WorldWideScience

Sample records for high-performance distributed computations

  1. Distributed metadata in a high performance computing environment

    Science.gov (United States)

    Bent, John M.; Faibish, Sorin; Zhang, Zhenhua; Liu, Xuezhao; Tang, Haiying

    2017-07-11

    A computer-executable method, system, and computer program product for managing meta-data in a distributed storage system, wherein the distributed storage system includes one or more burst buffers enabled to operate with a distributed key-value store, the co computer-executable method, system, and computer program product comprising receiving a request for meta-data associated with a block of data stored in a first burst buffer of the one or more burst buffers in the distributed storage system, wherein the meta data is associated with a key-value, determining which of the one or more burst buffers stores the requested metadata, and upon determination that a first burst buffer of the one or more burst buffers stores the requested metadata, locating the key-value in a portion of the distributed key-value store accessible from the first burst buffer.

  2. Using high performance interconnects in a distributed computing and mass storage environment

    International Nuclear Information System (INIS)

    Ernst, M.

    1994-01-01

    Detector Collaborations of the HERA Experiments typically involve more than 500 physicists from a few dozen institutes. These physicists require access to large amounts of data in a fully transparent manner. Important issues include Distributed Mass Storage Management Systems in a Distributed and Heterogeneous Computing Environment. At the very center of a distributed system, including tens of CPUs and network attached mass storage peripherals are the communication links. Today scientists are witnessing an integration of computing and communication technology with the open-quote network close-quote becoming the computer. This contribution reports on a centrally operated computing facility for the HERA Experiments at DESY, including Symmetric Multiprocessor Machines (84 Processors), presently more than 400 GByte of magnetic disk and 40 TB of automoted tape storage, tied together by a HIPPI open-quote network close-quote. Focussing on the High Performance Interconnect technology, details will be provided about the HIPPI based open-quote Backplane close-quote configured around a 20 Gigabit/s Multi Media Router and the performance and efficiency of the related computer interfaces

  3. High Performance Computing Multicast

    Science.gov (United States)

    2012-02-01

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

  4. VLab: A Science Gateway for Distributed First Principles Calculations in Heterogeneous High Performance Computing Systems

    Science.gov (United States)

    da Silveira, Pedro Rodrigo Castro

    2014-01-01

    This thesis describes the development and deployment of a cyberinfrastructure for distributed high-throughput computations of materials properties at high pressures and/or temperatures--the Virtual Laboratory for Earth and Planetary Materials--VLab. VLab was developed to leverage the aggregated computational power of grid systems to solve…

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

    Energy Technology Data Exchange (ETDEWEB)

    Karonis, Nicholas T.

    2000-05-01

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

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

    Science.gov (United States)

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

    2000-01-01

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

  7. Computational Biology and High Performance Computing 2000

    Energy Technology Data Exchange (ETDEWEB)

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

    2000-10-19

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

  8. High Performance Spaceflight Computing (HPSC)

    Data.gov (United States)

    National Aeronautics and Space Administration — Space-based computing has not kept up with the needs of current and future NASA missions. We are developing a next-generation flight computing system that addresses...

  9. Inclusive vision for high performance computing at the CSIR

    CSIR Research Space (South Africa)

    Gazendam, A

    2006-02-01

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

  10. High performance computing in Windows Azure cloud

    OpenAIRE

    Ambruš, Dejan

    2013-01-01

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

  11. High-performance computing using FPGAs

    CERN Document Server

    Benkrid, Khaled

    2013-01-01

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

  12. High-performance computing — an overview

    Science.gov (United States)

    Marksteiner, Peter

    1996-08-01

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

  13. Molecular simulation workflows as parallel algorithms: the execution engine of Copernicus, a distributed high-performance computing platform.

    Science.gov (United States)

    Pronk, Sander; Pouya, Iman; Lundborg, Magnus; Rotskoff, Grant; Wesén, Björn; Kasson, Peter M; Lindahl, Erik

    2015-06-09

    Computational chemistry and other simulation fields are critically dependent on computing resources, but few problems scale efficiently to the hundreds of thousands of processors available in current supercomputers-particularly for molecular dynamics. This has turned into a bottleneck as new hardware generations primarily provide more processing units rather than making individual units much faster, which simulation applications are addressing by increasingly focusing on sampling with algorithms such as free-energy perturbation, Markov state modeling, metadynamics, or milestoning. All these rely on combining results from multiple simulations into a single observation. They are potentially powerful approaches that aim to predict experimental observables directly, but this comes at the expense of added complexity in selecting sampling strategies and keeping track of dozens to thousands of simulations and their dependencies. Here, we describe how the distributed execution framework Copernicus allows the expression of such algorithms in generic workflows: dataflow programs. Because dataflow algorithms explicitly state dependencies of each constituent part, algorithms only need to be described on conceptual level, after which the execution is maximally parallel. The fully automated execution facilitates the optimization of these algorithms with adaptive sampling, where undersampled regions are automatically detected and targeted without user intervention. We show how several such algorithms can be formulated for computational chemistry problems, and how they are executed efficiently with many loosely coupled simulations using either distributed or parallel resources with Copernicus.

  14. Embedded High Performance Scalable Computing Systems

    National Research Council Canada - National Science Library

    Ngo, David

    2003-01-01

    The Embedded High Performance Scalable Computing Systems (EHPSCS) program is a cooperative agreement between Sanders, A Lockheed Martin Company and DARPA that ran for three years, from Apr 1995 - Apr 1998...

  15. Debugging a high performance computing program

    Science.gov (United States)

    Gooding, Thomas M.

    2013-08-20

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

  16. High performance computing on vector systems

    CERN Document Server

    Roller, Sabine

    2008-01-01

    Presents the developments in high-performance computing and simulation on modern supercomputer architectures. This book covers trends in hardware and software development in general and specifically the vector-based systems and heterogeneous architectures. It presents innovative fields like coupled multi-physics or multi-scale simulations.

  17. AHPCRC - Army High Performance Computing Research Center

    Science.gov (United States)

    2010-01-01

    computing. Of particular interest is the ability of a distrib- uted jamming network (DJN) to jam signals in all or part of a sensor or communications net...and reasoning, assistive technologies. FRIEDRICH (FRITZ) PRINZ Finmeccanica Professor of Engineering, Robert Bosch Chair, Department of Engineering...High Performance Computing Research Center www.ahpcrc.org BARBARA BRYAN AHPCRC Research and Outreach Manager, HPTi (650) 604-3732 bbryan@hpti.com Ms

  18. DURIP: High Performance Computing in Biomathematics Applications

    Science.gov (United States)

    2017-05-10

    Mathematics and Statistics (AMS) at the University of California, Santa Cruz (UCSC) to conduct research and research-related education in areas of...Computing in Biomathematics Applications Report Title The goal of this award was to enhance the capabilities of the Department of Applied Mathematics and...DURIP: High Performance Computing in Biomathematics Applications The goal of this award was to enhance the capabilities of the Department of Applied

  19. High-Performance Computing Paradigm and Infrastructure

    CERN Document Server

    Yang, Laurence T

    2006-01-01

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

  20. Monitoring SLAC High Performance UNIX Computing Systems

    International Nuclear Information System (INIS)

    Lettsome, Annette K.

    2005-01-01

    Knowledge of the effectiveness and efficiency of computers is important when working with high performance systems. The monitoring of such systems is advantageous in order to foresee possible misfortunes or system failures. Ganglia is a software system designed for high performance computing systems to retrieve specific monitoring information. An alternative storage facility for Ganglia's collected data is needed since its default storage system, the round-robin database (RRD), struggles with data integrity. The creation of a script-driven MySQL database solves this dilemma. This paper describes the process took in the creation and implementation of the MySQL database for use by Ganglia. Comparisons between data storage by both databases are made using gnuplot and Ganglia's real-time graphical user interface

  1. High-performance computing for airborne applications

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  2. High Performance Computing Operations Review Report

    Energy Technology Data Exchange (ETDEWEB)

    Cupps, Kimberly C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2013-12-19

    The High Performance Computing Operations Review (HPCOR) meeting—requested by the ASC and ASCR program headquarters at DOE—was held November 5 and 6, 2013, at the Marriott Hotel in San Francisco, CA. The purpose of the review was to discuss the processes and practices for HPC integration and its related software and facilities. Experiences and lessons learned from the most recent systems deployed were covered in order to benefit the deployment of new systems.

  3. High-performance computing in seismology

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-09-01

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

  4. Evaluation of high-performance computing software

    Energy Technology Data Exchange (ETDEWEB)

    Browne, S.; Dongarra, J. [Univ. of Tennessee, Knoxville, TN (United States); Rowan, T. [Oak Ridge National Lab., TN (United States)

    1996-12-31

    The absence of unbiased and up to date comparative evaluations of high-performance computing software complicates a user`s search for the appropriate software package. The National HPCC Software Exchange (NHSE) is attacking this problem using an approach that includes independent evaluations of software, incorporation of author and user feedback into the evaluations, and Web access to the evaluations. We are applying this approach to the Parallel Tools Library (PTLIB), a new software repository for parallel systems software and tools, and HPC-Netlib, a high performance branch of the Netlib mathematical software repository. Updating the evaluations with feed-back and making it available via the Web helps ensure accuracy and timeliness, and using independent reviewers produces unbiased comparative evaluations difficult to find elsewhere.

  5. High performance parallel computers for science

    International Nuclear Information System (INIS)

    Nash, T.; Areti, H.; Atac, R.; Biel, J.; Cook, A.; Deppe, J.; Edel, M.; Fischler, M.; Gaines, I.; Hance, R.

    1989-01-01

    This paper reports that Fermilab's Advanced Computer Program (ACP) has been developing cost effective, yet practical, parallel computers for high energy physics since 1984. The ACP's latest developments are proceeding in two directions. A Second Generation ACP Multiprocessor System for experiments will include $3500 RISC processors each with performance over 15 VAX MIPS. To support such high performance, the new system allows parallel I/O, parallel interprocess communication, and parallel host processes. The ACP Multi-Array Processor, has been developed for theoretical physics. Each $4000 node is a FORTRAN or C programmable pipelined 20 Mflops (peak), 10 MByte single board computer. These are plugged into a 16 port crossbar switch crate which handles both inter and intra crate communication. The crates are connected in a hypercube. Site oriented applications like lattice gauge theory are supported by system software called CANOPY, which makes the hardware virtually transparent to users. A 256 node, 5 GFlop, system is under construction

  6. High performance computing in linear control

    International Nuclear Information System (INIS)

    Datta, B.N.

    1993-01-01

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

  7. High Performance Networks From Supercomputing to Cloud Computing

    CERN Document Server

    Abts, Dennis

    2011-01-01

    Datacenter networks provide the communication substrate for large parallel computer systems that form the ecosystem for high performance computing (HPC) systems and modern Internet applications. The design of new datacenter networks is motivated by an array of applications ranging from communication intensive climatology, complex material simulations and molecular dynamics to such Internet applications as Web search, language translation, collaborative Internet applications, streaming video and voice-over-IP. For both Supercomputing and Cloud Computing the network enables distributed applicati

  8. The path toward HEP High Performance Computing

    International Nuclear Information System (INIS)

    Apostolakis, John; Brun, René; Gheata, Andrei; Wenzel, Sandro; Carminati, Federico

    2014-01-01

    High Energy Physics code has been known for making poor use of high performance computing architectures. Efforts in optimising HEP code on vector and RISC architectures have yield limited results and recent studies have shown that, on modern architectures, it achieves a performance between 10% and 50% of the peak one. Although several successful attempts have been made to port selected codes on GPUs, no major HEP code suite has a 'High Performance' implementation. With LHC undergoing a major upgrade and a number of challenging experiments on the drawing board, HEP cannot any longer neglect the less-than-optimal performance of its code and it has to try making the best usage of the hardware. This activity is one of the foci of the SFT group at CERN, which hosts, among others, the Root and Geant4 project. The activity of the experiments is shared and coordinated via a Concurrency Forum, where the experience in optimising HEP code is presented and discussed. Another activity is the Geant-V project, centred on the development of a highperformance prototype for particle transport. Achieving a good concurrency level on the emerging parallel architectures without a complete redesign of the framework can only be done by parallelizing at event level, or with a much larger effort at track level. Apart the shareable data structures, this typically implies a multiplication factor in terms of memory consumption compared to the single threaded version, together with sub-optimal handling of event processing tails. Besides this, the low level instruction pipelining of modern processors cannot be used efficiently to speedup the program. We have implemented a framework that allows scheduling vectors of particles to an arbitrary number of computing resources in a fine grain parallel approach. The talk will review the current optimisation activities within the SFT group with a particular emphasis on the development perspectives towards a simulation framework able to profit

  9. HIGH PERFORMANCE PHOTOGRAMMETRIC PROCESSING ON COMPUTER CLUSTERS

    Directory of Open Access Journals (Sweden)

    V. N. Adrov

    2012-07-01

    Full Text Available Most cpu consuming tasks in photogrammetric processing can be done in parallel. The algorithms take independent bits as input and produce independent bits as output. The independence of bits comes from the nature of such algorithms since images, stereopairs or small image blocks parts can be processed independently. Many photogrammetric algorithms are fully automatic and do not require human interference. Photogrammetric workstations can perform tie points measurements, DTM calculations, orthophoto construction, mosaicing and many other service operations in parallel using distributed calculations. Distributed calculations save time reducing several days calculations to several hours calculations. Modern trends in computer technology show the increase of cpu cores in workstations, speed increase in local networks, and as a result dropping the price of the supercomputers or computer clusters that can contain hundreds or even thousands of computing nodes. Common distributed processing in DPW is usually targeted for interactive work with a limited number of cpu cores and is not optimized for centralized administration. The bottleneck of common distributed computing in photogrammetry can be in the limited lan throughput and storage performance, since the processing of huge amounts of large raster images is needed.

  10. A High Performance COTS Based Computer Architecture

    Science.gov (United States)

    Patte, Mathieu; Grimoldi, Raoul; Trautner, Roland

    2014-08-01

    Using Commercial Off The Shelf (COTS) electronic components for space applications is a long standing idea. Indeed the difference in processing performance and energy efficiency between radiation hardened components and COTS components is so important that COTS components are very attractive for use in mass and power constrained systems. However using COTS components in space is not straightforward as one must account with the effects of the space environment on the COTS components behavior. In the frame of the ESA funded activity called High Performance COTS Based Computer, Airbus Defense and Space and its subcontractor OHB CGS have developed and prototyped a versatile COTS based architecture for high performance processing. The rest of the paper is organized as follows: in a first section we will start by recapitulating the interests and constraints of using COTS components for space applications; then we will briefly describe existing fault mitigation architectures and present our solution for fault mitigation based on a component called the SmartIO; in the last part of the paper we will describe the prototyping activities executed during the HiP CBC project.

  11. The path toward HEP High Performance Computing

    CERN Document Server

    Apostolakis, John; Carminati, Federico; Gheata, Andrei; Wenzel, Sandro

    2014-01-01

    High Energy Physics code has been known for making poor use of high performance computing architectures. Efforts in optimising HEP code on vector and RISC architectures have yield limited results and recent studies have shown that, on modern architectures, it achieves a performance between 10% and 50% of the peak one. Although several successful attempts have been made to port selected codes on GPUs, no major HEP code suite has a 'High Performance' implementation. With LHC undergoing a major upgrade and a number of challenging experiments on the drawing board, HEP cannot any longer neglect the less-than-optimal performance of its code and it has to try making the best usage of the hardware. This activity is one of the foci of the SFT group at CERN, which hosts, among others, the Root and Geant4 project. The activity of the experiments is shared and coordinated via a Concurrency Forum, where the experience in optimising HEP code is presented and discussed. Another activity is the Geant-V project, centred on th...

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

    CERN Document Server

    Kröner, Dietmar; Resch, Michael

    2016-01-01

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

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

    CERN Document Server

    Kröner, Dietmar; Resch, Michael; HLRS 2017

    2018-01-01

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

  14. Visualization and Data Analysis for High-Performance Computing

    Energy Technology Data Exchange (ETDEWEB)

    Sewell, Christopher Meyer [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-09-27

    This is a set of slides from a guest lecture for a class at the University of Texas, El Paso on visualization and data analysis for high-performance computing. The topics covered are the following: trends in high-performance computing; scientific visualization, such as OpenGL, ray tracing and volume rendering, VTK, and ParaView; data science at scale, such as in-situ visualization, image databases, distributed memory parallelism, shared memory parallelism, VTK-m, "big data", and then an analysis example.

  15. HPDC ´12 : proceedings of the 21st ACM symposium on high-performance parallel and distributed computing, June 18-22, 2012, Delft, The Netherlands

    NARCIS (Netherlands)

    Epema, D.H.J.; Kielmann, T.; Ripeanu, M.

    2012-01-01

    Welcome to ACM HPDC 2012! This is the twenty-first year of HPDC and we are pleased to report that our community continues to grow in size, quality and reputation. The program consists of three days packed with presentations on the latest developments in high-performance parallel and distributed

  16. High Performance Computing in Science and Engineering '99 : Transactions of the High Performance Computing Center

    CERN Document Server

    Jäger, Willi

    2000-01-01

    The book contains reports about the most significant projects from science and engineering of the Federal High Performance Computing Center Stuttgart (HLRS). They were carefully selected in a peer-review process and are showcases of an innovative combination of state-of-the-art modeling, novel algorithms and the use of leading-edge parallel computer technology. The projects of HLRS are using supercomputer systems operated jointly by university and industry and therefore a special emphasis has been put on the industrial relevance of results and methods.

  17. High Performance Computing in Science and Engineering '98 : Transactions of the High Performance Computing Center

    CERN Document Server

    Jäger, Willi

    1999-01-01

    The book contains reports about the most significant projects from science and industry that are using the supercomputers of the Federal High Performance Computing Center Stuttgart (HLRS). These projects are from different scientific disciplines, with a focus on engineering, physics and chemistry. They were carefully selected in a peer-review process and are showcases for an innovative combination of state-of-the-art physical modeling, novel algorithms and the use of leading-edge parallel computer technology. As HLRS is in close cooperation with industrial companies, special emphasis has been put on the industrial relevance of results and methods.

