosing appropriate games and (2) investigate and track the temporal evolution of the child's progress through a set of automatically extracted quantitative performance metrics. The platform allows the therapist to change the game or its difficulty levels during the intervention depending on the child's progress. Performance of the platform was assessed in a 3-month open trial with 10 children with autism (Trial ID: NCT02560415, Clinicaltrials.gov). The children and the parents participated in 80% of the sessions both at home (77.5%) and at the hospital (90%). All children went through all the games but, given the diversity of the games and the heterogeneity of children profiles and abilities, for a given game the number of sessions dedicated to the game varied and could be tailored through automatic scoring. Parents (N = 10) highlighted enhancement in the child's concentration, flexibility, and self-esteem in 78, 89, and 44% of the cases, respectively, and 56% observed an enhanced parents

iMagis 2.0: a platform toward image-based processes inherent to radiation therapy

International Nuclear Information System (INIS)

Daudinot Lopez, M.; Miller Clemente, R.; Gonce Hernandez, E.

2015-01-01

Radiotherapy is one of the main weapons against the leading cause of death in Cuba. The integration between radiotherapy and imaging modalities show an increasing trend across clinical applications, innovation and research. The availability of a platform for the inclusion of new applications in this area is crucial. the goal of this work was to demonstrate the possibilities of iMagis 2.0 as an existing platform, with applications in the planning process of pre-treatment based on images of cancer patients. iMagis® was the first Cuban PACS DICOM support, and the most widely applied in the Cuban Health System. Some available plugins were applied for medical planning of simulated patients with a homemade flatbed prototype, the latter installed on a CT unit SHIMADZU SCT 7800 TC in an Oncology Center. Multiple views for definitions of treatment volume were used, including the two-dimensional multiplanar reconstructions visualization. the viability of basic operations such as zoom images, rotations and translations are demonstrated. Monitoring changes in tumor volume during treatment were shown in combination with the estimated statistics of regions of interest. iMagis® supports a wide range of imaging modalities: computed Tomography, Magnetic Imaging PET / CT scan, Ultrasound, angiography, SPECT and providing a ready platform for adding new feature for radiotherapy and diagnostic. (Author)

Design of the smart scenic spot service platform

Science.gov (United States)

Yin, Min; Wang, Shi-tai

2015-12-01

With the deepening of the smart city construction, the model "smart+" is rapidly developing. Guilin, the international tourism metropolis fast constructing need smart tourism technology support. This paper studied the smart scenic spot service object and its requirements. And then constructed the smart service platform of the scenic spot application of 3S technology (Geographic Information System (GIS), Remote Sensing (RS) and Global Navigation Satellite System (GNSS)) and the Internet of things, cloud computing. Based on Guilin Seven-star Park scenic area as an object, this paper designed the Seven-star smart scenic spot service platform framework. The application of this platform will improve the tourists' visiting experience, make the tourism management more scientifically and standardly, increase tourism enterprises operating earnings.

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 ...

Sensitive Data Protection Based on Intrusion Tolerance in Cloud Computing

OpenAIRE

Jingyu Wang; xuefeng Zheng; Dengliang Luo

2011-01-01

Service integration and supply on-demand coming from cloud computing can significantly improve the utilization of computing resources and reduce power consumption of per service, and effectively avoid the error of computing resources. However, cloud computing is still facing the problem of intrusion tolerance of the cloud computing platform and sensitive data of new enterprise data center. In order to address the problem of intrusion tolerance of cloud computing platform and sensitive data in...

Computer-assisted upper extremity training using interactive biking exercise (iBikE) platform.

Science.gov (United States)

Jeong, In Cheol; Finkelstein, Joseph

2012-01-01

Upper extremity exercise training has been shown to improve clinical outcomes in different chronic health conditions. Arm-operated bicycles are frequently used to facilitate upper extremity training however effective use of these devices at patient homes is hampered by lack of remote connectivity with clinical rehabilitation team, inability to monitor exercise progress in real time using simple graphical representation, and absence of an alert system which would prevent exertion levels exceeding those approved by the clinical rehabilitation team. We developed an interactive biking exercise (iBikE) platform aimed at addressing these limitations. The platform uses a miniature wireless 3-axis accelerometer mounted on a patient wrist that transmits the cycling acceleration data to a laptop. The laptop screen presents an exercise dashboard to the patient in real time allowing easy graphical visualization of exercise progress and presentation of exercise parameters in relation to prescribed targets. The iBikE platform is programmed to alert the patient when exercise intensity exceeds the levels recommended by the patient care provider. The iBikE platform has been tested in 7 healthy volunteers (age range: 26-50 years) and shown to reliably reflect exercise progress and to generate alerts at pre-setup levels. Implementation of remote connectivity with patient rehabilitation team is warranted for future extension and evaluation efforts.

Crowd-Sourcing the Aesthetics of Platform Games

DEFF Research Database (Denmark)

Shaker, Noor; Yannakakis, Georgios N.; Togelius, Julian

2014-01-01

What are the aesthetics of platform games and what makes a platform level engaging, challenging and/or frustrating? We attempt to answer such questions through mining a large-set of crowd-sourced gameplay data of a clone of the classic platform game Super Mario Bros. The data consists of 40 short...... game levels that differ along six key level design parameters. Collectively, these levels are played 1560 times over the Internet and the perceived experience is annotated by experiment participants via self-reported ranking (pairwise preferences). Given the wealth of this crowd-sourced data, as all...... details about players’ in-game behaviour are logged, the problem becomes one of extracting meaningful numerical features at the appropriate level of abstraction for the construction of generic computational models of player experience and, thereby, game aesthetics. We explore dissimilar types of features...

Real-time Java simulations of multiple interference dielectric filters

Science.gov (United States)

Kireev, Alexandre N.; Martin, Olivier J. F.

2008-12-01

An interactive Java applet for real-time simulation and visualization of the transmittance properties of multiple interference dielectric filters is presented. The most commonly used interference filters as well as the state-of-the-art ones are embedded in this platform-independent applet which can serve research and education purposes. The Transmittance applet can be freely downloaded from the site http://cpc.cs.qub.ac.uk. Program summaryProgram title: Transmittance Catalogue identifier: AEBQ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBQ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 5778 No. of bytes in distributed program, including test data, etc.: 90 474 Distribution format: tar.gz Programming language: Java Computer: Developed on PC-Pentium platform Operating system: Any Java-enabled OS. Applet was tested on Windows ME, XP, Sun Solaris, Mac OS RAM: Variable Classification: 18 Nature of problem: Sophisticated wavelength selective multiple interference filters can include some tens or even hundreds of dielectric layers. The spectral response of such a stack is not obvious. On the other hand, there is a strong demand from application designers and students to get a quick insight into the properties of a given filter. Solution method: A Java applet was developed for the computation and the visualization of the transmittance of multilayer interference filters. It is simple to use and the embedded filter library can serve educational purposes. Also, its ability to handle complex structures will be appreciated as a useful research and development tool. Running time: Real-time simulations

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].

Moving Virtual Research Environments from high maintenance Stovepipes to Multi-purpose Sustainable Service-oriented Science Platforms

Science.gov (United States)

Klump, Jens; Fraser, Ryan; Wyborn, Lesley; Friedrich, Carsten; Squire, Geoffrey; Barker, Michelle; Moloney, Glenn

2017-04-01

The researcher of today is likely to be part of a team distributed over multiple sites that will access data from an external repository and then process the data on a public or private cloud or even on a large centralised supercomputer. They are increasingly likely to use a mixture of their own code, third party software and libraries, or even access global community codes. These components will be connected into a Virtual Research Environments (VREs) that will enable members of the research team who are not co-located to actively work together at various scales to share data, models, tools, software, workflows, best practices, infrastructures, etc. Many VRE's are built in isolation: designed to meet a specific research program with components tightly coupled and not capable of being repurposed for other use cases - they are becoming 'stovepipes'. The limited number of users of some VREs also means that the cost of maintenance per researcher can be unacceptably high. The alternative is to develop service-oriented Science Platforms that enable multiple communities to develop specialised solutions for specific research programs. The platforms can offer access to data, software tools and processing infrastructures (cloud, supercomputers) through globally distributed, interconnected modules. In Australia, the Virtual Geophysics Laboratory (VGL) was initially built to enable a specific set of researchers in government agencies access to specific data sets and a limited number of tools, that is now rapidly evolving into a multi-purpose Earth science platform with access to an increased variety of data, a broader range of tools, users from more sectors and a diversity of computational infrastructures. The expansion has been relatively easy, because of the architecture whereby data, tools and compute resources are loosely coupled via interfaces that are built on international standards and accessed as services wherever possible. In recent years, investments in