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

    CERN Document Server

    Jäger, Willi

    2003-01-01

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

  19. DOE research in utilization of high-performance computers

    International Nuclear Information System (INIS)

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

    1980-12-01

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

  20. Peregrine System | High-Performance Computing | NREL

    Science.gov (United States)

    classes of nodes that users access: Login Nodes Peregrine has four login nodes, each of which has Intel E5 /scratch file systems, the /mss file system is mounted on all login nodes. Compute Nodes Peregrine has 2592

  1. High Performance Data Distribution for Scientific Community

    Science.gov (United States)

    Tirado, Juan M.; Higuero, Daniel; Carretero, Jesus

    2010-05-01

    Institutions such as NASA, ESA or JAXA find solutions to distribute data from their missions to the scientific community, and their long term archives. This is a complex problem, as it includes a vast amount of data, several geographically distributed archives, heterogeneous architectures with heterogeneous networks, and users spread around the world. We propose a novel architecture (HIDDRA) that solves this problem aiming to reduce user intervention in data acquisition and processing. HIDDRA is a modular system that provides a highly efficient parallel multiprotocol download engine, using a publish/subscribe policy which helps the final user to obtain data of interest transparently. Our system can deal simultaneously with multiple protocols (HTTP,HTTPS, FTP, GridFTP among others) to obtain the maximum bandwidth, reducing the workload in data server and increasing flexibility. It can also provide high reliability and fault tolerance, as several sources of data can be used to perform one file download. HIDDRA architecture can be arranged into a data distribution network deployed on several sites that can cooperate to provide former features. HIDDRA has been addressed by the 2009 e-IRG Report on Data Management as a promising initiative for data interoperability. Our first prototype has been evaluated in collaboration with the ESAC centre in Villafranca del Castillo (Spain) that shows a high scalability and performance, opening a wide spectrum of opportunities. Some preliminary results have been published in the Journal of Astrophysics and Space Science [1]. [1] D. Higuero, J.M. Tirado, J. Carretero, F. Félix, and A. de La Fuente. HIDDRA: a highly independent data distribution and retrieval architecture for space observation missions. Astrophysics and Space Science, 321(3):169-175, 2009

  2. High performance computations using dynamical nucleation theory

    International Nuclear Information System (INIS)

    Windus, T L; Crosby, L D; Kathmann, S M

    2008-01-01

    Chemists continue to explore the use of very large computations to perform simulations that describe the molecular level physics of critical challenges in science. In this paper, we describe the Dynamical Nucleation Theory Monte Carlo (DNTMC) model - a model for determining molecular scale nucleation rate constants - and its parallel capabilities. The potential for bottlenecks and the challenges to running on future petascale or larger resources are delineated. A 'master-slave' solution is proposed to scale to the petascale and will be developed in the NWChem software. In addition, mathematical and data analysis challenges are described

  3. RISC Processors and High Performance Computing

    Science.gov (United States)

    Bailey, David H.; Saini, Subhash; Craw, James M. (Technical Monitor)

    1995-01-01

    This tutorial will discuss the top five RISC microprocessors and the parallel systems in which they are used. It will provide a unique cross-machine comparison not available elsewhere. The effective performance of these processors will be compared by citing standard benchmarks in the context of real applications. The latest NAS Parallel Benchmarks, both absolute performance and performance per dollar, will be listed. The next generation of the NPB will be described. The tutorial will conclude with a discussion of future directions in the field. Technology Transfer Considerations: All of these computer systems are commercially available internationally. Information about these processors is available in the public domain, mostly from the vendors themselves. The NAS Parallel Benchmarks and their results have been previously approved numerous times for public release, beginning back in 1991.

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

    CERN Document Server

    Kröner, Dietmar; Resch, Michael

    2009-01-01

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

  5. NINJA: Java for High Performance Numerical Computing

    Directory of Open Access Journals (Sweden)

    José E. Moreira

    2002-01-01

    Full Text Available When Java was first introduced, there was a perception that its many benefits came at a significant performance cost. In the particularly performance-sensitive field of numerical computing, initial measurements indicated a hundred-fold performance disadvantage between Java and more established languages such as Fortran and C. Although much progress has been made, and Java now can be competitive with C/C++ in many important situations, significant performance challenges remain. Existing Java virtual machines are not yet capable of performing the advanced loop transformations and automatic parallelization that are now common in state-of-the-art Fortran compilers. Java also has difficulties in implementing complex arithmetic efficiently. These performance deficiencies can be attacked with a combination of class libraries (packages, in Java that implement truly multidimensional arrays and complex numbers, and new compiler techniques that exploit the properties of these class libraries to enable other, more conventional, optimizations. Two compiler techniques, versioning and semantic expansion, can be leveraged to allow fully automatic optimization and parallelization of Java code. Our measurements with the NINJA prototype Java environment show that Java can be competitive in performance with highly optimized and tuned Fortran code.

  6. Contemporary high performance computing from petascale toward exascale

    CERN Document Server

    Vetter, Jeffrey S

    2013-01-01

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

  7. Enabling High-Performance Computing as a Service

    KAUST Repository

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

    2012-01-01

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

  8. High Performance Computing Modernization Program Kerberos Throughput Test Report

    Science.gov (United States)

    2017-10-26

    Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/5524--17-9751 High Performance Computing Modernization Program Kerberos Throughput Test ...NUMBER 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 2. REPORT TYPE1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 6. AUTHOR(S) 8. PERFORMING...PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT High Performance Computing Modernization Program Kerberos Throughput Test Report Daniel G. Gdula* and

  9. 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...

  10. Quantum Accelerators for High-Performance Computing Systems

    OpenAIRE

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

    2017-01-01

    We define some of the programming and system-level challenges facing the application of quantum processing to high-performance computing. Alongside barriers to physical integration, prominent differences in the execution of quantum and conventional programs challenges the intersection of these computational models. Following a brief overview of the state of the art, we discuss recent advances in programming and execution models for hybrid quantum-classical computing. We discuss a novel quantu...

  11. High Performance Computing Software Applications for Space Situational Awareness

    Science.gov (United States)

    Giuliano, C.; Schumacher, P.; Matson, C.; Chun, F.; Duncan, B.; Borelli, K.; Desonia, R.; Gusciora, G.; Roe, K.

    The High Performance Computing Software Applications Institute for Space Situational Awareness (HSAI-SSA) has completed its first full year of applications development. The emphasis of our work in this first year was in improving space surveillance sensor models and image enhancement software. These applications are the Space Surveillance Network Analysis Model (SSNAM), the Air Force Space Fence simulation (SimFence), and physically constrained iterative de-convolution (PCID) image enhancement software tool. Specifically, we have demonstrated order of magnitude speed-up in those codes running on the latest Cray XD-1 Linux supercomputer (Hoku) at the Maui High Performance Computing Center. The software applications improvements that HSAI-SSA has made, has had significant impact to the warfighter and has fundamentally changed the role of high performance computing in SSA.

  12. The Milan Project: A New Method for High-Assurance and High-Performance Computing on Large-Scale Distributed Platforms

    National Research Council Canada - National Science Library

    Kedem, Zvi

    2000-01-01

    ...: Calypso, Chime, and Charlotte; which enable applications developed for ideal, shared memory, parallel machines to execute on distributed platforms that are subject to failures, slowdowns, and changing resource availability...

  13. 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.

  14. High performance computing and communications: FY 1997 implementation plan

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-12-01

    The High Performance Computing and Communications (HPCC) Program was formally authorized by passage, with bipartisan support, of the High-Performance Computing Act of 1991, signed on December 9, 1991. The original Program, in which eight Federal agencies participated, has now grown to twelve agencies. This Plan provides a detailed description of the agencies` FY 1996 HPCC accomplishments and FY 1997 HPCC plans. Section 3 of this Plan provides an overview of the HPCC Program. Section 4 contains more detailed definitions of the Program Component Areas, with an emphasis on the overall directions and milestones planned for each PCA. Appendix A provides a detailed look at HPCC Program activities within each agency.

  15. High Performance Computing in Science and Engineering '14

    CERN Document Server

    Kröner, Dietmar; Resch, Michael

    2015-01-01

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

  16. Quantum Accelerators for High-performance Computing Systems

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-11-01

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

  17. Optical interconnection networks for high-performance computing systems

    International Nuclear Information System (INIS)

    Biberman, Aleksandr; Bergman, Keren

    2012-01-01

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

  18. High Performance Data Transfer for Distributed Data Intensive Sciences

    Energy Technology Data Exchange (ETDEWEB)

    Fang, Chin [Zettar Inc., Mountain View, CA (United States); Cottrell, R ' Les' A. [SLAC National Accelerator Lab., Menlo Park, CA (United States); Hanushevsky, Andrew B. [SLAC National Accelerator Lab., Menlo Park, CA (United States); Kroeger, Wilko [SLAC National Accelerator Lab., Menlo Park, CA (United States); Yang, Wei [SLAC National Accelerator Lab., Menlo Park, CA (United States)

    2017-03-06

    We report on the development of ZX software providing high performance data transfer and encryption. The design scales in: computation power, network interfaces, and IOPS while carefully balancing the available resources. Two U.S. patent-pending algorithms help tackle data sets containing lots of small files and very large files, and provide insensitivity to network latency. It has a cluster-oriented architecture, using peer-to-peer technologies to ease deployment, operation, usage, and resource discovery. Its unique optimizations enable effective use of flash memory. Using a pair of existing data transfer nodes at SLAC and NERSC, we compared its performance to that of bbcp and GridFTP and determined that they were comparable. With a proof of concept created using two four-node clusters with multiple distributed multi-core CPUs, network interfaces and flash memory, we achieved 155Gbps memory-to-memory over a 2x100Gbps link aggregated channel and 70Gbps file-to-file with encryption over a 5000 mile 100Gbps link.

  19. Software Systems for High-performance Quantum Computing

    Energy Technology Data Exchange (ETDEWEB)

    Humble, Travis S [ORNL; Britt, Keith A [ORNL

    2016-01-01

    Quantum computing promises new opportunities for solving hard computational problems, but harnessing this novelty requires breakthrough concepts in the design, operation, and application of computing systems. We define some of the challenges facing the development of quantum computing systems as well as software-based approaches that can be used to overcome these challenges. Following a brief overview of the state of the art, we present models for the quantum programming and execution models, the development of architectures for hybrid high-performance computing systems, and the realization of software stacks for quantum networking. This leads to a discussion of the role that conventional computing plays in the quantum paradigm and how some of the current challenges for exascale computing overlap with those facing quantum computing.

  20. High-performance scientific computing in the cloud

    Science.gov (United States)

    Jorissen, Kevin; Vila, Fernando; Rehr, John

    2011-03-01

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

  1. GPU-based high-performance computing for radiation therapy

    International Nuclear Information System (INIS)

    Jia, Xun; Jiang, Steve B; Ziegenhein, Peter

    2014-01-01

    Recent developments in radiotherapy therapy demand high computation powers to solve challenging problems in a timely fashion in a clinical environment. The graphics processing unit (GPU), as an emerging high-performance computing platform, has been introduced to radiotherapy. It is particularly attractive due to its high computational power, small size, and low cost for facility deployment and maintenance. Over the past few years, GPU-based high-performance computing in radiotherapy has experienced rapid developments. A tremendous amount of study has been conducted, in which large acceleration factors compared with the conventional CPU platform have been observed. In this paper, we will first give a brief introduction to the GPU hardware structure and programming model. We will then review the current applications of GPU in major imaging-related and therapy-related problems encountered in radiotherapy. A comparison of GPU with other platforms will also be presented. (topical review)

  2. Enabling High-Performance Computing as a Service

    KAUST Repository

    AbdelBaky, Moustafa

    2012-10-01

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

  3. Computer science of the high performance; Informatica del alto rendimiento

    Energy Technology Data Exchange (ETDEWEB)

    Moraleda, A.

    2008-07-01

    The high performance computing is taking shape as a powerful accelerator of the process of innovation, to drastically reduce the waiting times for access to the results and the findings in a growing number of processes and activities as complex and important as medicine, genetics, pharmacology, environment, natural resources management or the simulation of complex processes in a wide variety of industries. (Author)

  4. Contemporary high performance computing from petascale toward exascale

    CERN Document Server

    Vetter, Jeffrey S

    2015-01-01

    A continuation of Contemporary High Performance Computing: From Petascale toward Exascale, this second volume continues the discussion of HPC flagship systems, major application workloads, facilities, and sponsors. The book includes of figures and pictures that capture the state of existing systems: pictures of buildings, systems in production, floorplans, and many block diagrams and charts to illustrate system design and performance.

  5. Enabling high performance computational science through combinatorial algorithms

    International Nuclear Information System (INIS)

    Boman, Erik G; Bozdag, Doruk; Catalyurek, Umit V; Devine, Karen D; Gebremedhin, Assefaw H; Hovland, Paul D; Pothen, Alex; Strout, Michelle Mills

    2007-01-01

    The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation

  6. Enabling high performance computational science through combinatorial algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Boman, Erik G [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Bozdag, Doruk [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Catalyurek, Umit V [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Devine, Karen D [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Gebremedhin, Assefaw H [Computer Science and Center for Computational Science, Old Dominion University (United States); Hovland, Paul D [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Pothen, Alex [Computer Science and Center for Computational Science, Old Dominion University (United States); Strout, Michelle Mills [Computer Science, Colorado State University (United States)

    2007-07-15

    The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation.

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

    CERN Document Server

    Kröner, Dietmar; Resch, Michael

    2016-01-01

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

  8. High performance computing in power and energy systems

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-07-01

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

  9. High performance distributed objects in large hadron collider experiments

    International Nuclear Information System (INIS)

    Gutleber, J.

    1999-11-01

    This dissertation demonstrates how object-oriented technology can support the development of software that has to meet the requirements of high performance distributed data acquisition systems. The environment for this work is a system under planning for the Compact Muon Solenoid experiment at CERN that shall start its operation in the year 2005. The long operational phase of the experiment together with a tight and puzzling interaction with custom devices make the quest for an evolvable architecture that exhibits a high level of abstraction the driving issue. The question arises if an existing approach already fits our needs. The presented work casts light on these problems and as a result comprises the following novel contributions: - Application of object technology at hardware/software boundary. Software components at this level must be characterised by high efficiency and extensibility at the same time. - Identification of limitations when deploying commercial-off-the-shelf middleware for distributed object-oriented computing. - Capturing of software component properties in an efficiency model for ease of comparison and improvement. - Proof of feasibility that the encountered deficiencies in middleware can be avoided and that with the use of software components the imposed requirements can be met. - Design and implementation of an on-line software control system that allows to take into account the ever evolving requirements by avoiding hardwired policies. We conclude that state-of-the-art middleware cannot meet the required efficiency of the planned data acquisition system. Although new tool generations already provide a certain degree of configurability, the obligation to follow standards specifications does not allow the necessary optimisations. We identified the major limiting factors and argue that a custom solution following a component model with narrow interfaces can satisfy our requirements. This approach has been adopted for the current design

  10. 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.

  11. High performance computing and communications: FY 1996 implementation plan

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-05-16

    The High Performance Computing and Communications (HPCC) Program was formally authorized by passage of the High Performance Computing Act of 1991, signed on December 9, 1991. Twelve federal agencies, in collaboration with scientists and managers from US industry, universities, and research laboratories, have developed the Program to meet the challenges of advancing computing and associated communications technologies and practices. This plan provides a detailed description of the agencies` HPCC implementation plans for FY 1995 and FY 1996. This Implementation Plan contains three additional sections. Section 3 provides an overview of the HPCC Program definition and organization. Section 4 contains a breakdown of the five major components of the HPCC Program, with an emphasis on the overall directions and milestones planned for each one. Section 5 provides a detailed look at HPCC Program activities within each agency.

  12. 3rd International Conference on High Performance Scientific Computing

    CERN Document Server

    Kostina, Ekaterina; Phu, Hoang; Rannacher, Rolf

    2008-01-01

    This proceedings volume contains a selection of papers presented at the Third International Conference on High Performance Scientific Computing held at the Hanoi Institute of Mathematics, Vietnamese Academy of Science and Technology (VAST), March 6-10, 2006. The conference has been organized by the Hanoi Institute of Mathematics, Interdisciplinary Center for Scientific Computing (IWR), Heidelberg, and its International PhD Program ``Complex Processes: Modeling, Simulation and Optimization'', and Ho Chi Minh City University of Technology. The contributions cover the broad interdisciplinary spectrum of scientific computing and present recent advances in theory, development of methods, and applications in practice. Subjects covered are mathematical modelling, numerical simulation, methods for optimization and control, parallel computing, software development, applications of scientific computing in physics, chemistry, biology and mechanics, environmental and hydrology problems, transport, logistics and site loca...

  13. 5th International Conference on High Performance Scientific Computing

    CERN Document Server

    Hoang, Xuan; Rannacher, Rolf; Schlöder, Johannes

    2014-01-01

    This proceedings volume gathers a selection of papers presented at the Fifth International Conference on High Performance Scientific Computing, which took place in Hanoi on March 5-9, 2012. The conference was organized by the Institute of Mathematics of the Vietnam Academy of Science and Technology (VAST), the Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University, Ho Chi Minh City University of Technology, and the Vietnam Institute for Advanced Study in Mathematics. The contributions cover the broad interdisciplinary spectrum of scientific computing and present recent advances in theory, development of methods, and practical applications. Subjects covered include mathematical modeling; numerical simulation; methods for optimization and control; parallel computing; software development; and applications of scientific computing in physics, mechanics and biomechanics, material science, hydrology, chemistry, biology, biotechnology, medicine, sports, psychology, transport, logistics, com...

  14. 6th International Conference on High Performance Scientific Computing

    CERN Document Server

    Phu, Hoang; Rannacher, Rolf; Schlöder, Johannes

    2017-01-01

    This proceedings volume highlights a selection of papers presented at the Sixth International Conference on High Performance Scientific Computing, which took place in Hanoi, Vietnam on March 16-20, 2015. The conference was jointly organized by the Heidelberg Institute of Theoretical Studies (HITS), the Institute of Mathematics of the Vietnam Academy of Science and Technology (VAST), the Interdisciplinary Center for Scientific Computing (IWR) at Heidelberg University, and the Vietnam Institute for Advanced Study in Mathematics, Ministry of Education The contributions cover a broad, interdisciplinary spectrum of scientific computing and showcase recent advances in theory, methods, and practical applications. Subjects covered numerical simulation, methods for optimization and control, parallel computing, and software development, as well as the applications of scientific computing in physics, mechanics, biomechanics and robotics, material science, hydrology, biotechnology, medicine, transport, scheduling, and in...

  15. Unravelling the structure of matter on high-performance computers

    International Nuclear Information System (INIS)

    Kieu, T.D.; McKellar, B.H.J.