Wearable Device Control Platform Technology for Network Application Development

Directory of Open Access Journals (Sweden)

Heejung Kim

2016-01-01

Full Text Available Application development platform is the most important environment in IT industry. There are a variety of platforms. Although the native development enables application to optimize, various languages and software development kits need to be acquired according to the device. The coexistence of smart devices and platforms has rendered the native development approach time and cost consuming. Cross-platform development emerged as a response to these issues. These platforms generate applications for multiple devices based on web languages. Nevertheless, development requires additional implementation based on a native language because of the coverage and functions of supported application programming interfaces (APIs. Wearable devices have recently attracted considerable attention. These devices only support Bluetooth-based interdevice communication, thereby making communication and device control impossible beyond a certain range. We propose Network Application Agent (NetApp-Agent in order to overcome issues. NetApp-Agent based on the Cordova is a wearable device control platform for the development of network applications, controls input/output functions of smartphones and wearable/IoT through the Cordova and Native API, and enables device control and information exchange by external users by offering a self-defined API. We confirmed the efficiency of the proposed platform through experiments and a qualitative assessment of its implementation.

Seeing is believing: video classification for computed tomographic colonography using multiple-instance learning.

Science.gov (United States)

Wang, Shijun; McKenna, Matthew T; Nguyen, Tan B; Burns, Joseph E; Petrick, Nicholas; Sahiner, Berkman; Summers, Ronald M

2012-05-01

In this paper, we present development and testing results for a novel colonic polyp classification method for use as part of a computed tomographic colonography (CTC) computer-aided detection (CAD) system. Inspired by the interpretative methodology of radiologists using 3-D fly-through mode in CTC reading, we have developed an algorithm which utilizes sequences of images (referred to here as videos) for classification of CAD marks. For each CAD mark, we created a video composed of a series of intraluminal, volume-rendered images visualizing the detection from multiple viewpoints. We then framed the video classification question as a multiple-instance learning (MIL) problem. Since a positive (negative) bag may contain negative (positive) instances, which in our case depends on the viewing angles and camera distance to the target, we developed a novel MIL paradigm to accommodate this class of problems. We solved the new MIL problem by maximizing a L2-norm soft margin using semidefinite programming, which can optimize relevant parameters automatically. We tested our method by analyzing a CTC data set obtained from 50 patients from three medical centers. Our proposed method showed significantly better performance compared with several traditional MIL methods.

Opportunity for Realizing Ideal Computing System using Cloud Computing Model

OpenAIRE

Sreeramana Aithal; Vaikunth Pai T

2017-01-01

An ideal computing system is a computing system with ideal characteristics. The major components and their performance characteristics of such hypothetical system can be studied as a model with predicted input, output, system and environmental characteristics using the identified objectives of computing which can be used in any platform, any type of computing system, and for application automation, without making modifications in the form of structure, hardware, and software coding by an exte...

The big data processing platform for intelligent agriculture

Science.gov (United States)

Huang, Jintao; Zhang, Lichen

2017-08-01

Big data technology is another popular technology after the Internet of Things and cloud computing. Big data is widely used in many fields such as social platform, e-commerce, and financial analysis and so on. Intelligent agriculture in the course of the operation will produce large amounts of data of complex structure, fully mining the value of these data for the development of agriculture will be very meaningful. This paper proposes an intelligent data processing platform based on Storm and Cassandra to realize the storage and management of big data of intelligent agriculture.

The novel cloud application technology with virtual platform

Directory of Open Access Journals (Sweden)

Chen Ying-Chuan

2018-01-01

Full Text Available Virtualization technology of cloud application service is the major research issue in recent years. Our virtual platform can obtain a lot of advantages base on virtualization technology with suitable virtual machine solution that all system resources can deployed quickly and managed competently, and it has some features including the high capacity for reliability, elasticity and customization. In our virtual platform, there are many different application services are provided for cloud service style. For system computing resources, we need to share all of system and software resources using the virtualization technology is presented in related sections, and we proposed virtual and remote application technology to implement innovative, convenient and powerful cloud application service base on virtual platform. For users of our platform, they can easy to use any software and tools on demand with pay per use mode anytime, and they do not have specialized knowledge and ability of install and maintenance.

TDat: An Efficient Platform for Processing Petabyte-Scale Whole-Brain Volumetric Images.