    1992-11-01

    The various phenomena and the different forms of matter in nature are believed to be the manifestation of only a handful set of fundamental building blocks-the elementary particles-which interact through the four fundamental forces. In the study of the structure of matter at this level one has to consider forces which are not sufficiently weak to be treated as small perturbations to the system, an example of which is the strong force that binds the nucleons together. High-performance computers, both vector and parallel machines, have facilitated the necessary non-perturbative treatments. The principles and the techniques of computer simulations applied to Quantum Chromodynamics are explained examples include the strong interactions, the calculation of the mass of nucleons and their decay rates. Some commercial and special-purpose high-performance machines for such calculations are also mentioned. 3 refs., 2 tabs

  16. Multi-Language Programming Environments for High Performance Java Computing

    OpenAIRE

    Vladimir Getov; Paul Gray; Sava Mintchev; Vaidy Sunderam

    1999-01-01

    Recent developments in processor capabilities, software tools, programming languages and programming paradigms have brought about new approaches to high performance computing. A steadfast component of this dynamic evolution has been the scientific community’s reliance on established scientific packages. As a consequence, programmers of high‐performance applications are reluctant to embrace evolving languages such as Java. This paper describes the Java‐to‐C Interface (JCI) tool which provides ...

  17. High-Performance Java Codes for Computational Fluid Dynamics

    Science.gov (United States)

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

    2001-01-01

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

  18. Component-based software for high-performance scientific computing

    Energy Technology Data Exchange (ETDEWEB)

    Alexeev, Yuri; Allan, Benjamin A; Armstrong, Robert C; Bernholdt, David E; Dahlgren, Tamara L; Gannon, Dennis; Janssen, Curtis L; Kenny, Joseph P; Krishnan, Manojkumar; Kohl, James A; Kumfert, Gary; McInnes, Lois Curfman; Nieplocha, Jarek; Parker, Steven G; Rasmussen, Craig; Windus, Theresa L

    2005-01-01

    Recent advances in both computational hardware and multidisciplinary science have given rise to an unprecedented level of complexity in scientific simulation software. This paper describes an ongoing grass roots effort aimed at addressing complexity in high-performance computing through the use of Component-Based Software Engineering (CBSE). Highlights of the benefits and accomplishments of the Common Component Architecture (CCA) Forum and SciDAC ISIC are given, followed by an illustrative example of how the CCA has been applied to drive scientific discovery in quantum chemistry. Thrusts for future research are also described briefly.

  19. Component-based software for high-performance scientific computing

    International Nuclear Information System (INIS)

    Alexeev, Yuri; Allan, Benjamin A; Armstrong, Robert C; Bernholdt, David E; Dahlgren, Tamara L; Gannon, Dennis; Janssen, Curtis L; Kenny, Joseph P; Krishnan, Manojkumar; Kohl, James A; Kumfert, Gary; McInnes, Lois Curfman; Nieplocha, Jarek; Parker, Steven G; Rasmussen, Craig; Windus, Theresa L

    2005-01-01

    Recent advances in both computational hardware and multidisciplinary science have given rise to an unprecedented level of complexity in scientific simulation software. This paper describes an ongoing grass roots effort aimed at addressing complexity in high-performance computing through the use of Component-Based Software Engineering (CBSE). Highlights of the benefits and accomplishments of the Common Component Architecture (CCA) Forum and SciDAC ISIC are given, followed by an illustrative example of how the CCA has been applied to drive scientific discovery in quantum chemistry. Thrusts for future research are also described briefly

  20. Nuclear forces and high-performance computing: The perfect match

    International Nuclear Information System (INIS)

    Luu, T; Walker-Loud, A

    2009-01-01

    High-performance computing is now enabling the calculation of certain hadronic interaction parameters directly from Quantum Chromodynamics, the quantum field theory that governs the behavior of quarks and gluons and is ultimately responsible for the nuclear strong force. In this paper we briefly describe the state of the field and show how other aspects of hadronic interactions will be ascertained in the near future. We give estimates of computational requirements needed to obtain these goals, and outline a procedure for incorporating these results into the broader nuclear physics community.

  1. High-performance computing in accelerating structure design and analysis

    International Nuclear Information System (INIS)

    Li Zenghai; Folwell, Nathan; Ge Lixin; Guetz, Adam; Ivanov, Valentin; Kowalski, Marc; Lee, Lie-Quan; Ng, Cho-Kuen; Schussman, Greg; Stingelin, Lukas; Uplenchwar, Ravindra; Wolf, Michael; Xiao, Liling; Ko, Kwok

    2006-01-01

    Future high-energy accelerators such as the Next Linear Collider (NLC) will accelerate multi-bunch beams of high current and low emittance to obtain high luminosity, which put stringent requirements on the accelerating structures for efficiency and beam stability. While numerical modeling has been quite standard in accelerator R and D, designing the NLC accelerating structure required a new simulation capability because of the geometric complexity and level of accuracy involved. Under the US DOE Advanced Computing initiatives (first the Grand Challenge and now SciDAC), SLAC has developed a suite of electromagnetic codes based on unstructured grids and utilizing high-performance computing to provide an advanced tool for modeling structures at accuracies and scales previously not possible. This paper will discuss the code development and computational science research (e.g. domain decomposition, scalable eigensolvers, adaptive mesh refinement) that have enabled the large-scale simulations needed for meeting the computational challenges posed by the NLC as well as projects such as the PEP-II and RIA. Numerical results will be presented to show how high-performance computing has made a qualitative improvement in accelerator structure modeling for these accelerators, either at the component level (single cell optimization), or on the scale of an entire structure (beam heating and long-range wakefields)

  2. A High Performance VLSI Computer Architecture For Computer Graphics

    Science.gov (United States)

    Chin, Chi-Yuan; Lin, Wen-Tai

    1988-10-01

    A VLSI computer architecture, consisting of multiple processors, is presented in this paper to satisfy the modern computer graphics demands, e.g. high resolution, realistic animation, real-time display etc.. All processors share a global memory which are partitioned into multiple banks. Through a crossbar network, data from one memory bank can be broadcasted to many processors. Processors are physically interconnected through a hyper-crossbar network (a crossbar-like network). By programming the network, the topology of communication links among processors can be reconfigurated to satisfy specific dataflows of different applications. Each processor consists of a controller, arithmetic operators, local memory, a local crossbar network, and I/O ports to communicate with other processors, memory banks, and a system controller. Operations in each processor are characterized into two modes, i.e. object domain and space domain, to fully utilize the data-independency characteristics of graphics processing. Special graphics features such as 3D-to-2D conversion, shadow generation, texturing, and reflection, can be easily handled. With the current high density interconnection (MI) technology, it is feasible to implement a 64-processor system to achieve 2.5 billion operations per second, a performance needed in most advanced graphics applications.

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

    National Research Council Canada - National Science Library

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

    2010-01-01

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

  4. 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.

  5. High performance computing and communications: FY 1995 implementation plan

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-04-01

    The High Performance Computing and Communications (HPCC) Program was formally established following passage of the High Performance Computing Act of 1991 signed on December 9, 1991. Ten federal agencies in collaboration with scientists and managers from US industry, universities, and laboratories have developed the HPCC Program to meet the challenges of advancing computing and associated communications technologies and practices. This plan provides a detailed description of the agencies` HPCC implementation plans for FY 1994 and FY 1995. This Implementation Plan contains three additional sections. Section 3 provides an overview of the HPCC Program definition and organization. Section 4 contains a breakdown of the five major components of the HPCC Program, with an emphasis on the overall directions and milestones planned for each one. Section 5 provides a detailed look at HPCC Program activities within each agency. Although the Department of Education is an official HPCC agency, its current funding and reporting of crosscut activities goes through the Committee on Education and Health Resources, not the HPCC Program. For this reason the Implementation Plan covers nine HPCC agencies.

  6. Computational Fluid Dynamics (CFD) Computations With Zonal Navier-Stokes Flow Solver (ZNSFLOW) Common High Performance Computing Scalable Software Initiative (CHSSI) Software

    National Research Council Canada - National Science Library

    Edge, Harris

    1999-01-01

    ...), computational fluid dynamics (CFD) 6 project. Under the project, a proven zonal Navier-Stokes solver was rewritten for scalable parallel performance on both shared memory and distributed memory high performance computers...

  7. High Performance Computing - Power Application Programming Interface Specification.

    Energy Technology Data Exchange (ETDEWEB)

    Laros, James H.,; Kelly, Suzanne M.; Pedretti, Kevin; Grant, Ryan; Olivier, Stephen Lecler; Levenhagen, Michael J.; DeBonis, David

    2014-08-01

    Measuring and controlling the power and energy consumption of high performance computing systems by various components in the software stack is an active research area [13, 3, 5, 10, 4, 21, 19, 16, 7, 17, 20, 18, 11, 1, 6, 14, 12]. Implementations in lower level software layers are beginning to emerge in some production systems, which is very welcome. To be most effective, a portable interface to measurement and control features would significantly facilitate participation by all levels of the software stack. We present a proposal for a standard power Application Programming Interface (API) that endeavors to cover the entire software space, from generic hardware interfaces to the input from the computer facility manager.

  8. Benchmarking high performance computing architectures with CMS’ skeleton framework

    Science.gov (United States)

    Sexton-Kennedy, E.; Gartung, P.; Jones, C. D.

    2017-10-01

    In 2012 CMS evaluated which underlying concurrency technology would be the best to use for its multi-threaded framework. The available technologies were evaluated on the high throughput computing systems dominating the resources in use at that time. A skeleton framework benchmarking suite that emulates the tasks performed within a CMSSW application was used to select Intel’s Thread Building Block library, based on the measured overheads in both memory and CPU on the different technologies benchmarked. In 2016 CMS will get access to high performance computing resources that use new many core architectures; machines such as Cori Phase 1&2, Theta, Mira. Because of this we have revived the 2012 benchmark to test it’s performance and conclusions on these new architectures. This talk will discuss the results of this exercise.

  9. Simple, parallel, high-performance virtual machines for extreme computations

    International Nuclear Information System (INIS)

    Chokoufe Nejad, Bijan; Ohl, Thorsten; Reuter, Jurgen

    2014-11-01

    We introduce a high-performance virtual machine (VM) written in a numerically fast language like Fortran or C to evaluate very large expressions. We discuss the general concept of how to perform computations in terms of a VM and present specifically a VM that is able to compute tree-level cross sections for any number of external legs, given the corresponding byte code from the optimal matrix element generator, O'Mega. Furthermore, this approach allows to formulate the parallel computation of a single phase space point in a simple and obvious way. We analyze hereby the scaling behaviour with multiple threads as well as the benefits and drawbacks that are introduced with this method. Our implementation of a VM can run faster than the corresponding native, compiled code for certain processes and compilers, especially for very high multiplicities, and has in general runtimes in the same order of magnitude. By avoiding the tedious compile and link steps, which may fail for source code files of gigabyte sizes, new processes or complex higher order corrections that are currently out of reach could be evaluated with a VM given enough computing power.

  10. What Physicists Should Know About High Performance Computing - Circa 2002

    Science.gov (United States)

    Frederick, Donald

    2002-08-01

    High Performance Computing (HPC) is a dynamic, cross-disciplinary field that traditionally has involved applied mathematicians, computer scientists, and others primarily from the various disciplines that have been major users of HPC resources - physics, chemistry, engineering, with increasing use by those in the life sciences. There is a technological dynamic that is powered by economic as well as by technical innovations and developments. This talk will discuss practical ideas to be considered when developing numerical applications for research purposes. Even with the rapid pace of development in the field, the author believes that these concepts will not become obsolete for a while, and will be of use to scientists who either are considering, or who have already started down the HPC path. These principles will be applied in particular to current parallel HPC systems, but there will also be references of value to desktop users. The talk will cover such topics as: computing hardware basics, single-cpu optimization, compilers, timing, numerical libraries, debugging and profiling tools and the emergence of Computational Grids.

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

    Science.gov (United States)

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

    2015-04-01

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

  12. Trends in high-performance computing for engineering calculations.

    Science.gov (United States)

    Giles, M B; Reguly, I

    2014-08-13

    High-performance computing has evolved remarkably over the past 20 years, and that progress is likely to continue. However, in recent years, this progress has been achieved through greatly increased hardware complexity with the rise of multicore and manycore processors, and this is affecting the ability of application developers to achieve the full potential of these systems. This article outlines the key developments on the hardware side, both in the recent past and in the near future, with a focus on two key issues: energy efficiency and the cost of moving data. It then discusses the much slower evolution of system software, and the implications of all of this for application developers. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  13. Power/energy use cases for high performance computing

    Energy Technology Data Exchange (ETDEWEB)

    Laros, James H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kelly, Suzanne M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hammond, Steven [National Renewable Energy Lab. (NREL), Golden, CO (United States); Elmore, Ryan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Munch, Kristin [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2013-12-01

    Power and Energy have been identified as a first order challenge for future extreme scale high performance computing (HPC) systems. In practice the breakthroughs will need to be provided by the hardware vendors. But to make the best use of the solutions in an HPC environment, it will likely require periodic tuning by facility operators and software components. This document describes the actions and interactions needed to maximize power resources. It strives to cover the entire operational space in which an HPC system occupies. The descriptions are presented as formal use cases, as documented in the Unified Modeling Language Specification [1]. The document is intended to provide a common understanding to the HPC community of the necessary management and control capabilities. Assuming a common understanding can be achieved, the next step will be to develop a set of Application Programing Interfaces (APIs) to which hardware vendors and software developers could utilize to steer power consumption.

  14. Scalability of DL_POLY on High Performance Computing Platform

    Directory of Open Access Journals (Sweden)

    Mabule Samuel Mabakane

    2017-12-01

    Full Text Available This paper presents a case study on the scalability of several versions of the molecular dynamics code (DL_POLY performed on South Africa‘s Centre for High Performance Computing e1350 IBM Linux cluster, Sun system and Lengau supercomputers. Within this study different problem sizes were designed and the same chosen systems were employed in order to test the performance of DL_POLY using weak and strong scalability. It was found that the speed-up results for the small systems were better than large systems on both Ethernet and Infiniband network. However, simulations of large systems in DL_POLY performed well using Infiniband network on Lengau cluster as compared to e1350 and Sun supercomputer.

  15. Multicore Challenges and Benefits for High Performance Scientific Computing

    Directory of Open Access Journals (Sweden)

    Ida M.B. Nielsen

    2008-01-01

    Full Text Available Until recently, performance gains in processors were achieved largely by improvements in clock speeds and instruction level parallelism. Thus, applications could obtain performance increases with relatively minor changes by upgrading to the latest generation of computing hardware. Currently, however, processor performance improvements are realized by using multicore technology and hardware support for multiple threads within each core, and taking full advantage of this technology to improve the performance of applications requires exposure of extreme levels of software parallelism. We will here discuss the architecture of parallel computers constructed from many multicore chips as well as techniques for managing the complexity of programming such computers, including the hybrid message-passing/multi-threading programming model. We will illustrate these ideas with a hybrid distributed memory matrix multiply and a quantum chemistry algorithm for energy computation using Møller–Plesset perturbation theory.

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

    Science.gov (United States)

    Ahn, Sul-Ah; Jung, Youngim

    2016-10-01

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

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

    Science.gov (United States)

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

    2014-12-01

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

  18. 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,…

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

    Science.gov (United States)

    2016-11-15

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

  20. Real-time Tsunami Inundation Prediction Using High Performance Computers

    Science.gov (United States)

    Oishi, Y.; Imamura, F.; Sugawara, D.

    2014-12-01

    Recently off-shore tsunami observation stations based on cabled ocean bottom pressure gauges are actively being deployed especially in Japan. These cabled systems are designed to provide real-time tsunami data before tsunamis reach coastlines for disaster mitigation purposes. To receive real benefits of these observations, real-time analysis techniques to make an effective use of these data are necessary. A representative study was made by Tsushima et al. (2009) that proposed a method to provide instant tsunami source prediction based on achieving tsunami waveform data. As time passes, the prediction is improved by using updated waveform data. After a tsunami source is predicted, tsunami waveforms are synthesized from pre-computed tsunami Green functions of linear long wave equations. Tsushima et al. (2014) updated the method by combining the tsunami waveform inversion with an instant inversion of coseismic crustal deformation and improved the prediction accuracy and speed in the early stages. For disaster mitigation purposes, real-time predictions of tsunami inundation are also important. In this study, we discuss the possibility of real-time tsunami inundation predictions, which require faster-than-real-time tsunami inundation simulation in addition to instant tsunami source analysis. Although the computational amount is large to solve non-linear shallow water equations for inundation predictions, it has become executable through the recent developments of high performance computing technologies. We conducted parallel computations of tsunami inundation and achieved 6.0 TFLOPS by using 19,000 CPU cores. We employed a leap-frog finite difference method with nested staggered grids of which resolution range from 405 m to 5 m. The resolution ratio of each nested domain was 1/3. Total number of grid points were 13 million, and the time step was 0.1 seconds. Tsunami sources of 2011 Tohoku-oki earthquake were tested. The inundation prediction up to 2 hours after the

  1. High performance computing environment for multidimensional image analysis.

    Science.gov (United States)

    Rao, A Ravishankar; Cecchi, Guillermo A; Magnasco, Marcelo

    2007-07-10

    The processing of images acquired through microscopy is a challenging task due to the large size of datasets (several gigabytes) and the fast turnaround time required. If the throughput of the image processing stage is significantly increased, it can have a major impact in microscopy applications. We present a high performance computing (HPC) solution to this problem. This involves decomposing the spatial 3D image into segments that are assigned to unique processors, and matched to the 3D torus architecture of the IBM Blue Gene/L machine. Communication between segments is restricted to the nearest neighbors. When running on a 2 Ghz Intel CPU, the task of 3D median filtering on a typical 256 megabyte dataset takes two and a half hours, whereas by using 1024 nodes of Blue Gene, this task can be performed in 18.8 seconds, a 478x speedup. Our parallel solution dramatically improves the performance of image processing, feature extraction and 3D reconstruction tasks. This increased throughput permits biologists to conduct unprecedented large scale experiments with massive datasets.

  2. The Future of Software Engineering for High Performance Computing

    Energy Technology Data Exchange (ETDEWEB)

    Pope, G [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-07-16

    DOE ASCR requested that from May through mid-July 2015 a study group identify issues and recommend solutions from a software engineering perspective transitioning into the next generation of High Performance Computing. The approach used was to ask some of the DOE complex experts who will be responsible for doing this work to contribute to the study group. The technique used was to solicit elevator speeches: a short and concise write up done as if the author was a speaker with only a few minutes to convince a decision maker of their top issues. Pages 2-18 contain the original texts of the contributed elevator speeches and end notes identifying the 20 contributors. The study group also ranked the importance of each topic, and those scores are displayed with each topic heading. A perfect score (and highest priority) is three, two is medium priority, and one is lowest priority. The highest scoring topic areas were software engineering and testing resources; the lowest scoring area was compliance to DOE standards. The following two paragraphs are an elevator speech summarizing the contributed elevator speeches. Each sentence or phrase in the summary is hyperlinked to its source via a numeral embedded in the text. A risk one liner has also been added to each topic to allow future risk tracking and mitigation.