Science.gov (United States)

Li, Yuxin; Gong, Hui; Yang, Xiaoquan; Yuan, Jing; Jiang, Tao; Li, Xiangning; Sun, Qingtao; Zhu, Dan; Wang, Zhenyu; Luo, Qingming; Li, Anan

2017-01-01

Three-dimensional imaging of whole mammalian brains at single-neuron resolution has generated terabyte (TB)- and even petabyte (PB)-sized datasets. Due to their size, processing these massive image datasets can be hindered by the computer hardware and software typically found in biological laboratories. To fill this gap, we have developed an efficient platform named TDat, which adopts a novel data reformatting strategy by reading cuboid data and employing parallel computing. In data reformatting, TDat is more efficient than any other software. In data accessing, we adopted parallelization to fully explore the capability for data transmission in computers. We applied TDat in large-volume data rigid registration and neuron tracing in whole-brain data with single-neuron resolution, which has never been demonstrated in other studies. We also showed its compatibility with various computing platforms, image processing software and imaging systems.

Computational multiple steady states for enzymatic esterification of ethanol and oleic acid in an isothermal CSTR.

Science.gov (United States)

Ho, Pang-Yen; Chuang, Guo-Syong; Chao, An-Chong; Li, Hsing-Ya

2005-05-01

The capacity of complex biochemical reaction networks (consisting of 11 coupled non-linear ordinary differential equations) to show multiple steady states, was investigated. The system involved esterification of ethanol and oleic acid by lipase in an isothermal continuous stirred tank reactor (CSTR). The Deficiency One Algorithm and the Subnetwork Analysis were applied to determine the steady state multiplicity. A set of rate constants and two corresponding steady states are computed. The phenomena of bistability, hysteresis and bifurcation are discussed. Moreover, the capacity of steady state multiplicity is extended to the family of the studied reaction networks.

Application of Soft Computing in Coherent Communications Phase Synchronization

Science.gov (United States)

Drake, Jeffrey T.; Prasad, Nadipuram R.

2000-01-01

The use of soft computing techniques in coherent communications phase synchronization provides an alternative to analytical or hard computing methods. This paper discusses a novel use of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for phase synchronization in coherent communications systems utilizing Multiple Phase Shift Keying (MPSK) modulation. A brief overview of the M-PSK digital communications bandpass modulation technique is presented and it's requisite need for phase synchronization is discussed. We briefly describe the hybrid platform developed by Jang that incorporates fuzzy/neural structures namely the, Adaptive Neuro-Fuzzy Interference Systems (ANFIS). We then discuss application of ANFIS to phase estimation for M-PSK. The modeling of both explicit, and implicit phase estimation schemes for M-PSK symbols with unknown structure are discussed. Performance results from simulation of the above scheme is presented.

Computed a multiple band metamaterial absorber and its application based on the figure of merit value

Science.gov (United States)

Chen, Chao; Sheng, Yuping; Jun, Wang

2018-01-01

A high performed multiple band metamaterial absorber is designed and computed through the software Ansofts HFSS 10.0, which is constituted with two kinds of separated metal particles sub-structures. The multiple band absorption property of the metamaterial absorber is based on the resonance of localized surface plasmon (LSP) modes excited near edges of metal particles. The damping constant of gold layer is optimized to obtain a near-perfect absorption rate. Four kinds of dielectric layers is computed to achieve the perfect absorption perform. The perfect absorption perform of the metamaterial absorber is enhanced through optimizing the structural parameters (R = 75 nm, w = 80 nm). Moreover, a perfect absorption band is achieved because of the plasmonic hybridization phenomenon between LSP modes. The designed metamaterial absorber shows high sensitive in the changed of the refractive index of the liquid. A liquid refractive index sensor strategy is proposed based on the computed figure of merit (FOM) value of the metamaterial absorber. High FOM values (116, 111, and 108) are achieved with three liquid (Methanol, Carbon tetrachloride, and Carbon disulfide).

The Common Data Acquisition Platform in the Helmholtz Association

International Nuclear Information System (INIS)

Kaever, P.; Balzer, M.; Kopmann, A.; Zimmer, M.; Rongen, H.

2017-01-01

Various centres of the German Helmholtz Association (HGF) started in 2012 to develop a modular data acquisition (DAQ) platform, covering the entire range from detector readout to data transfer into parallel computing environments. This platform integrates generic hardware components like the multi-purpose HGF-Advanced Mezzanine Card or a smart scientific camera framework, adding user value with Linux drivers and board support packages. Technically the scope comprises the DAQ-chain from FPGA-modules to computing servers, notably frontend-electronics-interfaces, microcontrollers and GPUs with their software plus high-performance data transmission links. The core idea is a generic and component-based approach, enabling the implementation of specific experiment requirements with low effort. This so called DTS-platform will support standards like MTCA.4 in hard- and software to ensure compatibility with commercial components. Its capability to deploy on other crate standards or FPGA-boards with PCI express or Ethernet interfaces remains an essential feature. Competences of the participating centres are coordinated in order to provide a solid technological basis for both research topics in the Helmholtz Programme ''Matter and Technology'': ''Detector Technology and Systems'' and ''Accelerator Research and Development''. The DTS-platform aims at reducing costs and development time and will ensure access to latest technologies for the collaboration. Due to its flexible approach, it has the potential to be applied in other scientific programs.

The Common Data Acquisition Platform in the Helmholtz Association

Science.gov (United States)

Kaever, P.; Balzer, M.; Kopmann, A.; Zimmer, M.; Rongen, H.

2017-04-01

Various centres of the German Helmholtz Association (HGF) started in 2012 to develop a modular data acquisition (DAQ) platform, covering the entire range from detector readout to data transfer into parallel computing environments. This platform integrates generic hardware components like the multi-purpose HGF-Advanced Mezzanine Card or a smart scientific camera framework, adding user value with Linux drivers and board support packages. Technically the scope comprises the DAQ-chain from FPGA-modules to computing servers, notably frontend-electronics-interfaces, microcontrollers and GPUs with their software plus high-performance data transmission links. The core idea is a generic and component-based approach, enabling the implementation of specific experiment requirements with low effort. This so called DTS-platform will support standards like MTCA.4 in hard- and software to ensure compatibility with commercial components. Its capability to deploy on other crate standards or FPGA-boards with PCI express or Ethernet interfaces remains an essential feature. Competences of the participating centres are coordinated in order to provide a solid technological basis for both research topics in the Helmholtz Programme ``Matter and Technology'': ``Detector Technology and Systems'' and ``Accelerator Research and Development''. The DTS-platform aims at reducing costs and development time and will ensure access to latest technologies for the collaboration. Due to its flexible approach, it has the potential to be applied in other scientific programs.

Circular Bioassay Platforms for Applications in Microwave-Accelerated Techniques.

Science.gov (United States)

Mohammed, Muzaffer; Clement, Travis C; Aslan, Kadir

2014-12-02

In this paper, we present the design of four different circular bioassay platforms, which are suitable for homogeneous microwave heating, using theoretical calculations (i.e., COMSOL™ multiphysics software). Circular bioassay platforms are constructed from poly(methyl methacrylate) (PMMA) for optical transparency between 400-800 nm, has multiple sample capacity (12, 16, 19 and 21 wells) and modified with silver nanoparticle films (SNFs) to be used in microwave-accelerated bioassays (MABs). In addition, a small monomode microwave cavity, which can be operated with an external microwave generator (100 W), for use with the bioassay platforms in MABs is also developed. Our design parameters for the circular bioassay platforms and monomode microwave cavity during microwave heating were: (i) temperature profiles, (ii) electric field distributions, (iii) location of the circular bioassay platforms inside the microwave cavity, and (iv) design and number of wells on the circular bioassay platforms. We have also carried out additional simulations to assess the use of circular bioassay platforms in a conventional kitchen microwave oven (e.g., 900 W). Our results show that the location of the circular bioassay platforms in the microwave cavity was predicted to have a significant effect on the homogeneous heating of these platforms. The 21-well circular bioassay platform design in our monomode microwave cavity was predicted to offer a homogeneous heating pattern, where inter-well temperature was observed to be in between 23.72-24.13°C and intra-well temperature difference was less than 0.21°C for 60 seconds of microwave heating, which was also verified experimentally.

Resource Management in Mobile Cloud Computing

Directory of Open Access Journals (Sweden)

Andrei IONESCU

2015-01-01

Full Text Available Mobile cloud computing is a major research topic in Information Technology & Communications. It integrates cloud computing, mobile computing and wireless networks. While mainly built on cloud computing, it has to operate using more heterogeneous resources with implications on how these resources are managed and used. Managing the resources of a mobile cloud is not a trivial task, involving vastly different architectures. The process is outside the scope of human users. Using the resources by the applications at both platform and software tiers come with its own challenges. This paper presents different approaches in use for managing cloud resources at infrastructure and platform levels.