  3. A checkpoint compression study for high-performance computing systems

    Energy Technology Data Exchange (ETDEWEB)

    Ibtesham, Dewan [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Computer Science; Ferreira, Kurt B. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States). Scalable System Software Dept.; Arnold, Dorian [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Computer Science

    2015-02-17

    As high-performance computing systems continue to increase in size and complexity, higher failure rates and increased overheads for checkpoint/restart (CR) protocols have raised concerns about the practical viability of CR protocols for future systems. Previously, compression has proven to be a viable approach for reducing checkpoint data volumes and, thereby, reducing CR protocol overhead leading to improved application performance. In this article, we further explore compression-based CR optimization by exploring its baseline performance and scaling properties, evaluating whether improved compression algorithms might lead to even better application performance and comparing checkpoint compression against and alongside other software- and hardware-based optimizations. Our results highlights are: (1) compression is a very viable CR optimization; (2) generic, text-based compression algorithms appear to perform near optimally for checkpoint data compression and faster compression algorithms will not lead to better application performance; (3) compression-based optimizations fare well against and alongside other software-based optimizations; and (4) while hardware-based optimizations outperform software-based ones, they are not as cost effective.

  4. Lightweight Provenance Service for High-Performance Computing

    Energy Technology Data Exchange (ETDEWEB)

    Dai, Dong; Chen, Yong; Carns, Philip; Jenkins, John; Ross, Robert

    2017-09-09

    Provenance describes detailed information about the history of a piece of data, containing the relationships among elements such as users, processes, jobs, and workflows that contribute to the existence of data. Provenance is key to supporting many data management functionalities that are increasingly important in operations such as identifying data sources, parameters, or assumptions behind a given result; auditing data usage; or understanding details about how inputs are transformed into outputs. Despite its importance, however, provenance support is largely underdeveloped in highly parallel architectures and systems. One major challenge is the demanding requirements of providing provenance service in situ. The need to remain lightweight and to be always on often conflicts with the need to be transparent and offer an accurate catalog of details regarding the applications and systems. To tackle this challenge, we introduce a lightweight provenance service, called LPS, for high-performance computing (HPC) systems. LPS leverages a kernel instrument mechanism to achieve transparency and introduces representative execution and flexible granularity to capture comprehensive provenance with controllable overhead. Extensive evaluations and use cases have confirmed its efficiency and usability. We believe that LPS can be integrated into current and future HPC systems to support a variety of data management needs.

  5. Enabling Efficient Climate Science Workflows in High Performance Computing Environments

    Science.gov (United States)

    Krishnan, H.; Byna, S.; Wehner, M. F.; Gu, J.; O'Brien, T. A.; Loring, B.; Stone, D. A.; Collins, W.; Prabhat, M.; Liu, Y.; Johnson, J. N.; Paciorek, C. J.

    2015-12-01

    A typical climate science workflow often involves a combination of acquisition of data, modeling, simulation, analysis, visualization, publishing, and storage of results. Each of these tasks provide a myriad of challenges when running on a high performance computing environment such as Hopper or Edison at NERSC. Hurdles such as data transfer and management, job scheduling, parallel analysis routines, and publication require a lot of forethought and planning to ensure that proper quality control mechanisms are in place. These steps require effectively utilizing a combination of well tested and newly developed functionality to move data, perform analysis, apply statistical routines, and finally, serve results and tools to the greater scientific community. As part of the CAlibrated and Systematic Characterization, Attribution and Detection of Extremes (CASCADE) project we highlight a stack of tools our team utilizes and has developed to ensure that large scale simulation and analysis work are commonplace and provide operations that assist in everything from generation/procurement of data (HTAR/Globus) to automating publication of results to portals like the Earth Systems Grid Federation (ESGF), all while executing everything in between in a scalable environment in a task parallel way (MPI). We highlight the use and benefit of these tools by showing several climate science analysis use cases they have been applied to.

  6. Multi-Language Programming Environments for High Performance Java Computing

    Directory of Open Access Journals (Sweden)

    Vladimir Getov

    1999-01-01

    Full Text Available Recent developments in processor capabilities, software tools, programming languages and programming paradigms have brought about new approaches to high performance computing. A steadfast component of this dynamic evolution has been the scientific community’s reliance on established scientific packages. As a consequence, programmers of high‐performance applications are reluctant to embrace evolving languages such as Java. This paper describes the Java‐to‐C Interface (JCI tool which provides application programmers wishing to use Java with immediate accessibility to existing scientific packages. The JCI tool also facilitates rapid development and reuse of existing code. These benefits are provided at minimal cost to the programmer. While beneficial to the programmer, the additional advantages of mixed‐language programming in terms of application performance and portability are addressed in detail within the context of this paper. In addition, we discuss how the JCI tool is complementing other ongoing projects such as IBM’s High‐Performance Compiler for Java (HPCJ and IceT’s metacomputing environment.

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

    Data.gov (United States)

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

  8. Mixed-Language High-Performance Computing for Plasma Simulations

    Directory of Open Access Journals (Sweden)

    Quanming Lu

    2003-01-01

    Full Text Available Java is receiving increasing attention as the most popular platform for distributed computing. However, programmers are still reluctant to embrace Java as a tool for writing scientific and engineering applications due to its still noticeable performance drawbacks compared with other programming languages such as Fortran or C. In this paper, we present a hybrid Java/Fortran implementation of a parallel particle-in-cell (PIC algorithm for plasma simulations. In our approach, the time-consuming components of this application are designed and implemented as Fortran subroutines, while less calculation-intensive components usually involved in building the user interface are written in Java. The two types of software modules have been glued together using the Java native interface (JNI. Our mixed-language PIC code was tested and its performance compared with pure Java and Fortran versions of the same algorithm on a Sun E6500 SMP system and a Linux cluster of Pentium~III machines.

  9. Electromagnetic Modeling of Human Body Using High Performance Computing

    Science.gov (United States)

    Ng, Cho-Kuen; Beall, Mark; Ge, Lixin; Kim, Sanghoek; Klaas, Ottmar; Poon, Ada

    Realistic simulation of electromagnetic wave propagation in the actual human body can expedite the investigation of the phenomenon of harvesting implanted devices using wireless powering coupled from external sources. The parallel electromagnetics code suite ACE3P developed at SLAC National Accelerator Laboratory is based on the finite element method for high fidelity accelerator simulation, which can be enhanced to model electromagnetic wave propagation in the human body. Starting with a CAD model of a human phantom that is characterized by a number of tissues, a finite element mesh representing the complex geometries of the individual tissues is built for simulation. Employing an optimal power source with a specific pattern of field distribution, the propagation and focusing of electromagnetic waves in the phantom has been demonstrated. Substantial speedup of the simulation is achieved by using multiple compute cores on supercomputers.

  10. High Performance Polar Decomposition on Distributed Memory Systems

    KAUST Repository

    Sukkari, Dalal E.

    2016-08-08

    The polar decomposition of a dense matrix is an important operation in linear algebra. It can be directly calculated through the singular value decomposition (SVD) or iteratively using the QR dynamically-weighted Halley algorithm (QDWH). The former is difficult to parallelize due to the preponderant number of memory-bound operations during the bidiagonal reduction. We investigate the latter scenario, which performs more floating-point operations but exposes at the same time more parallelism, and therefore, runs closer to the theoretical peak performance of the system, thanks to more compute-bound matrix operations. Profiling results show the performance scalability of QDWH for calculating the polar decomposition using around 9200 MPI processes on well and ill-conditioned matrices of 100K×100K problem size. We study then the performance impact of the QDWH-based polar decomposition as a pre-processing step toward calculating the SVD itself. The new distributed-memory implementation of the QDWH-SVD solver achieves up to five-fold speedup against current state-of-the-art vendor SVD implementations. © Springer International Publishing Switzerland 2016.

  11. COMPUTERS: Teraflops for Europe; EEC Working Group on High Performance Computing

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    1991-03-15

    In little more than a decade, simulation on high performance computers has become an essential tool for theoretical physics, capable of solving a vast range of crucial problems inaccessible to conventional analytic mathematics. In many ways, computer simulation has become the calculus for interacting many-body systems, a key to the study of transitions from isolated to collective behaviour.

  12. COMPUTERS: Teraflops for Europe; EEC Working Group on High Performance Computing

    International Nuclear Information System (INIS)

    Anon.

    1991-01-01

    In little more than a decade, simulation on high performance computers has become an essential tool for theoretical physics, capable of solving a vast range of crucial problems inaccessible to conventional analytic mathematics. In many ways, computer simulation has become the calculus for interacting many-body systems, a key to the study of transitions from isolated to collective behaviour

  13. High performance computing network for cloud environment using simulators

    OpenAIRE

    Singh, N. Ajith; Hemalatha, M.

    2012-01-01

    Cloud computing is the next generation computing. Adopting the cloud computing is like signing up new form of a website. The GUI which controls the cloud computing make is directly control the hardware resource and your application. The difficulty part in cloud computing is to deploy in real environment. Its' difficult to know the exact cost and it's requirement until and unless we buy the service not only that whether it will support the existing application which is available on traditional...

  14. Architectural Principles and Experimentation of Distributed High Performance Virtual Clusters

    Science.gov (United States)

    Younge, Andrew J.

    2016-01-01

    With the advent of virtualization and Infrastructure-as-a-Service (IaaS), the broader scientific computing community is considering the use of clouds for their scientific computing needs. This is due to the relative scalability, ease of use, advanced user environment customization abilities, and the many novel computing paradigms available for…

  15. Big Data and High-Performance Computing in Global Seismology

    Science.gov (United States)

    Bozdag, Ebru; Lefebvre, Matthieu; Lei, Wenjie; Peter, Daniel; Smith, James; Komatitsch, Dimitri; Tromp, Jeroen

    2014-05-01

    Much of our knowledge of Earth's interior is based on seismic observations and measurements. Adjoint methods provide an efficient way of incorporating 3D full wave propagation in iterative seismic inversions to enhance tomographic images and thus our understanding of processes taking place inside the Earth. Our aim is to take adjoint tomography, which has been successfully applied to regional and continental scale problems, further to image the entire planet. This is one of the extreme imaging challenges in seismology, mainly due to the intense computational requirements and vast amount of high-quality seismic data that can potentially be assimilated. We have started low-resolution inversions (T > 30 s and T > 60 s for body and surface waves, respectively) with a limited data set (253 carefully selected earthquakes and seismic data from permanent and temporary networks) on Oak Ridge National Laboratory's Cray XK7 "Titan" system. Recent improvements in our 3D global wave propagation solvers, such as a GPU version of the SPECFEM3D_GLOBE package, will enable us perform higher-resolution (T > 9 s) and longer duration (~180 m) simulations to take the advantage of high-frequency body waves and major-arc surface waves, thereby improving imbalanced ray coverage as a result of the uneven global distribution of sources and receivers. Our ultimate goal is to use all earthquakes in the global CMT catalogue within the magnitude range of our interest and data from all available seismic networks. To take the full advantage of computational resources, we need a solid framework to manage big data sets during numerical simulations, pre-processing (i.e., data requests and quality checks, processing data, window selection, etc.) and post-processing (i.e., pre-conditioning and smoothing kernels, etc.). We address the bottlenecks in our global seismic workflow, which are mainly coming from heavy I/O traffic during simulations and the pre- and post-processing stages, by defining new data

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

    International Nuclear Information System (INIS)

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

    2011-01-01

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

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

    International Nuclear Information System (INIS)

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

    1980-08-01

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

  18. How to build a high-performance compute cluster for the Grid

    CERN Document Server

    Reinefeld, A

    2001-01-01

    The success of large-scale multi-national projects like the forthcoming analysis of the LHC particle collision data at CERN relies to a great extent on the ability to efficiently utilize computing and data-storage resources at geographically distributed sites. Currently, much effort is spent on the design of Grid management software (Datagrid, Globus, etc.), while the effective integration of computing nodes has been largely neglected up to now. This is the focus of our work. We present a framework for a high- performance cluster that can be used as a reliable computing node in the Grid. We outline the cluster architecture, the management of distributed data and the seamless integration of the cluster into the Grid environment. (11 refs).

  19. The ongoing investigation of high performance parallel computing in HEP

    CERN Document Server

    Peach, Kenneth J; Böck, R K; Dobinson, Robert W; Hansroul, M; Norton, Alan Robert; Willers, Ian Malcolm; Baud, J P; Carminati, F; Gagliardi, F; McIntosh, E; Metcalf, M; Robertson, L; CERN. Geneva. Detector Research and Development Committee

    1993-01-01

    Past and current exploitation of parallel computing in High Energy Physics is summarized and a list of R & D projects in this area is presented. The applicability of new parallel hardware and software to physics problems is investigated, in the light of the requirements for computing power of LHC experiments and the current trends in the computer industry. Four main themes are discussed (possibilities for a finer grain of parallelism; fine-grain communication mechanism; usable parallel programming environment; different programming models and architectures, using standard commercial products). Parallel computing technology is potentially of interest for offline and vital for real time applications in LHC. A substantial investment in applications development and evaluation of state of the art hardware and software products is needed. A solid development environment is required at an early stage, before mainline LHC program development begins.

  20. Software Applications on the Peregrine System | High-Performance Computing

    Science.gov (United States)

    Algebraic Modeling System (GAMS) Statistics and analysis High-level modeling system for mathematical reactivity. Gurobi Optimizer Statistics and analysis Solver for mathematical programming LAMMPS Chemistry and , reactivities, and vibrational, electronic and NMR spectra. R Statistical Computing Environment Statistics and

  1. Benchmark Numerical Toolkits for High Performance Computing, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Computational codes in physics and engineering often use implicit solution algorithms that require linear algebra tools such as Ax=b solvers, eigenvalue,...

  2. Coping with distributed computing

    International Nuclear Information System (INIS)

    Cormell, L.

    1992-09-01

    The rapid increase in the availability of high performance, cost-effective RISC/UNIX workstations has been both a blessing and a curse. The blessing of having extremely powerful computing engines available on the desk top is well-known to many users. The user has tremendous freedom, flexibility, and control of his environment. That freedom can, however, become the curse of distributed computing. The user must become a system manager to some extent, he must worry about backups, maintenance, upgrades, etc. Traditionally these activities have been the responsibility of a central computing group. The central computing group, however, may find that it can no longer provide all of the traditional services. With the plethora of workstations now found on so many desktops throughout the entire campus or lab, the central computing group may be swamped by support requests. This talk will address several of these computer support and management issues by providing some examples of the approaches taken at various HEP institutions. In addition, a brief review of commercial directions or products for distributed computing and management will be given

  3. Scalability of DL_POLY on High Performance Computing Platform

    CSIR Research Space (South Africa)

    Mabakane, Mabule S

    2017-12-01

    Full Text Available stream_source_info Mabakanea_19979_2017.pdf.txt stream_content_type text/plain stream_size 33716 Content-Encoding UTF-8 stream_name Mabakanea_19979_2017.pdf.txt Content-Type text/plain; charset=UTF-8 SACJ 29(3) December... when using many processors within the compute nodes of the supercomputer. The type of the processors of compute nodes and their memory also play an important role in the overall performance of the parallel application running on a supercomputer. DL...

  4. Running Batch Jobs on Peregrine | High-Performance Computing | NREL

    Science.gov (United States)

    and run your application. Users typically create or edit job scripts using a text editor such as vi Using Resource Feature to Request Different Node Types Peregrine has several types of compute nodes , which differ in the amount of memory and number of processor cores. The majority of the nodes have 24

  5. Running Interactive Jobs on Peregrine | High-Performance Computing | NREL

    Science.gov (United States)

    shell prompt, which allows users to execute commands and scripts as they would on the login nodes. Login performed on the compute nodes rather than on login nodes. This page provides instructions and examples of , start GUIs etc. and the commands will execute on that node instead of on the login node. The -V option

  6. Simulating elastic light scattering using high performance computing methods

    NARCIS (Netherlands)

    Hoekstra, A.G.; Sloot, P.M.A.; Verbraeck, A.; Kerckhoffs, E.J.H.

    1993-01-01

    The Coupled Dipole method, as originally formulated byPurcell and Pennypacker, is a very powerful method tosimulate the Elastic Light Scattering from arbitraryparticles. This method, which is a particle simulationmodel for Computational Electromagnetics, has one majordrawback: if the size of the

  7. High performance computer code for molecular dynamics simulations

    International Nuclear Information System (INIS)

    Levay, I.; Toekesi, K.

    2007-01-01

    Complete text of publication follows. Molecular Dynamics (MD) simulation is a widely used technique for modeling complicated physical phenomena. Since 2005 we are developing a MD simulations code for PC computers. The computer code is written in C++ object oriented programming language. The aim of our work is twofold: a) to develop a fast computer code for the study of random walk of guest atoms in Be crystal, b) 3 dimensional (3D) visualization of the particles motion. In this case we mimic the motion of the guest atoms in the crystal (diffusion-type motion), and the motion of atoms in the crystallattice (crystal deformation). Nowadays, it is common to use Graphics Devices in intensive computational problems. There are several ways to use this extreme processing performance, but never before was so easy to programming these devices as now. The CUDA (Compute Unified Device) Architecture introduced by nVidia Corporation in 2007 is a very useful for every processor hungry application. A Unified-architecture GPU include 96-128, or more stream processors, so the raw calculation performance is 576(!) GFLOPS. It is ten times faster, than the fastest dual Core CPU [Fig.1]. Our improved MD simulation software uses this new technology, which speed up our software and the code run 10 times faster in the critical calculation code segment. Although the GPU is a very powerful tool, it has a strongly paralleled structure. It means, that we have to create an algorithm, which works on several processors without deadlock. Our code currently uses 256 threads, shared and constant on-chip memory, instead of global memory, which is 100 times slower than others. It is possible to implement the total algorithm on GPU, therefore we do not need to download and upload the data in every iteration. On behalf of maximal throughput, every thread run with the same instructions

  8. High performance stream computing for particle beam transport simulations

    International Nuclear Information System (INIS)

    Appleby, R; Bailey, D; Higham, J; Salt, M

    2008-01-01

    Understanding modern particle accelerators requires simulating charged particle transport through the machine elements. These simulations can be very time consuming due to the large number of particles and the need to consider many turns of a circular machine. Stream computing offers an attractive way to dramatically improve the performance of such simulations by calculating the simultaneous transport of many particles using dedicated hardware. Modern Graphics Processing Units (GPUs) are powerful and affordable stream computing devices. The results of simulations of particle transport through the booster-to-storage-ring transfer line of the DIAMOND synchrotron light source using an NVidia GeForce 7900 GPU are compared to the standard transport code MAD. It is found that particle transport calculations are suitable for stream processing and large performance increases are possible. The accuracy and potential speed gains are compared and the prospects for future work in the area are discussed

  9. A high level language for a high performance computer

    Science.gov (United States)

    Perrott, R. H.

    1978-01-01

    The proposed computational aerodynamic facility will join the ranks of the supercomputers due to its architecture and increased execution speed. At present, the languages used to program these supercomputers have been modifications of programming languages which were designed many years ago for sequential machines. A new programming language should be developed based on the techniques which have proved valuable for sequential programming languages and incorporating the algorithmic techniques required for these supercomputers. The design objectives for such a language are outlined.

  10. WinHPC System Configuration | High-Performance Computing | NREL

    Science.gov (United States)

    ), login node (WinHPC02) and worker/compute nodes. The head node acts as the file, DNS, and license server . The login node is where the users connect to access the cluster. Node 03 has dual Intel Xeon E5530 2008 R2 HPC Edition. The login node, WinHPC02, is where users login to access the system. This is where

  11. Architecture and Programming Models for High Performance Intensive Computation

    Science.gov (United States)

    2016-06-29

    commands from the data processing center to the sensors is needed. It has been noted that the ubiquity of mobile communication devices offers the...commands from a Processing Facility by way of mobile Relay Stations. The activity of each component of this model other than the Merge module can be...evaluation of the initial system implementation. Gao also was in charge of the development of Fresh Breeze architecture backend on new many-core computers

  12. Using High Performance Computing to Support Water Resource Planning

    Energy Technology Data Exchange (ETDEWEB)

    Groves, David G. [RAND Corporation, Santa Monica, CA (United States); Lembert, Robert J. [RAND Corporation, Santa Monica, CA (United States); May, Deborah W. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Leek, James R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Syme, James [RAND Corporation, Santa Monica, CA (United States)

    2015-10-22

    In recent years, decision support modeling has embraced deliberation-withanalysis— an iterative process in which decisionmakers come together with experts to evaluate a complex problem and alternative solutions in a scientifically rigorous and transparent manner. Simulation modeling supports decisionmaking throughout this process; visualizations enable decisionmakers to assess how proposed strategies stand up over time in uncertain conditions. But running these simulation models over standard computers can be slow. This, in turn, can slow the entire decisionmaking process, interrupting valuable interaction between decisionmakers and analytics.

  13. Detecting Distributed Scans Using High-Performance Query-DrivenVisualization

    Energy Technology Data Exchange (ETDEWEB)

    Stockinger, Kurt; Bethel, E. Wes; Campbell, Scott; Dart, Eli; Wu,Kesheng

    2006-09-01

    Modern forensic analytics applications, like network trafficanalysis, perform high-performance hypothesis testing, knowledgediscovery and data mining on very large datasets. One essential strategyto reduce the time required for these operations is to select only themost relevant data records for a given computation. In this paper, wepresent a set of parallel algorithms that demonstrate how an efficientselection mechanism -- bitmap indexing -- significantly speeds up acommon analysist ask, namely, computing conditional histogram on verylarge datasets. We present a thorough study of the performancecharacteristics of the parallel conditional histogram algorithms. Asacase study, we compute conditional histograms for detecting distributedscans hidden in a dataset consisting of approximately 2.5 billion networkconnection records. We show that these conditional histograms can becomputed on interactive timescale (i.e., in seconds). We also show how toprogressively modify the selection criteria to narrow the analysis andfind the sources of the distributed scans.

  14. High performance statistical computing with parallel R: applications to biology and climate modelling

    International Nuclear Information System (INIS)

    Samatova, Nagiza F; Branstetter, Marcia; Ganguly, Auroop R; Hettich, Robert; Khan, Shiraj; Kora, Guruprasad; Li, Jiangtian; Ma, Xiaosong; Pan, Chongle; Shoshani, Arie; Yoginath, Srikanth

    2006-01-01

    Ultrascale computing and high-throughput experimental technologies have enabled the production of scientific data about complex natural phenomena. With this opportunity, comes a new problem - the massive quantities of data so produced. Answers to fundamental questions about the nature of those phenomena remain largely hidden in the produced data. The goal of this work is to provide a scalable high performance statistical data analysis framework to help scientists perform interactive analyses of these raw data to extract knowledge. Towards this goal we have been developing an open source parallel statistical analysis package, called Parallel R, that lets scientists employ a wide range of statistical analysis routines on high performance shared and distributed memory architectures without having to deal with the intricacies of parallelizing these routines

  15. Interactive Data Exploration for High-Performance Fluid Flow Computations through Porous Media

    KAUST Repository

    Perovic, Nevena

    2014-09-01

    © 2014 IEEE. Huge data advent in high-performance computing (HPC) applications such as fluid flow simulations usually hinders the interactive processing and exploration of simulation results. Such an interactive data exploration not only allows scientiest to \\'play\\' with their data but also to visualise huge (distributed) data sets in both an efficient and easy way. Therefore, we propose an HPC data exploration service based on a sliding window concept, that enables researches to access remote data (available on a supercomputer or cluster) during simulation runtime without exceeding any bandwidth limitations between the HPC back-end and the user front-end.

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

    International Nuclear Information System (INIS)

    Lederer, H

    2008-01-01

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

  17. PGHPF – An Optimizing High Performance Fortran Compiler for Distributed Memory Machines

    Directory of Open Access Journals (Sweden)

    Zeki Bozkus

    1997-01-01

    Full Text Available High Performance Fortran (HPF is the first widely supported, efficient, and portable parallel programming language for shared and distributed memory systems. HPF is realized through a set of directive-based extensions to Fortran 90. It enables application developers and Fortran end-users to write compact, portable, and efficient software that will compile and execute on workstations, shared memory servers, clusters, traditional supercomputers, or massively parallel processors. This article describes a production-quality HPF compiler for a set of parallel machines. Compilation techniques such as data and computation distribution, communication generation, run-time support, and optimization issues are elaborated as the basis for an HPF compiler implementation on distributed memory machines. The performance of this compiler on benchmark programs demonstrates that high efficiency can be achieved executing HPF code on parallel architectures.

  18. A Linear Algebra Framework for Static High Performance Fortran Code Distribution

    Directory of Open Access Journals (Sweden)

    Corinne Ancourt

    1997-01-01

    Full Text Available High Performance Fortran (HPF was developed to support data parallel programming for single-instruction multiple-data (SIMD and multiple-instruction multiple-data (MIMD machines with distributed memory. The programmer is provided a familiar uniform logical address space and specifies the data distribution by directives. The compiler then exploits these directives to allocate arrays in the local memories, to assign computations to elementary processors, and to migrate data between processors when required. We show here that linear algebra is a powerful framework to encode HPF directives and to synthesize distributed code with space-efficient array allocation, tight loop bounds, and vectorized communications for INDEPENDENT loops. The generated code includes traditional optimizations such as guard elimination, message vectorization and aggregation, and overlap analysis. The systematic use of an affine framework makes it possible to prove the compilation scheme correct.

  19. Generalized Portable SHMEM Library for High Performance Computing

    Energy Technology Data Exchange (ETDEWEB)

    Parzyszek, Krzysztof [Iowa State Univ., Ames, IA (United States)

    2003-01-01

    This dissertation describes the efforts to design and implement the Generalized Portable SHMEM library, GPSHMEM, as well as supplementary tools. There are two major components of the GPSHMEM project: the GPSHMEM library itself and the Fortran 77 source-to-source translator. The rest of this thesis is divided into two parts. Part I introduces the shared memory model and the distributed shared memory model. It explains the motivation behind GPSHMEM and presents its functionality and performance results. Part II is entirely devoted to the Fortran 77 translator call fgpp. The need for such a tool is demonstrated, functionality goals are stated, and the design issues are presented along with the development of the solutions.

  20. FY 1992 Blue Book: Grand Challenges: High Performance Computing and Communications

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — High performance computing and computer communications networks are becoming increasingly important to scientific advancement, economic competition, and national...

  1. FY 1993 Blue Book: Grand Challenges 1993: High Performance Computing and Communications

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — High performance computing and computer communications networks are becoming increasingly important to scientific advancement, economic competition, and national...

  2. The contribution of high-performance computing and modelling for industrial development

    CSIR Research Space (South Africa)

    Sithole, Happy

    2017-10-01

    Full Text Available Performance Computing and Modelling for Industrial Development Dr Happy Sithole and Dr Onno Ubbink 2 Strategic context • High-performance computing (HPC) combined with machine Learning and artificial intelligence present opportunities to non...

  3. Use of high performance computing to examine the effectiveness of aquifer remediation

    International Nuclear Information System (INIS)

    Tompson, A.F.B.; Ashby, S.F.; Falgout, R.D.; Smith, S.G.; Fogwell, T.W.; Loosmore, G.A.

    1994-06-01

    Large-scale simulation of fluid flow and chemical migration is being used to study the effectiveness of pump-and-treat restoration of a contaminated, saturated aquifer. A three-element approach focusing on geostatistical representations of heterogeneous aquifers, high-performance computing strategies for simulating flow, migration, and reaction processes in large three-dimensional systems, and highly-resolved simulations of flow and chemical migration in porous formations will be discussed. Results from a preliminary application of this approach to examine pumping behavior at a real, heterogeneous field site will be presented. Future activities will emphasize parallel computations in larger, dynamic, and nonlinear (two-phase) flow problems as well as improved interpretive methods for defining detailed material property distributions

  4. Analysis and modeling of social influence in high performance computing workloads

    KAUST Repository

    Zheng, Shuai

    2011-01-01

    Social influence among users (e.g., collaboration on a project) creates bursty behavior in the underlying high performance computing (HPC) workloads. Using representative HPC and cluster workload logs, this paper identifies, analyzes, and quantifies the level of social influence across HPC users. We show the existence of a social graph that is characterized by a pattern of dominant users and followers. This pattern also follows a power-law distribution, which is consistent with those observed in mainstream social networks. Given its potential impact on HPC workloads prediction and scheduling, we propose a fast-converging, computationally-efficient online learning algorithm for identifying social groups. Extensive evaluation shows that our online algorithm can (1) quickly identify the social relationships by using a small portion of incoming jobs and (2) can efficiently track group evolution over time. © 2011 Springer-Verlag.

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

    Science.gov (United States)

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

    2012-09-01

    , and so the costs of running applications vary widely according to how they use resources. The cloud is well suited to processing CPU-bound (and memory bound) workflows such as the periodogram code, given the relatively low cost of processing in comparison with I/O operations. I/O-bound applications such as Montage perform best on high-performance clusters with fast networks and parallel file-systems. Science-driven Cyberinfrastructure: Montage has been widely used as a driver application to develop workflow management services, such as task scheduling in distributed environments, designing fault tolerance techniques for job schedulers, and developing workflow orchestration techniques. Running Parallel Applications Across Distributed Cloud Environments: Data processing will eventually take place in parallel distributed across cyber infrastructure environments having different architectures. We have used the Pegasus Work Management System (WMS) to successfully run applications across three very different environments: TeraGrid, OSG (Open Science Grid), and FutureGrid. Provisioning resources across different grids and clouds (also referred to as Sky Computing), involves establishing a distributed environment, where issues of, e.g, remote job submission, data management, and security need to be addressed. This environment also requires building virtual machine images that can run in different environments. Usually, each cloud provides basic images that can be customized with additional software and services. In most of our work, we provisioned compute resources using a custom application, called Wrangler. Pegasus WMS abstracts the architectures of the compute environments away from the end-user, and can be considered a first-generation tool suitable for scientists to run their applications on disparate environments.

  6. Distributed multiscale computing

    NARCIS (Netherlands)

    Borgdorff, J.

    2014-01-01

    Multiscale models combine knowledge, data, and hypotheses from different scales. Simulating a multiscale model often requires extensive computation. This thesis evaluates distributing these computations, an approach termed distributed multiscale computing (DMC). First, the process of multiscale

  7. High performance parallel computers for science: New developments at the Fermilab advanced computer program

    International Nuclear Information System (INIS)

    Nash, T.; Areti, H.; Atac, R.

    1988-08-01

    Fermilab's Advanced Computer Program (ACP) has been developing highly cost effective, yet practical, parallel computers for high energy physics since 1984. The ACP's latest developments are proceeding in two directions. A Second Generation ACP Multiprocessor System for experiments will include $3500 RISC processors each with performance over 15 VAX MIPS. To support such high performance, the new system allows parallel I/O, parallel interprocess communication, and parallel host processes. The ACP Multi-Array Processor, has been developed for theoretical physics. Each $4000 node is a FORTRAN or C programmable pipelined 20 MFlops (peak), 10 MByte single board computer. These are plugged into a 16 port crossbar switch crate which handles both inter and intra crate communication. The crates are connected in a hypercube. Site oriented applications like lattice gauge theory are supported by system software called CANOPY, which makes the hardware virtually transparent to users. A 256 node, 5 GFlop, system is under construction. 10 refs., 7 figs

  8. CUDA/GPU Technology : Parallel Programming For High Performance Scientific Computing

    OpenAIRE

    YUHENDRA; KUZE, Hiroaki; JOSAPHAT, Tetuko Sri Sumantyo

    2009-01-01

    [ABSTRACT]Graphics processing units (GP Us) originally designed for computer video cards have emerged as the most powerful chip in a high-performance workstation. In the high performance computation capabilities, graphic processing units (GPU) lead to much more powerful performance than conventional CPUs by means of parallel processing. In 2007, the birth of Compute Unified Device Architecture (CUDA) and CUDA-enabled GPUs by NVIDIA Corporation brought a revolution in the general purpose GPU a...

  9. Implementing Molecular Dynamics for Hybrid High Performance Computers - 1. Short Range Forces

    International Nuclear Information System (INIS)

    Brown, W. Michael; Wang, Peng; Plimpton, Steven J.; Tharrington, Arnold N.

    2011-01-01

    The use of accelerators such as general-purpose graphics processing units (GPGPUs) have become popular in scientific computing applications due to their low cost, impressive floating-point capabilities, high memory bandwidth, and low electrical power requirements. Hybrid high performance computers, machines with more than one type of floating-point processor, are now becoming more prevalent due to these advantages. In this work, we discuss several important issues in porting a large molecular dynamics code for use on parallel hybrid machines - (1) choosing a hybrid parallel decomposition that works on central processing units (CPUs) with distributed memory and accelerator cores with shared memory, (2) minimizing the amount of code that must be ported for efficient acceleration, (3) utilizing the available processing power from both many-core CPUs and accelerators, and (4) choosing a programming model for acceleration. We present our solution to each of these issues for short-range force calculation in the molecular dynamics package LAMMPS. We describe algorithms for efficient short range force calculation on hybrid high performance machines. We describe a new approach for dynamic load balancing of work between CPU and accelerator cores. We describe the Geryon library that allows a single code to compile with both CUDA and OpenCL for use on a variety of accelerators. Finally, we present results on a parallel test cluster containing 32 Fermi GPGPUs and 180 CPU cores.

  10. Department of Energy Mathematical, Information, and Computational Sciences Division: High Performance Computing and Communications Program

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-11-01

    This document is intended to serve two purposes. Its first purpose is that of a program status report of the considerable progress that the Department of Energy (DOE) has made since 1993, the time of the last such report (DOE/ER-0536, The DOE Program in HPCC), toward achieving the goals of the High Performance Computing and Communications (HPCC) Program. The second purpose is that of a summary report of the many research programs administered by the Mathematical, Information, and Computational Sciences (MICS) Division of the Office of Energy Research under the auspices of the HPCC Program and to provide, wherever relevant, easy access to pertinent information about MICS-Division activities via universal resource locators (URLs) on the World Wide Web (WWW).

  11. Department of Energy: MICS (Mathematical Information, and Computational Sciences Division). High performance computing and communications program

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-06-01

    This document is intended to serve two purposes. Its first purpose is that of a program status report of the considerable progress that the Department of Energy (DOE) has made since 1993, the time of the last such report (DOE/ER-0536, {open_quotes}The DOE Program in HPCC{close_quotes}), toward achieving the goals of the High Performance Computing and Communications (HPCC) Program. The second purpose is that of a summary report of the many research programs administered by the Mathematical, Information, and Computational Sciences (MICS) Division of the Office of Energy Research under the auspices of the HPCC Program and to provide, wherever relevant, easy access to pertinent information about MICS-Division activities via universal resource locators (URLs) on the World Wide Web (WWW). The information pointed to by the URL is updated frequently, and the interested reader is urged to access the WWW for the latest information.

  12. DDT: A Research Tool for Automatic Data Distribution in High Performance Fortran

    Directory of Open Access Journals (Sweden)

    Eduard AyguadÉ

    1997-01-01

    Full Text Available This article describes the main features and implementation of our automatic data distribution research tool. The tool (DDT accepts programs written in Fortran 77 and generates High Performance Fortran (HPF directives to map arrays onto the memories of the processors and parallelize loops, and executable statements to remap these arrays. DDT works by identifying a set of computational phases (procedures and loops. The algorithm builds a search space of candidate solutions for these phases which is explored looking for the combination that minimizes the overall cost; this cost includes data movement cost and computation cost. The movement cost reflects the cost of accessing remote data during the execution of a phase and the remapping costs that have to be paid in order to execute the phase with the selected mapping. The computation cost includes the cost of executing a phase in parallel according to the selected mapping and the owner computes rule. The tool supports interprocedural analysis and uses control flow information to identify how phases are sequenced during the execution of the application.

  13. Scientific Grand Challenges: Forefront Questions in Nuclear Science and the Role of High Performance Computing

    International Nuclear Information System (INIS)

    Khaleel, Mohammad A.

    2009-01-01

    This report is an account of the deliberations and conclusions of the workshop on 'Forefront Questions in Nuclear Science and the Role of High Performance Computing' held January 26-28, 2009, co-sponsored by the U.S. Department of Energy (DOE) Office of Nuclear Physics (ONP) and the DOE Office of Advanced Scientific Computing (ASCR). Representatives from the national and international nuclear physics communities, as well as from the high performance computing community, participated. The purpose of this workshop was to (1) identify forefront scientific challenges in nuclear physics and then determine which-if any-of these could be aided by high performance computing at the extreme scale; (2) establish how and why new high performance computing capabilities could address issues at the frontiers of nuclear science; (3) provide nuclear physicists the opportunity to influence the development of high performance computing; and (4) provide the nuclear physics community with plans for development of future high performance computing capability by DOE ASCR.