BrainFrame: a node-level heterogeneous accelerator platform for neuron simulations

Science.gov (United States)

Smaragdos, Georgios; Chatzikonstantis, Georgios; Kukreja, Rahul; Sidiropoulos, Harry; Rodopoulos, Dimitrios; Sourdis, Ioannis; Al-Ars, Zaid; Kachris, Christoforos; Soudris, Dimitrios; De Zeeuw, Chris I.; Strydis, Christos

2017-12-01

Objective. The advent of high-performance computing (HPC) in recent years has led to its increasing use in brain studies through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though modern HPC platforms can often deal with such challenges, the vast diversity of the modeling field does not permit for a homogeneous acceleration platform to effectively address the complete array of modeling requirements. Approach. In this paper we propose and build BrainFrame, a heterogeneous acceleration platform that incorporates three distinct acceleration technologies, an Intel Xeon-Phi CPU, a NVidia GP-GPU and a Maxeler Dataflow Engine. The PyNN software framework is also integrated into the platform. As a challenging proof of concept, we analyze the performance of BrainFrame on different experiment instances of a state-of-the-art neuron model, representing the inferior-olivary nucleus using a biophysically-meaningful, extended Hodgkin-Huxley representation. The model instances take into account not only the neuronal-network dimensions but also different network-connectivity densities, which can drastically affect the workload’s performance characteristics. Main results. The combined use of different HPC technologies demonstrates that BrainFrame is better able to cope with the modeling diversity encountered in realistic experiments while at the same time running on significantly lower energy budgets. Our performance analysis clearly shows that the model directly affects performance and all three technologies are required to cope with all the model use cases. Significance. The BrainFrame framework is designed to transparently configure and select the appropriate back-end accelerator technology for use per simulation run. The PyNN integration provides a familiar bridge to the vast number of models already available. Additionally, it gives a clear roadmap for extending the platform

Property-Based Anonymous Attestation in Trusted Cloud Computing

Directory of Open Access Journals (Sweden)

Zhen-Hu Ning

2014-01-01

Full Text Available In the remote attestation on Trusted Computer (TC computing mode TCCP, the trusted computer TC has an excessive burden, and anonymity and platform configuration information security of computing nodes cannot be guaranteed. To overcome these defects, based on the research on and analysis of current schemes, we propose an anonymous proof protocol based on property certificate. The platform configuration information is converted by the matrix algorithm into the property certificate, and the remote attestation is implemented by trusted ring signature scheme based on Strong RSA Assumption. By the trusted ring signature scheme based on property certificate, we achieve the anonymity of computing nodes and prevent the leakage of platform configuration information. By simulation, we obtain the computational efficiency of the scheme. We also expand the protocol and obtain the anonymous attestation based on ECC. By scenario comparison, we obtain the trusted ring signature scheme based on RSA, which has advantages with the growth of the ring numbers.

Remote Video Monitor of Vehicles in Cooperative Information Platform

Science.gov (United States)

Qin, Guofeng; Wang, Xiaoguo; Wang, Li; Li, Yang; Li, Qiyan

Detection of vehicles plays an important role in the area of the modern intelligent traffic management. And the pattern recognition is a hot issue in the area of computer vision. An auto- recognition system in cooperative information platform is studied. In the cooperative platform, 3G wireless network, including GPS, GPRS (CDMA), Internet (Intranet), remote video monitor and M-DMB networks are integrated. The remote video information can be taken from the terminals and sent to the cooperative platform, then detected by the auto-recognition system. The images are pretreated and segmented, including feature extraction, template matching and pattern recognition. The system identifies different models and gets vehicular traffic statistics. Finally, the implementation of the system is introduced.

Cross-brain neurofeedback: scientific concept and experimental platform.

Directory of Open Access Journals (Sweden)

Lian Duan

Full Text Available The present study described a new type of multi-person neurofeedback with the neural synchronization between two participants as the direct regulating target, termed as "cross-brain neurofeedback." As a first step to implement this concept, an experimental platform was built on the basis of functional near-infrared spectroscopy, and was validated with a two-person neurofeedback experiment. This novel concept as well as the experimental platform established a framework for investigation of the relationship between multiple participants' cross-brain neural synchronization and their social behaviors, which could provide new insight into the neural substrate of human social interactions.

A high performance scientific cloud computing environment for materials simulations

OpenAIRE

Jorissen, Kevin; Vila, Fernando D.; Rehr, John J.