  14. Scientific Grand Challenges: Forefront Questions in Nuclear Science and the Role of High Performance Computing

    Energy Technology Data Exchange (ETDEWEB)

    Khaleel, Mohammad A.

    2009-10-01

    This report is an account of the deliberations and conclusions of the workshop on "Forefront Questions in Nuclear Science and the Role of High Performance Computing" held January 26-28, 2009, co-sponsored by the U.S. Department of Energy (DOE) Office of Nuclear Physics (ONP) and the DOE Office of Advanced Scientific Computing (ASCR). Representatives from the national and international nuclear physics communities, as well as from the high performance computing community, participated. The purpose of this workshop was to 1) identify forefront scientific challenges in nuclear physics and then determine which-if any-of these could be aided by high performance computing at the extreme scale; 2) establish how and why new high performance computing capabilities could address issues at the frontiers of nuclear science; 3) provide nuclear physicists the opportunity to influence the development of high performance computing; and 4) provide the nuclear physics community with plans for development of future high performance computing capability by DOE ASCR.

  15. Parameters that affect parallel processing for computational electromagnetic simulation codes on high performance computing clusters

    Science.gov (United States)

    Moon, Hongsik

    changing computer hardware platforms in order to provide fast, accurate and efficient solutions to large, complex electromagnetic problems. The research in this dissertation proves that the performance of parallel code is intimately related to the configuration of the computer hardware and can be maximized for different hardware platforms. To benchmark and optimize the performance of parallel CEM software, a variety of large, complex projects are created and executed on a variety of computer platforms. The computer platforms used in this research are detailed in this dissertation. The projects run as benchmarks are also described in detail and results are presented. The parameters that affect parallel CEM software on High Performance Computing Clusters (HPCC) are investigated. This research demonstrates methods to maximize the performance of parallel CEM software code.

  16. A performance model for the communication in fast multipole methods on high-performance computing platforms

    KAUST Repository

    Ibeid, Huda; Yokota, Rio; Keyes, David E.

    2016-01-01

    model and the actual communication time on four high-performance computing (HPC) systems, when latency, bandwidth, network topology, and multicore penalties are all taken into account. To our knowledge, this is the first formal characterization

  17. Spatial Processing of Urban Acoustic Wave Fields from High-Performance Computations

    National Research Council Canada - National Science Library

    Ketcham, Stephen A; Wilson, D. K; Cudney, Harley H; Parker, Michael W

    2007-01-01

    .... The objective of this work is to develop spatial processing techniques for acoustic wave propagation data from three-dimensional high-performance computations to quantify scattering due to urban...

  18. FY 1996 Blue Book: High Performance Computing and Communications: Foundations for America`s Information Future

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — The Federal High Performance Computing and Communications HPCC Program will celebrate its fifth anniversary in October 1996 with an impressive array of...

  19. Optical high-performance computing: introduction to the JOSA A and Applied Optics feature.

    Science.gov (United States)

    Caulfield, H John; Dolev, Shlomi; Green, William M J

    2009-08-01

    The feature issues in both Applied Optics and the Journal of the Optical Society of America A focus on topics of immediate relevance to the community working in the area of optical high-performance computing.

  20. FY 1997 Blue Book: High Performance Computing and Communications: Advancing the Frontiers of Information Technology

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — The Federal High Performance Computing and Communications HPCC Program will celebrate its fifth anniversary in October 1996 with an impressive array of...

  1. Can We Build a Truly High Performance Computer Which is Flexible and Transparent?

    KAUST Repository

    Rojas, Jhonathan Prieto; Sevilla, Galo T.; Hussain, Muhammad Mustafa

    2013-01-01

    cost advantage. In that context, low-cost mono-crystalline bulk silicon (100) based high performance transistors are considered as the heart of today's computers. One limitation is silicon's rigidity and brittleness. Here we show a generic batch process

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

    Data.gov (United States)

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

  3. Analysis and modeling of social influence in high performance computing workloads

    KAUST Repository

    Zheng, Shuai; Shae, Zon Yin; Zhang, Xiangliang; Jamjoom, Hani T.; Fong, Liana

    2011-01-01

    Social influence among users (e.g., collaboration on a project) creates bursty behavior in the underlying high performance computing (HPC) workloads. Using representative HPC and cluster workload logs, this paper identifies, analyzes, and quantifies

  4. Export Controls: Implementation of the 1998 Legislative Mandate for High Performance Computers

    National Research Council Canada - National Science Library

    1999-01-01

    We found that most of the 938 proposed exports of high performance computers to civilian end users in countries of concern from February 3, 1998, when procedures implementing the 1998 authorization...

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

    Science.gov (United States)

    Baxter, C.; Matott, L.

    2012-12-01

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

  6. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-08-01

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

  8. 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.

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

    Science.gov (United States)

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

    2018-05-03

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

  10. High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

    Science.gov (United States)

    Maly, K.

    1998-01-01

    Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated

  11. High-performance computing on GPUs for resistivity logging of oil and gas wells

    Science.gov (United States)

    Glinskikh, V.; Dudaev, A.; Nechaev, O.; Surodina, I.

    2017-10-01

    We developed and implemented into software an algorithm for high-performance simulation of electrical logs from oil and gas wells using high-performance heterogeneous computing. The numerical solution of the 2D forward problem is based on the finite-element method and the Cholesky decomposition for solving a system of linear algebraic equations (SLAE). Software implementations of the algorithm used the NVIDIA CUDA technology and computing libraries are made, allowing us to perform decomposition of SLAE and find its solution on central processor unit (CPU) and graphics processor unit (GPU). The calculation time is analyzed depending on the matrix size and number of its non-zero elements. We estimated the computing speed on CPU and GPU, including high-performance heterogeneous CPU-GPU computing. Using the developed algorithm, we simulated resistivity data in realistic models.

  12. Analysis and Modeling of Social In uence in High Performance Computing Workloads

    KAUST Repository

    Zheng, Shuai

    2011-06-01

    High Performance Computing (HPC) is becoming a common tool in many research areas. Social influence (e.g., project collaboration) among increasing users of HPC systems creates bursty behavior in underlying workloads. This bursty behavior is increasingly common with the advent of grid computing and cloud computing. Mining the user bursty behavior is important for HPC workloads prediction and scheduling, which has direct impact on overall HPC computing performance. A representative work in this area is the Mixed User Group Model (MUGM), which clusters users according to the resource demand features of their submissions, such as duration time and parallelism. However, MUGM has some difficulties when implemented in real-world system. First, representing user behaviors by the features of their resource demand is usually difficult. Second, these features are not always available. Third, measuring the similarities among users is not a well-defined problem. In this work, we propose a Social Influence Model (SIM) to identify, analyze, and quantify the level of social influence across HPC users. The advantage of the SIM model is that it finds HPC communities by analyzing user job submission time, thereby avoiding the difficulties of MUGM. An offline algorithm and a fast-converging, computationally-efficient online learning algorithm for identifying social groups are proposed. Both offline and online algorithms are applied on several HPC and grid workloads, including Grid 5000, EGEE 2005 and 2007, and KAUST Supercomputing Lab (KSL) BGP data. From the experimental results, we show the existence of a social graph, which is characterized by a pattern of dominant users and followers. In order to evaluate the effectiveness of identified user groups, we show the pattern discovered by the offline algorithm follows a power-law distribution, which is consistent with those observed in mainstream social networks. We finally conclude the thesis and discuss future directions of our work.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-03-01

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

  14. High performance computing in science and engineering Garching/Munich 2016

    Energy Technology Data Exchange (ETDEWEB)

    Wagner, Siegfried; Bode, Arndt; Bruechle, Helmut; Brehm, Matthias (eds.)

    2016-11-01

    Computer simulations are the well-established third pillar of natural sciences along with theory and experimentation. Particularly high performance computing is growing fast and constantly demands more and more powerful machines. To keep pace with this development, in spring 2015, the Leibniz Supercomputing Centre installed the high performance computing system SuperMUC Phase 2, only three years after the inauguration of its sibling SuperMUC Phase 1. Thereby, the compute capabilities were more than doubled. This book covers the time-frame June 2014 until June 2016. Readers will find many examples of outstanding research in the more than 130 projects that are covered in this book, with each one of these projects using at least 4 million core-hours on SuperMUC. The largest scientific communities using SuperMUC in the last two years were computational fluid dynamics simulations, chemistry and material sciences, astrophysics, and life sciences.

  15. The Convergence of High Performance Computing and Large Scale Data Analytics

    Science.gov (United States)

    Duffy, D.; Bowen, M. K.; Thompson, J. H.; Yang, C. P.; Hu, F.; Wills, B.

    2015-12-01

    As the combinations of remote sensing observations and model outputs have grown, scientists are increasingly burdened with both the necessity and complexity of large-scale data analysis. Scientists are increasingly applying traditional high performance computing (HPC) solutions to solve their "Big Data" problems. While this approach has the benefit of limiting data movement, the HPC system is not optimized to run analytics, which can create problems that permeate throughout the HPC environment. To solve these issues and to alleviate some of the strain on the HPC environment, the NASA Center for Climate Simulation (NCCS) has created the Advanced Data Analytics Platform (ADAPT), which combines both HPC and cloud technologies to create an agile system designed for analytics. Large, commonly used data sets are stored in this system in a write once/read many file system, such as Landsat, MODIS, MERRA, and NGA. High performance virtual machines are deployed and scaled according to the individual scientist's requirements specifically for data analysis. On the software side, the NCCS and GMU are working with emerging commercial technologies and applying them to structured, binary scientific data in order to expose the data in new ways. Native NetCDF data is being stored within a Hadoop Distributed File System (HDFS) enabling storage-proximal processing through MapReduce while continuing to provide accessibility of the data to traditional applications. Once the data is stored within HDFS, an additional indexing scheme is built on top of the data and placed into a relational database. This spatiotemporal index enables extremely fast mappings of queries to data locations to dramatically speed up analytics. These are some of the first steps toward a single unified platform that optimizes for both HPC and large-scale data analysis, and this presentation will elucidate the resulting and necessary exascale architectures required for future systems.

  16. A performance model for the communication in fast multipole methods on high-performance computing platforms

    KAUST Repository

    Ibeid, Huda

    2016-03-04

    Exascale systems are predicted to have approximately 1 billion cores, assuming gigahertz cores. Limitations on affordable network topologies for distributed memory systems of such massive scale bring new challenges to the currently dominant parallel programing model. Currently, there are many efforts to evaluate the hardware and software bottlenecks of exascale designs. It is therefore of interest to model application performance and to understand what changes need to be made to ensure extrapolated scalability. The fast multipole method (FMM) was originally developed for accelerating N-body problems in astrophysics and molecular dynamics but has recently been extended to a wider range of problems. Its high arithmetic intensity combined with its linear complexity and asynchronous communication patterns make it a promising algorithm for exascale systems. In this paper, we discuss the challenges for FMM on current parallel computers and future exascale architectures, with a focus on internode communication. We focus on the communication part only; the efficiency of the computational kernels are beyond the scope of the present study. We develop a performance model that considers the communication patterns of the FMM and observe a good match between our model and the actual communication time on four high-performance computing (HPC) systems, when latency, bandwidth, network topology, and multicore penalties are all taken into account. To our knowledge, this is the first formal characterization of internode communication in FMM that validates the model against actual measurements of communication time. The ultimate communication model is predictive in an absolute sense; however, on complex systems, this objective is often out of reach or of a difficulty out of proportion to its benefit when there exists a simpler model that is inexpensive and sufficient to guide coding decisions leading to improved scaling. The current model provides such guidance.

  17. High Performance Numerical Computing for High Energy Physics: A New Challenge for Big Data Science

    International Nuclear Information System (INIS)

    Pop, Florin

    2014-01-01

    Modern physics is based on both theoretical analysis and experimental validation. Complex scenarios like subatomic dimensions, high energy, and lower absolute temperature are frontiers for many theoretical models. Simulation with stable numerical methods represents an excellent instrument for high accuracy analysis, experimental validation, and visualization. High performance computing support offers possibility to make simulations at large scale, in parallel, but the volume of data generated by these experiments creates a new challenge for Big Data Science. This paper presents existing computational methods for high energy physics (HEP) analyzed from two perspectives: numerical methods and high performance computing. The computational methods presented are Monte Carlo methods and simulations of HEP processes, Markovian Monte Carlo, unfolding methods in particle physics, kernel estimation in HEP, and Random Matrix Theory used in analysis of particles spectrum. All of these methods produce data-intensive applications, which introduce new challenges and requirements for ICT systems architecture, programming paradigms, and storage capabilities.

  18. 14th annual Results and Review Workshop on High Performance Computing in Science and Engineering

    CERN Document Server

    Nagel, Wolfgang E; Resch, Michael M; Transactions of the High Performance Computing Center, Stuttgart (HLRS) 2011; High Performance Computing in Science and Engineering '11

    2012-01-01

    This book presents the state-of-the-art in simulation on supercomputers. Leading researchers present results achieved on systems of the High Performance Computing Center Stuttgart (HLRS) for the year 2011. The reports cover all fields of computational science and engineering, ranging from CFD to computational physics and chemistry, to computer science, with a special emphasis on industrially relevant applications. Presenting results for both vector systems and microprocessor-based systems, the book allows readers to compare the performance levels and usability of various architectures. As HLRS

  19. InfoMall: An Innovative Strategy for High-Performance Computing and Communications Applications Development.

    Science.gov (United States)

    Mills, Kim; Fox, Geoffrey

    1994-01-01

    Describes the InfoMall, a program led by the Northeast Parallel Architectures Center (NPAC) at Syracuse University (New York). The InfoMall features a partnership of approximately 24 organizations offering linked programs in High Performance Computing and Communications (HPCC) technology integration, software development, marketing, education and…

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

    Science.gov (United States)

    Eurich, Markus; Calleja, Paul; Boutellier, Roman

    2013-01-01

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

  1. High-Performance Computing in Neuroscience for Data-Driven Discovery, Integration, and Dissemination

    International Nuclear Information System (INIS)

    Bouchard, Kristofer E.

    2016-01-01

    A lack of coherent plans to analyze, manage, and understand data threatens the various opportunities offered by new neuro-technologies. High-performance computing will allow exploratory analysis of massive datasets stored in standardized formats, hosted in open repositories, and integrated with simulations.

  2. Requirements for high performance computing for lattice QCD. Report of the ECFA working panel

    International Nuclear Information System (INIS)

    Jegerlehner, F.; Kenway, R.D.; Martinelli, G.; Michael, C.; Pene, O.; Petersson, B.; Petronzio, R.; Sachrajda, C.T.; Schilling, K.

    2000-01-01

    This report, prepared at the request of the European Committee for Future Accelerators (ECFA), contains an assessment of the High Performance Computing resources which will be required in coming years by European physicists working in Lattice Field Theory and a review of the scientific opportunities which these resources would open. (orig.)

  3. The high performance cluster computing system for BES offline data analysis

    International Nuclear Information System (INIS)

    Sun Yongzhao; Xu Dong; Zhang Shaoqiang; Yang Ting

    2004-01-01

    A high performance cluster computing system (EPCfarm) is introduced, which used for BES offline data analysis. The setup and the characteristics of the hardware and software of EPCfarm are described. The PBS, a queue management package, and the performance of EPCfarm is presented also. (authors)

  4. STEMsalabim: A high-performance computing cluster friendly code for scanning transmission electron microscopy image simulations of thin specimens

    International Nuclear Information System (INIS)

    Oelerich, Jan Oliver; Duschek, Lennart; Belz, Jürgen; Beyer, Andreas; Baranovskii, Sergei D.; Volz, Kerstin

    2017-01-01

    Highlights: • We present STEMsalabim, a modern implementation of the multislice algorithm for simulation of STEM images. • Our package is highly parallelizable on high-performance computing clusters, combining shared and distributed memory architectures. • With STEMsalabim, computationally and memory expensive STEM image simulations can be carried out within reasonable time. - Abstract: We present a new multislice code for the computer simulation of scanning transmission electron microscope (STEM) images based on the frozen lattice approximation. Unlike existing software packages, the code is optimized to perform well on highly parallelized computing clusters, combining distributed and shared memory architectures. This enables efficient calculation of large lateral scanning areas of the specimen within the frozen lattice approximation and fine-grained sweeps of parameter space.

  5. STEMsalabim: A high-performance computing cluster friendly code for scanning transmission electron microscopy image simulations of thin specimens

    Energy Technology Data Exchange (ETDEWEB)

    Oelerich, Jan Oliver, E-mail: jan.oliver.oelerich@physik.uni-marburg.de; Duschek, Lennart; Belz, Jürgen; Beyer, Andreas; Baranovskii, Sergei D.; Volz, Kerstin

    2017-06-15

    Highlights: • We present STEMsalabim, a modern implementation of the multislice algorithm for simulation of STEM images. • Our package is highly parallelizable on high-performance computing clusters, combining shared and distributed memory architectures. • With STEMsalabim, computationally and memory expensive STEM image simulations can be carried out within reasonable time. - Abstract: We present a new multislice code for the computer simulation of scanning transmission electron microscope (STEM) images based on the frozen lattice approximation. Unlike existing software packages, the code is optimized to perform well on highly parallelized computing clusters, combining distributed and shared memory architectures. This enables efficient calculation of large lateral scanning areas of the specimen within the frozen lattice approximation and fine-grained sweeps of parameter space.

  6. Intelligent distributed computing

    CERN Document Server

    Thampi, Sabu

    2015-01-01

    This book contains a selection of refereed and revised papers of the Intelligent Distributed Computing Track originally presented at the third International Symposium on Intelligent Informatics (ISI-2014), September 24-27, 2014, Delhi, India.  The papers selected for this Track cover several Distributed Computing and related topics including Peer-to-Peer Networks, Cloud Computing, Mobile Clouds, Wireless Sensor Networks, and their applications.

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

    CERN Document Server

    Hori, Muneo; Ohsaki, Makoto

    2016-01-01

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

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

    CERN Document Server

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

    2015-01-01

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

  9. A parallel calibration utility for WRF-Hydro on high performance computers

    Science.gov (United States)

    Wang, J.; Wang, C.; Kotamarthi, V. R.

    2017-12-01

    A successful modeling of complex hydrological processes comprises establishing an integrated hydrological model which simulates the hydrological processes in each water regime, calibrates and validates the model performance based on observation data, and estimates the uncertainties from different sources especially those associated with parameters. Such a model system requires large computing resources and often have to be run on High Performance Computers (HPC). The recently developed WRF-Hydro modeling system provides a significant advancement in the capability to simulate regional water cycles more completely. The WRF-Hydro model has a large range of parameters such as those in the input table files — GENPARM.TBL, SOILPARM.TBL and CHANPARM.TBL — and several distributed scaling factors such as OVROUGHRTFAC. These parameters affect the behavior and outputs of the model and thus may need to be calibrated against the observations in order to obtain a good modeling performance. Having a parameter calibration tool specifically for automate calibration and uncertainty estimates of WRF-Hydro model can provide significant convenience for the modeling community. In this study, we developed a customized tool using the parallel version of the model-independent parameter estimation and uncertainty analysis tool, PEST, to enabled it to run on HPC with PBS and SLURM workload manager and job scheduler. We also developed a series of PEST input file templates that are specifically for WRF-Hydro model calibration and uncertainty analysis. Here we will present a flood case study occurred in April 2013 over Midwest. The sensitivity and uncertainties are analyzed using the customized PEST tool we developed.

  10. High performance computing and communications: Advancing the frontiers of information technology

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-12-31

    This report, which supplements the President`s Fiscal Year 1997 Budget, describes the interagency High Performance Computing and Communications (HPCC) Program. The HPCC Program will celebrate its fifth anniversary in October 1996 with an impressive array of accomplishments to its credit. Over its five-year history, the HPCC Program has focused on developing high performance computing and communications technologies that can be applied to computation-intensive applications. Major highlights for FY 1996: (1) High performance computing systems enable practical solutions to complex problems with accuracies not possible five years ago; (2) HPCC-funded research in very large scale networking techniques has been instrumental in the evolution of the Internet, which continues exponential growth in size, speed, and availability of information; (3) The combination of hardware capability measured in gigaflop/s, networking technology measured in gigabit/s, and new computational science techniques for modeling phenomena has demonstrated that very large scale accurate scientific calculations can be executed across heterogeneous parallel processing systems located thousands of miles apart; (4) Federal investments in HPCC software R and D support researchers who pioneered the development of parallel languages and compilers, high performance mathematical, engineering, and scientific libraries, and software tools--technologies that allow scientists to use powerful parallel systems to focus on Federal agency mission applications; and (5) HPCC support for virtual environments has enabled the development of immersive technologies, where researchers can explore and manipulate multi-dimensional scientific and engineering problems. Educational programs fostered by the HPCC Program have brought into classrooms new science and engineering curricula designed to teach computational science. This document contains a small sample of the significant HPCC Program accomplishments in FY 1996.

  11. High performance computing system in the framework of the Higgs boson studies

    CERN Document Server

    Belyaev, Nikita; The ATLAS collaboration

    2017-01-01

    The Higgs boson physics is one of the most important and promising fields of study in modern High Energy Physics. To perform precision measurements of the Higgs boson properties, the use of fast and efficient instruments of Monte Carlo event simulation is required. Due to the increasing amount of data and to the growing complexity of the simulation software tools, the computing resources currently available for Monte Carlo simulation on the LHC GRID are not sufficient. One of the possibilities to address this shortfall of computing resources is the usage of institutes computer clusters, commercial computing resources and supercomputers. In this paper, a brief description of the Higgs boson physics, the Monte-Carlo generation and event simulation techniques are presented. A description of modern high performance computing systems and tests of their performance are also discussed. These studies have been performed on the Worldwide LHC Computing Grid and Kurchatov Institute Data Processing Center, including Tier...

  12. Visualization of Distributed Data Structures for High Performance Fortran-Like Languages

    Directory of Open Access Journals (Sweden)

    Rainer Koppler

    1997-01-01

    Full Text Available This article motivates the usage of graphics and visualization for efficient utilization of High Performance Fortran's (HPF's data distribution facilities. It proposes a graphical toolkit consisting of exploratory and estimation tools which allow the programmer to navigate through complex distributions and to obtain graphical ratings with respect to load distribution and communication. The toolkit has been implemented in a mapping design and visualization tool which is coupled with a compilation system for the HPF predecessor Vienna Fortran. Since this language covers a superset of HPF's facilities, the tool may also be used for visualization of HPF data structures.

  13. Topic 14+16: High-performance and scientific applications and extreme-scale computing (Introduction)

    KAUST Repository

    Downes, Turlough P.

    2013-01-01

    As our understanding of the world around us increases it becomes more challenging to make use of what we already know, and to increase our understanding still further. Computational modeling and simulation have become critical tools in addressing this challenge. The requirements of high-resolution, accurate modeling have outstripped the ability of desktop computers and even small clusters to provide the necessary compute power. Many applications in the scientific and engineering domains now need very large amounts of compute time, while other applications, particularly in the life sciences, frequently have large data I/O requirements. There is thus a growing need for a range of high performance applications which can utilize parallel compute systems effectively, which have efficient data handling strategies and which have the capacity to utilise current and future systems. The High Performance and Scientific Applications topic aims to highlight recent progress in the use of advanced computing and algorithms to address the varied, complex and increasing challenges of modern research throughout both the "hard" and "soft" sciences. This necessitates being able to use large numbers of compute nodes, many of which are equipped with accelerators, and to deal with difficult I/O requirements. © 2013 Springer-Verlag.

  14. Thinking processes used by high-performing students in a computer programming task

    Directory of Open Access Journals (Sweden)

    Marietjie Havenga

    2011-07-01

    Full Text Available Computer programmers must be able to understand programming source code and write programs that execute complex tasks to solve real-world problems. This article is a trans- disciplinary study at the intersection of computer programming, education and psychology. It outlines the role of mental processes in the process of programming and indicates how successful thinking processes can support computer science students in writing correct and well-defined programs. A mixed methods approach was used to better understand the thinking activities and programming processes of participating students. Data collection involved both computer programs and students’ reflective thinking processes recorded in their journals. This enabled analysis of psychological dimensions of participants’ thinking processes and their problem-solving activities as they considered a programming problem. Findings indicate that the cognitive, reflective and psychological processes used by high-performing programmers contributed to their success in solving a complex programming problem. Based on the thinking processes of high performers, we propose a model of integrated thinking processes, which can support computer programming students. Keywords: Computer programming, education, mixed methods research, thinking processes.  Disciplines: Computer programming, education, psychology

  15. 10th International Workshop on Parallel Tools for High Performance Computing

    CERN Document Server

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

    2017-01-01

    This book presents the proceedings of the 10th International Parallel Tools Workshop, held October 4-5, 2016 in Stuttgart, Germany – a forum to discuss the latest advances in parallel tools. High-performance computing plays an increasingly important role for numerical simulation and modelling in academic and industrial research. At the same time, using large-scale parallel systems efficiently is becoming more difficult. A number of tools addressing parallel program development and analysis have emerged from the high-performance computing community over the last decade, and what may have started as collection of small helper script has now matured to production-grade frameworks. Powerful user interfaces and an extensive body of documentation allow easy usage by non-specialists.

  16. International Conference on Modern Mathematical Methods and High Performance Computing in Science and Technology

    CERN Document Server

    Srivastava, HM; Venturino, Ezio; Resch, Michael; Gupta, Vijay

    2016-01-01

    The book discusses important results in modern mathematical models and high performance computing, such as applied operations research, simulation of operations, statistical modeling and applications, invisibility regions and regular meta-materials, unmanned vehicles, modern radar techniques/SAR imaging, satellite remote sensing, coding, and robotic systems. Furthermore, it is valuable as a reference work and as a basis for further study and research. All contributing authors are respected academicians, scientists and researchers from around the globe. All the papers were presented at the international conference on Modern Mathematical Methods and High Performance Computing in Science & Technology (M3HPCST 2015), held at Raj Kumar Goel Institute of Technology, Ghaziabad, India, from 27–29 December 2015, and peer-reviewed by international experts. The conference provided an exceptional platform for leading researchers, academicians, developers, engineers and technocrats from a broad range of disciplines ...

  17. Distributed computing at the SSCL

    International Nuclear Information System (INIS)

    Cormell, L.; White, R.

    1993-05-01

    The rapid increase in the availability of high performance, cost- effective RISC/UNIX workstations has been both a blessing and a curse. The blessing of having extremely powerful computing engines available on the desk top is well-known to many users. The user has tremendous freedom, flexibility, and control of his environment. That freedom can, however, become the curse of distributed computing. The user must become a system manager to some extent, he must worry about backups, maintenance, upgrades, etc. Traditionally these activities have been the responsibility of a central computing group. The central computing group, however, may find that it can no linger provide all of the traditional services. With the plethora of workstations now found on so many desktops throughout the entire campus or lab, the central computing group may be swamped by support requests. This talk will address several of these computer support and management issues by discussing the approach taken at the Superconducting Super Collider Laboratory. In addition, a brief review of the future directions of commercial products for distributed computing and management will be given

  18. Distributed computing at the SSCL

    International Nuclear Information System (INIS)

    Cormell, L.R.; White, R.C.

    1994-01-01

    The rapid increase in the availability of high performance, cost-effective RISC/UNIX workstations has been both a blessing and a curse. The blessing of having extremely powerful computing engines available on the desk top is well-known to many users. The user has tremendous freedom, flexibility, and control of his environment. That freedom can, however, become the curse of distributed computing. The user must become a system manager to some extent, he must worry about backups, maintenance, upgrades, etc. Traditionally these activities have been the responsibility of central computing group. The central computing group, however, may find that it can no longer provide all of the traditional services. With the plethora of workstations now found on so many desktops throughout the entire campus or lab, the central computing group may be swamped by support requests. This talk will address several of these computer support and management issues by discussing the approach taken at the Superconducting Super Collider Laboratory (SSCL). In addition, a brief review of the future directions of commercial products for distributed computing and management will be given

  19. Solving Problems in Various Domains by Hybrid Models of High Performance Computations

    Directory of Open Access Journals (Sweden)

    Yurii Rogozhin

    2014-03-01

    Full Text Available This work presents a hybrid model of high performance computations. The model is based on membrane system (P~system where some membranes may contain quantum device that is triggered by the data entering the membrane. This model is supposed to take advantages of both biomolecular and quantum paradigms and to overcome some of their inherent limitations. The proposed approach is demonstrated through two selected problems: SAT, and image retrieving.

  20. High-performance computing on the Intel Xeon Phi how to fully exploit MIC architectures

    CERN Document Server

    Wang, Endong; Shen, Bo; Zhang, Guangyong; Lu, Xiaowei; Wu, Qing; Wang, Yajuan

    2014-01-01

    The aim of this book is to explain to high-performance computing (HPC) developers how to utilize the Intel® Xeon Phi™ series products efficiently. To that end, it introduces some computing grammar, programming technology and optimization methods for using many-integrated-core (MIC) platforms and also offers tips and tricks for actual use, based on the authors' first-hand optimization experience.The material is organized in three sections. The first section, "Basics of MIC", introduces the fundamentals of MIC architecture and programming, including the specific Intel MIC programming environment

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-09-01

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

  2. High Performance Computing - Power Application Programming Interface Specification Version 2.0.

    Energy Technology Data Exchange (ETDEWEB)

    Laros, James H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grant, Ryan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Levenhagen, Michael J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Olivier, Stephen Lecler [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pedretti, Kevin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ward, H. Lee [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Younge, Andrew J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-03-01

    Measuring and controlling the power and energy consumption of high performance computing systems by various components in the software stack is an active research area. Implementations in lower level software layers are beginning to emerge in some production systems, which is very welcome. To be most effective, a portable interface to measurement and control features would significantly facilitate participation by all levels of the software stack. We present a proposal for a standard power Application Programming Interface (API) that endeavors to cover the entire software space, from generic hardware interfaces to the input from the computer facility manager.

  3. Cloud object store for archive storage of high performance computing data using decoupling middleware

    Science.gov (United States)

    Bent, John M.; Faibish, Sorin; Grider, Gary

    2015-06-30

    Cloud object storage is enabled for archived data, such as checkpoints and results, of high performance computing applications using a middleware process. A plurality of archived files, such as checkpoint files and results, generated by a plurality of processes in a parallel computing system are stored by obtaining the plurality of archived files from the parallel computing system; converting the plurality of archived files to objects using a log structured file system middleware process; and providing the objects for storage in a cloud object storage system. The plurality of processes may run, for example, on a plurality of compute nodes. The log structured file system middleware process may be embodied, for example, as a Parallel Log-Structured File System (PLFS). The log structured file system middleware process optionally executes on a burst buffer node.

  4. Cloud object store for checkpoints of high performance computing applications using decoupling middleware

    Science.gov (United States)

    Bent, John M.; Faibish, Sorin; Grider, Gary

    2016-04-19

    Cloud object storage is enabled for checkpoints of high performance computing applications using a middleware process. A plurality of files, such as checkpoint files, generated by a plurality of processes in a parallel computing system are stored by obtaining said plurality of files from said parallel computing system; converting said plurality of files to objects using a log structured file system middleware process; and providing said objects for storage in a cloud object storage system. The plurality of processes may run, for example, on a plurality of compute nodes. The log structured file system middleware process may be embodied, for example, as a Parallel Log-Structured File System (PLFS). The log structured file system middleware process optionally executes on a burst buffer node.

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

    Science.gov (United States)

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

    2013-01-28

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

  6. ATLAS Distributed Computing Automation

    CERN Document Server

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

    2012-01-01

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

  7. On the impact of quantum computing technology on future developments in high-performance scientific computing

    OpenAIRE

    Möller, Matthias; Vuik, Cornelis

    2017-01-01

    Quantum computing technologies have become a hot topic in academia and industry receiving much attention and financial support from all sides. Building a quantum computer that can be used practically is in itself an outstanding challenge that has become the ‘new race to the moon’. Next to researchers and vendors of future computing technologies, national authorities are showing strong interest in maturing this technology due to its known potential to break many of today’s encryption technique...

  8. Can We Build a Truly High Performance Computer Which is Flexible and Transparent?

    KAUST Repository

    Rojas, Jhonathan Prieto

    2013-09-10

    State-of-the art computers need high performance transistors, which consume ultra-low power resulting in longer battery lifetime. Billions of transistors are integrated neatly using matured silicon fabrication process to maintain the performance per cost advantage. In that context, low-cost mono-crystalline bulk silicon (100) based high performance transistors are considered as the heart of today\\'s computers. One limitation is silicon\\'s rigidity and brittleness. Here we show a generic batch process to convert high performance silicon electronics into flexible and semi-transparent one while retaining its performance, process compatibility, integration density and cost. We demonstrate high-k/metal gate stack based p-type metal oxide semiconductor field effect transistors on 4 inch silicon fabric released from bulk silicon (100) wafers with sub-threshold swing of 80 mV dec(-1) and on/off ratio of near 10(4) within 10% device uniformity with a minimum bending radius of 5 mm and an average transmittance of similar to 7% in the visible spectrum.

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

    Directory of Open Access Journals (Sweden)

    Anwar S. Shatil

    2015-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  12. Bringing high-performance computing to the biologist's workbench: approaches, applications, and challenges

    International Nuclear Information System (INIS)

    Oehmen, C S; Cannon, W R

    2008-01-01

    Data-intensive and high-performance computing are poised to significantly impact the future of biological research which is increasingly driven by the prevalence of high-throughput experimental methodologies for genome sequencing, transcriptomics, proteomics, and other areas. Large centers such as NIH's National Center for Biotechnology Information, The Institute for Genomic Research, and the DOE's Joint Genome Institute) have made extensive use of multiprocessor architectures to deal with some of the challenges of processing, storing and curating exponentially growing genomic and proteomic datasets, thus enabling users to rapidly access a growing public data source, as well as use analysis tools transparently on high-performance computing resources. Applying this computational power to single-investigator analysis, however, often relies on users to provide their own computational resources, forcing them to endure the learning curve of porting, building, and running software on multiprocessor architectures. Solving the next generation of large-scale biology challenges using multiprocessor machines-from small clusters to emerging petascale machines-can most practically be realized if this learning curve can be minimized through a combination of workflow management, data management and resource allocation as well as intuitive interfaces and compatibility with existing common data formats

  13. On the impact of quantum computing technology on future developments in high-performance scientific computing

    NARCIS (Netherlands)

    Möller, M.; Vuik, C.

    2017-01-01

    Quantum computing technologies have become a hot topic in academia and industry receiving much attention and financial support from all sides. Building a quantum computer that can be used practically is in itself an outstanding challenge that has become the ‘new race to the moon’. Next to

  14. A comprehensive approach to decipher biological computation to achieve next generation high-performance exascale computing.

    Energy Technology Data Exchange (ETDEWEB)

    James, Conrad D.; Schiess, Adrian B.; Howell, Jamie; Baca, Michael J.; Partridge, L. Donald; Finnegan, Patrick Sean; Wolfley, Steven L.; Dagel, Daryl James; Spahn, Olga Blum; Harper, Jason C.; Pohl, Kenneth Roy; Mickel, Patrick R.; Lohn, Andrew; Marinella, Matthew

    2013-10-01

    The human brain (volume=1200cm3) consumes 20W and is capable of performing > 10^16 operations/s. Current supercomputer technology has reached 1015 operations/s, yet it requires 1500m^3 and 3MW, giving the brain a 10^12 advantage in operations/s/W/cm^3. Thus, to reach exascale computation, two achievements are required: 1) improved understanding of computation in biological tissue, and 2) a paradigm shift towards neuromorphic computing where hardware circuits mimic properties of neural tissue. To address 1), we will interrogate corticostriatal networks in mouse brain tissue slices, specifically with regard to their frequency filtering capabilities as a function of input stimulus. To address 2), we will instantiate biological computing characteristics such as multi-bit storage into hardware devices with future computational and memory applications. Resistive memory devices will be modeled, designed, and fabricated in the MESA facility in consultation with our internal and external collaborators.

  15. DOE High Performance Computing Operational Review (HPCOR): Enabling Data-Driven Scientific Discovery at HPC Facilities

    Energy Technology Data Exchange (ETDEWEB)

    Gerber, Richard; Allcock, William; Beggio, Chris; Campbell, Stuart; Cherry, Andrew; Cholia, Shreyas; Dart, Eli; England, Clay; Fahey, Tim; Foertter, Fernanda; Goldstone, Robin; Hick, Jason; Karelitz, David; Kelly, Kaki; Monroe, Laura; Prabhat,; Skinner, David; White, Julia

    2014-10-17

    U.S. Department of Energy (DOE) High Performance Computing (HPC) facilities are on the verge of a paradigm shift in the way they deliver systems and services to science and engineering teams. Research projects are producing a wide variety of data at unprecedented scale and level of complexity, with community-specific services that are part of the data collection and analysis workflow. On June 18-19, 2014 representatives from six DOE HPC centers met in Oakland, CA at the DOE High Performance Operational Review (HPCOR) to discuss how they can best provide facilities and services to enable large-scale data-driven scientific discovery at the DOE national laboratories. The report contains findings from that review.