2011-01-01

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...

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.

Methodology of an International Study of People with Multiple Sclerosis Recruited through Web 2.0 Platforms: Demographics, Lifestyle, and Disease Characteristics

Directory of Open Access Journals (Sweden)

Emily J. Hadgkiss

2013-01-01

Full Text Available Background. Despite evidence of the potential importance of the role of health and lifestyle behaviours in multiple sclerosis (MS outcomes, there has not been a significant focus on this area of research. Aim. We aimed to recruit an international sample of people with MS at baseline and over a five-year timeframe, examine their health and lifestyle behaviours, and determine the relationship of these behaviours to self-reported disability, disease activity, and quality of life. Methods. People with MS were recruited through web 2.0 platforms including interactive websites, social media, blogs, and forums and completed a comprehensive, multifaceted online questionnaire incorporating validated and researcher-derived tools. Results. 2519 participants met inclusion criteria for this study. This paper describes the study methodology in detail and provides an overview of baseline participant demographics, clinical characteristics, summary outcome variables, and health and lifestyle behaviours. The sample described is unique due to the nature of recruitment through online media and due to the engagement of the group, which appears to be well informed and proactive in lifestyle modification. Conclusion. This sample provides a sound platform to undertake novel exploratory analyses of the association between a variety of lifestyle factors and MS outcomes.

HAlign-II: efficient ultra-large multiple sequence alignment and phylogenetic tree reconstruction with distributed and parallel computing.

Science.gov (United States)

Wan, Shixiang; Zou, Quan

2017-01-01

Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.

Multi-ASIP Platform Synthesis for Real-Time Applications

DEFF Research Database (Denmark)

Micconi, Laura; Gangadharan, Deepak; Pop, Paul

2013-01-01

In this paper we are interested in deriving a distributed platform, composed of heterogeneous processing elements, targeted to applications that have strict timing constraints. We consider that the platform may use multiple Application Specific Instruction Set Processors (ASIPs). An ASIP...... is synthesized and tuned for a specific set of tasks (i.e., a task cluster). During design space exploration (DSE), we evaluate each platform solution visited in terms of its cost and performance, i.e., its ability to execute the applications such that they meet their timing constraints. To determine...... if the applications are schedulable, we have to know the worst-case execution time (WCET) of each task. However, we can determine the WCETs only after the ASIPs are synthesized, which is time consuming and therefore cannot be done during DSE. To address this circular dependency (the ASIPs depend on the task...

A novel detection platform for parallel monitoring of DNA hybridization with high sensitivity and specificity

DEFF Research Database (Denmark)

Yi, Sun; Perch-Nielsen, Ivan R.; Wang, Zhenyu

We developed a high-sensitive platform to monior multiple hybridization events in real time. By creating a microoptical array in a polymeric chip, the system combine the excellent discriminative power of supercritical angle fluorescence (SAF) microscopy with high-throughput capabilities of microa......We developed a high-sensitive platform to monior multiple hybridization events in real time. By creating a microoptical array in a polymeric chip, the system combine the excellent discriminative power of supercritical angle fluorescence (SAF) microscopy with high-throughput capabilities...

Development of a scalable generic platform for adaptive optics real time control

Science.gov (United States)

Surendran, Avinash; Burse, Mahesh P.; Ramaprakash, A. N.; Parihar, Padmakar

2015-06-01

The main objective of the present project is to explore the viability of an adaptive optics control system based exclusively on Field Programmable Gate Arrays (FPGAs), making strong use of their parallel processing capability. In an Adaptive Optics (AO) system, the generation of the Deformable Mirror (DM) control voltages from the Wavefront Sensor (WFS) measurements is usually through the multiplication of the wavefront slopes with a predetermined reconstructor matrix. The ability to access several hundred hard multipliers and memories concurrently in an FPGA allows performance far beyond that of a modern CPU or GPU for tasks with a well-defined structure such as Adaptive Optics control. The target of the current project is to generate a signal for a real time wavefront correction, from the signals coming from a Wavefront Sensor, wherein the system would be flexible to accommodate all the current Wavefront Sensing techniques and also the different methods which are used for wavefront compensation. The system should also accommodate for different data transmission protocols (like Ethernet, USB, IEEE 1394 etc.) for transmitting data to and from the FPGA device, thus providing a more flexible platform for Adaptive Optics control. Preliminary simulation results for the formulation of the platform, and a design of a fully scalable slope computer is presented.

Memory Hierarchy Design for Next Generation Scalable Many-core Platforms

OpenAIRE

Azarkhish, Erfan

2016-01-01

Performance and energy consumption in modern computing platforms is largely dominated by the memory hierarchy. The increasing computational power in the multiprocessors and accelerators, and the emergence of the data-intensive workloads (e.g. large-scale graph traversal and scientific algorithms) requiring fast transfer of large volumes of data, are two main trends which intensify this problem by putting even higher pressure on the memory hierarchy. This increasing gap between computation spe...

A Hybrid Verifiable and Delegated Cryptographic Model in Cloud Computing

Directory of Open Access Journals (Sweden)

Jaber Ibrahim Naser

2018-02-01

Full Text Available Access control is very important in cloud data sharing. Especially in the domains like healthcare, it is essential to have access control mechanisms in place for confidentiality and secure data access. Attribute based encryption has been around for many years to secure data and provide controlled access. In this paper, we proposed a framework that supports circuit and attributes based encryption mechanism that involves multiple parties. They are data owner, data user, cloud server and attribute authority. An important feature of the proposed system is the verifiable delegation of the decryption process to cloud server. Data owner encrypts data and delegates decryption process to cloud. Cloud server performs partial decryption and then the final decrypted data are shared for users as per the privileges. Data owner  thus reduces computational complexity by delegating decryption process cloud server. We built a prototype application using the Microsoft.NET platform for proof of the concept. The empirical results revealed that there is controlled access with multiple user roles and access control rights for secure and confidential data access in cloud computing.

Generalized internal multiple imaging

KAUST Repository

Zuberi, Mohammad Akbar Hosain

2014-12-04

Various examples are provided for generalized internal multiple imaging (GIMI). In one example, among others, a method includes generating a higher order internal multiple image using a background Green\\'s function and rendering the higher order internal multiple image for presentation. In another example, a system includes a computing device and a generalized internal multiple imaging (GIMI) application executable in the computing device. The GIMI application includes logic that generates a higher order internal multiple image using a background Green\\'s function and logic that renders the higher order internal multiple image for display on a display device. In another example, a non-transitory computer readable medium has a program executable by processing circuitry that generates a higher order internal multiple image using a background Green\\'s function and renders the higher order internal multiple image for display on a display device.

Generalized internal multiple imaging

KAUST Repository

Zuberi, Mohammad Akbar Hosain; Alkhalifah, Tariq

2014-01-01

Various examples are provided for generalized internal multiple imaging (GIMI). In one example, among others, a method includes generating a higher order internal multiple image using a background Green's function and rendering the higher order internal multiple image for presentation. In another example, a system includes a computing device and a generalized internal multiple imaging (GIMI) application executable in the computing device. The GIMI application includes logic that generates a higher order internal multiple image using a background Green's function and logic that renders the higher order internal multiple image for display on a display device. In another example, a non-transitory computer readable medium has a program executable by processing circuitry that generates a higher order internal multiple image using a background Green's function and renders the higher order internal multiple image for display on a display device.

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...

A Platform for Mobile Service Provisioning Based on SOA-Integration

Science.gov (United States)

Decker, Michael; Bulander, Rebecca

A middleware platform designed for the provisioning of data services for mobile computers using wireless data communication (e.g. smartphones or PDAs) has to offer a variety of different features. Some of these features have to be provided by external parties, e.g. billing or content syndication. The integration of all these features while considering mobile-specific challenges is a demanding task. In the article at hand we thus describe a middleware platform for mobile services which follows the idea of a so called Enterprise Service Bus (ESB). We explain the concept of ESB and argue why an ESB is an appropriate fundament for a platform for mobile service provisioning.

Validation of MCNP6 Version 1.0 with the ENDF/B-VII.1 Cross Section Library for Plutonium Metals, Oxides, and Solutions on the High Performance Computing Platform Moonlight

Energy Technology Data Exchange (ETDEWEB)

Chapman, Bryan Scott [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Gough, Sean T. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-12-05

This report documents a validation of the MCNP6 Version 1.0 computer code on the high performance computing platform Moonlight, for operations at Los Alamos National Laboratory (LANL) that involve plutonium metals, oxides, and solutions. The validation is conducted using the ENDF/B-VII.1 continuous energy group cross section library at room temperature. The results are for use by nuclear criticality safety personnel in performing analysis and evaluation of various facility activities involving plutonium materials.