  16. Integrated State Estimation and Contingency Analysis Software Implementation using High Performance Computing Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Yousu; Glaesemann, Kurt R.; Rice, Mark J.; Huang, Zhenyu

    2015-12-31

    Power system simulation tools are traditionally developed in sequential mode and codes are optimized for single core computing only. However, the increasing complexity in the power grid models requires more intensive computation. The traditional simulation tools will soon not be able to meet the grid operation requirements. Therefore, power system simulation tools need to evolve accordingly to provide faster and better results for grid operations. This paper presents an integrated state estimation and contingency analysis software implementation using high performance computing techniques. The software is able to solve large size state estimation problems within one second and achieve a near-linear speedup of 9,800 with 10,000 cores for contingency analysis application. The performance evaluation is presented to show its effectiveness.

  17. SCEAPI: A unified Restful Web API for High-Performance Computing

    Science.gov (United States)

    Rongqiang, Cao; Haili, Xiao; Shasha, Lu; Yining, Zhao; Xiaoning, Wang; Xuebin, Chi

    2017-10-01

    The development of scientific computing is increasingly moving to collaborative web and mobile applications. All these applications need high-quality programming interface for accessing heterogeneous computing resources consisting of clusters, grid computing or cloud computing. In this paper, we introduce our high-performance computing environment that integrates computing resources from 16 HPC centers across China. Then we present a bundle of web services called SCEAPI and describe how it can be used to access HPC resources with HTTP or HTTPs protocols. We discuss SCEAPI from several aspects including architecture, implementation and security, and address specific challenges in designing compatible interfaces and protecting sensitive data. We describe the functions of SCEAPI including authentication, file transfer and job management for creating, submitting and monitoring, and how to use SCEAPI in an easy-to-use way. Finally, we discuss how to exploit more HPC resources quickly for the ATLAS experiment by implementing the custom ARC compute element based on SCEAPI, and our work shows that SCEAPI is an easy-to-use and effective solution to extend opportunistic HPC resources.

  18. Soft Computing Techniques for the Protein Folding Problem on High Performance Computing Architectures.

    Science.gov (United States)

    Llanes, Antonio; Muñoz, Andrés; Bueno-Crespo, Andrés; García-Valverde, Teresa; Sánchez, Antonia; Arcas-Túnez, Francisco; Pérez-Sánchez, Horacio; Cecilia, José M

    2016-01-01

    The protein-folding problem has been extensively studied during the last fifty years. The understanding of the dynamics of global shape of a protein and the influence on its biological function can help us to discover new and more effective drugs to deal with diseases of pharmacological relevance. Different computational approaches have been developed by different researchers in order to foresee the threedimensional arrangement of atoms of proteins from their sequences. However, the computational complexity of this problem makes mandatory the search for new models, novel algorithmic strategies and hardware platforms that provide solutions in a reasonable time frame. We present in this revision work the past and last tendencies regarding protein folding simulations from both perspectives; hardware and software. Of particular interest to us are both the use of inexact solutions to this computationally hard problem as well as which hardware platforms have been used for running this kind of Soft Computing techniques.

  19. Kemari: A Portable High Performance Fortran System for Distributed Memory Parallel Processors

    Directory of Open Access Journals (Sweden)

    T. Kamachi

    1997-01-01

    Full Text Available We have developed a compilation system which extends High Performance Fortran (HPF in various aspects. We support the parallelization of well-structured problems with loop distribution and alignment directives similar to HPF's data distribution directives. Such directives give both additional control to the user and simplify the compilation process. For the support of unstructured problems, we provide directives for dynamic data distribution through user-defined mappings. The compiler also allows integration of message-passing interface (MPI primitives. The system is part of a complete programming environment which also comprises a parallel debugger and a performance monitor and analyzer. After an overview of the compiler, we describe the language extensions and related compilation mechanisms in detail. Performance measurements demonstrate the compiler's applicability to a variety of application classes.

  20. ATLAS Distributed Computing

    CERN Document Server

    Schovancova, J; The ATLAS collaboration

    2011-01-01

    The poster details the different aspects of the ATLAS Distributed Computing experience after the first year of LHC data taking. We describe the performance of the ATLAS distributed computing system and the lessons learned during the 2010 run, pointing out parts of the system which were in a good shape, and also spotting areas which required improvements. Improvements ranged from hardware upgrade on the ATLAS Tier-0 computing pools to improve data distribution rates, tuning of FTS channels between CERN and Tier-1s, and studying data access patterns for Grid analysis to improve the global processing rate. We show recent software development driven by operational needs with emphasis on data management and job execution in the ATLAS production system.

  1. HIGH-PERFORMANCE COMPUTING FOR THE STUDY OF EARTH AND ENVIRONMENTAL SCIENCE MATERIALS USING SYNCHROTRON X-RAY COMPUTED MICROTOMOGRAPHY

    International Nuclear Information System (INIS)

    FENG, H.; JONES, K.W.; MCGUIGAN, M.; SMITH, G.J.; SPILETIC, J.

    2001-01-01

    Synchrotron x-ray computed microtomography (CMT) is a non-destructive method for examination of rock, soil, and other types of samples studied in the earth and environmental sciences. The high x-ray intensities of the synchrotron source make possible the acquisition of tomographic volumes at a high rate that requires the application of high-performance computing techniques for data reconstruction to produce the three-dimensional volumes, for their visualization, and for data analysis. These problems are exacerbated by the need to share information between collaborators at widely separated locations over both local and tide-area networks. A summary of the CMT technique and examples of applications are given here together with a discussion of the applications of high-performance computing methods to improve the experimental techniques and analysis of the data

  2. HIGH-PERFORMANCE COMPUTING FOR THE STUDY OF EARTH AND ENVIRONMENTAL SCIENCE MATERIALS USING SYNCHROTRON X-RAY COMPUTED MICROTOMOGRAPHY.

    Energy Technology Data Exchange (ETDEWEB)

    FENG,H.; JONES,K.W.; MCGUIGAN,M.; SMITH,G.J.; SPILETIC,J.

    2001-10-12

    Synchrotron x-ray computed microtomography (CMT) is a non-destructive method for examination of rock, soil, and other types of samples studied in the earth and environmental sciences. The high x-ray intensities of the synchrotron source make possible the acquisition of tomographic volumes at a high rate that requires the application of high-performance computing techniques for data reconstruction to produce the three-dimensional volumes, for their visualization, and for data analysis. These problems are exacerbated by the need to share information between collaborators at widely separated locations over both local and tide-area networks. A summary of the CMT technique and examples of applications are given here together with a discussion of the applications of high-performance computing methods to improve the experimental techniques and analysis of the data.

  3. High performance simulation for the Silva project using the tera computer

    Energy Technology Data Exchange (ETDEWEB)

    Bergeaud, V.; La Hargue, J.P.; Mougery, F. [CS Communication and Systemes, 92 - Clamart (France); Boulet, M.; Scheurer, B. [CEA Bruyeres-le-Chatel, 91 - Bruyeres-le-Chatel (France); Le Fur, J.F.; Comte, M.; Benisti, D.; Lamare, J. de; Petit, A. [CEA Saclay, 91 - Gif sur Yvette (France)

    2003-07-01

    In the context of the SILVA Project (Atomic Vapor Laser Isotope Separation), numerical simulation of the plant scale propagation of laser beams through uranium vapour was a great challenge. The PRODIGE code has been developed to achieve this goal. Here we focus on the task of achieving high performance simulation on the TERA computer. We describe the main issues for optimizing the parallelization of the PRODIGE code on TERA. Thus, we discuss advantages and drawbacks of the implemented diagonal parallelization scheme. As a consequence, it has been found fruitful to fit out the code in three aspects: memory allocation, MPI communications and interconnection network bandwidth usage. We stress out the interest of MPI/IO in this context and the benefit obtained for production computations on TERA. Finally, we shall illustrate our developments. We indicate some performance measurements reflecting the good parallelization properties of PRODIGE on the TERA computer. The code is currently used for demonstrating the feasibility of the laser propagation at a plant enrichment level and for preparing the 2003 Menphis experiment. We conclude by emphasizing the contribution of high performance TERA simulation to the project. (authors)

  4. High performance simulation for the Silva project using the tera computer

    International Nuclear Information System (INIS)

    Bergeaud, V.; La Hargue, J.P.; Mougery, F.; Boulet, M.; Scheurer, B.; Le Fur, J.F.; Comte, M.; Benisti, D.; Lamare, J. de; Petit, A.

    2003-01-01

    In the context of the SILVA Project (Atomic Vapor Laser Isotope Separation), numerical simulation of the plant scale propagation of laser beams through uranium vapour was a great challenge. The PRODIGE code has been developed to achieve this goal. Here we focus on the task of achieving high performance simulation on the TERA computer. We describe the main issues for optimizing the parallelization of the PRODIGE code on TERA. Thus, we discuss advantages and drawbacks of the implemented diagonal parallelization scheme. As a consequence, it has been found fruitful to fit out the code in three aspects: memory allocation, MPI communications and interconnection network bandwidth usage. We stress out the interest of MPI/IO in this context and the benefit obtained for production computations on TERA. Finally, we shall illustrate our developments. We indicate some performance measurements reflecting the good parallelization properties of PRODIGE on the TERA computer. The code is currently used for demonstrating the feasibility of the laser propagation at a plant enrichment level and for preparing the 2003 Menphis experiment. We conclude by emphasizing the contribution of high performance TERA simulation to the project. (authors)

  5. High Performance Computing and Storage Requirements for Nuclear Physics: Target 2017

    Energy Technology Data Exchange (ETDEWEB)

    Gerber, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wasserman, Harvey [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2014-04-30

    In April 2014, NERSC, ASCR, and the DOE Office of Nuclear Physics (NP) held a review to characterize high performance computing (HPC) and storage requirements for NP research through 2017. This review is the 12th in a series of reviews held by NERSC and Office of Science program offices that began in 2009. It is the second for NP, and the final in the second round of reviews that covered the six Office of Science program offices. This report is the result of that review

  6. Commercialization issues and funding opportunities for high-performance optoelectronic computing modules

    Science.gov (United States)

    Hessenbruch, John M.; Guilfoyle, Peter S.

    1997-01-01

    Low power, optoelectronic integrated circuits are being developed for high speed switching and data processing applications. These high performance optoelectronic computing modules consist of three primary components: vertical cavity surface emitting lasers, diffractive optical interconnect elements, and detector/amplifier/laser driver arrays. Following the design and fabrication of an HPOC module prototype, selected commercial funding sources will be evaluated to support a product development stage. These include the formation of a strategic alliance with one or more microprocessor or telecommunications vendors, and/or equity investment from one or more venture capital firms.

  7. Failure detection in high-performance clusters and computers using chaotic map computations

    Science.gov (United States)

    Rao, Nageswara S.

    2015-09-01

    A programmable media includes a processing unit capable of independent operation in a machine that is capable of executing 10.sup.18 floating point operations per second. The processing unit is in communication with a memory element and an interconnect that couples computing nodes. The programmable media includes a logical unit configured to execute arithmetic functions, comparative functions, and/or logical functions. The processing unit is configured to detect computing component failures, memory element failures and/or interconnect failures by executing programming threads that generate one or more chaotic map trajectories. The central processing unit or graphical processing unit is configured to detect a computing component failure, memory element failure and/or an interconnect failure through an automated comparison of signal trajectories generated by the chaotic maps.

  8. Computer-Aided Design of Drugs on Emerging Hybrid High Performance Computers

    Science.gov (United States)

    2013-09-01

    8.00 Obaidur Rahaman, Trilce P. Estrada, Douglas J. Doren, Michela Taufer, Charles L. Brooks, Roger S. Armen . Evaluation of Several Two-Step Scoring...Parallel and Distributed Processing Symposium (IPDPS), . 2011/04/18 00:00:00, . : , 08/15/2011 9.00 T. Estrada, R. Armen , M. Taufer. Automatic Selection

  9. Challenges and opportunities of modeling plasma–surface interactions in tungsten using high-performance computing

    Energy Technology Data Exchange (ETDEWEB)

    Wirth, Brian D., E-mail: bdwirth@utk.edu [Department of Nuclear Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Nuclear Science and Engineering Directorate, Oak Ridge National Laboratory, Oak Ridge, TN (United States); Hammond, K.D. [Department of Nuclear Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Krasheninnikov, S.I. [University of California, San Diego, La Jolla, CA (United States); Maroudas, D. [University of Massachusetts, Amherst, Amherst, MA 01003 (United States)

    2015-08-15

    The performance of plasma facing components (PFCs) is critical for ITER and future magnetic fusion reactors. The ITER divertor will be tungsten, which is the primary candidate material for future reactors. Recent experiments involving tungsten exposure to low-energy helium plasmas reveal significant surface modification, including the growth of nanometer-scale tendrils of “fuzz” and formation of nanometer-sized bubbles in the near-surface region. The large span of spatial and temporal scales governing plasma surface interactions are among the challenges to modeling divertor performance. Fortunately, recent innovations in computational modeling, increasingly powerful high-performance computers, and improved experimental characterization tools provide a path toward self-consistent, experimentally validated models of PFC and divertor performance. Recent advances in understanding tungsten–helium interactions are reviewed, including such processes as helium clustering, which serve as nuclei for gas bubbles; and trap mutation, dislocation loop punching and bubble bursting; which together initiate surface morphological modification.

  10. High Performance Computing - Power Application Programming Interface Specification Version 1.4

    Energy Technology Data Exchange (ETDEWEB)

    Laros III, James H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); DeBonis, David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grant, Ryan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kelly, Suzanne M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Levenhagen, Michael J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Olivier, Stephen Lecler [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pedretti, Kevin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-10-01

    Measuring and controlling the power and energy consumption of high performance computing systems by various components in the software stack is an active research area [13, 3, 5, 10, 4, 21, 19, 16, 7, 17, 20, 18, 11, 1, 6, 14, 12]. Implementations in lower level software layers are beginning to emerge in some production systems, which is very welcome. To be most effective, a portable interface to measurement and control features would significantly facilitate participation by all levels of the software stack. We present a proposal for a standard power Application Programming Interface (API) that endeavors to cover the entire software space, from generic hardware interfaces to the input from the computer facility manager.

  11. Polymer waveguides for electro-optical integration in data centers and high-performance computers.

    Science.gov (United States)

    Dangel, Roger; Hofrichter, Jens; Horst, Folkert; Jubin, Daniel; La Porta, Antonio; Meier, Norbert; Soganci, Ibrahim Murat; Weiss, Jonas; Offrein, Bert Jan

    2015-02-23

    To satisfy the intra- and inter-system bandwidth requirements of future data centers and high-performance computers, low-cost low-power high-throughput optical interconnects will become a key enabling technology. To tightly integrate optics with the computing hardware, particularly in the context of CMOS-compatible silicon photonics, optical printed circuit boards using polymer waveguides are considered as a formidable platform. IBM Research has already demonstrated the essential silicon photonics and interconnection building blocks. A remaining challenge is electro-optical packaging, i.e., the connection of the silicon photonics chips with the system. In this paper, we present a new single-mode polymer waveguide technology and a scalable method for building the optical interface between silicon photonics chips and single-mode polymer waveguides.

  12. Parallel Backprojection: A Case Study in High-Performance Reconfigurable Computing

    Directory of Open Access Journals (Sweden)

    Cordes Ben

    2009-01-01

    Full Text Available High-performance reconfigurable computing (HPRC is a novel approach to provide large-scale computing power to modern scientific applications. Using both general-purpose processors and FPGAs allows application designers to exploit fine-grained and coarse-grained parallelism, achieving high degrees of speedup. One scientific application that benefits from this technique is backprojection, an image formation algorithm that can be used as part of a synthetic aperture radar (SAR processing system. We present an implementation of backprojection for SAR on an HPRC system. Using simulated data taken at a variety of ranges, our implementation runs over 200 times faster than a similar software program, with an overall application speedup better than 50x. The backprojection application is easily parallelizable, achieving near-linear speedup when run on multiple nodes of a clustered HPRC system. The results presented can be applied to other systems and other algorithms with similar characteristics.

  13. Parallel Backprojection: A Case Study in High-Performance Reconfigurable Computing

    Directory of Open Access Journals (Sweden)

    2009-03-01

    Full Text Available High-performance reconfigurable computing (HPRC is a novel approach to provide large-scale computing power to modern scientific applications. Using both general-purpose processors and FPGAs allows application designers to exploit fine-grained and coarse-grained parallelism, achieving high degrees of speedup. One scientific application that benefits from this technique is backprojection, an image formation algorithm that can be used as part of a synthetic aperture radar (SAR processing system. We present an implementation of backprojection for SAR on an HPRC system. Using simulated data taken at a variety of ranges, our implementation runs over 200 times faster than a similar software program, with an overall application speedup better than 50x. The backprojection application is easily parallelizable, achieving near-linear speedup when run on multiple nodes of a clustered HPRC system. The results presented can be applied to other systems and other algorithms with similar characteristics.

  14. Challenges and opportunities of modeling plasma–surface interactions in tungsten using high-performance computing

    International Nuclear Information System (INIS)

    Wirth, Brian D.; Hammond, K.D.; Krasheninnikov, S.I.; Maroudas, D.

    2015-01-01

    The performance of plasma facing components (PFCs) is critical for ITER and future magnetic fusion reactors. The ITER divertor will be tungsten, which is the primary candidate material for future reactors. Recent experiments involving tungsten exposure to low-energy helium plasmas reveal significant surface modification, including the growth of nanometer-scale tendrils of “fuzz” and formation of nanometer-sized bubbles in the near-surface region. The large span of spatial and temporal scales governing plasma surface interactions are among the challenges to modeling divertor performance. Fortunately, recent innovations in computational modeling, increasingly powerful high-performance computers, and improved experimental characterization tools provide a path toward self-consistent, experimentally validated models of PFC and divertor performance. Recent advances in understanding tungsten–helium interactions are reviewed, including such processes as helium clustering, which serve as nuclei for gas bubbles; and trap mutation, dislocation loop punching and bubble bursting; which together initiate surface morphological modification

  15. 9th International Workshop on Parallel Tools for High Performance Computing

    CERN Document Server

    Hilbrich, Tobias; Niethammer, Christoph; Gracia, José; Nagel, Wolfgang; Resch, Michael

    2016-01-01

    High Performance Computing (HPC) remains a driver that offers huge potentials and benefits for science and society. However, a profound understanding of the computational matters and specialized software is needed to arrive at effective and efficient simulations. Dedicated software tools are important parts of the HPC software landscape, and support application developers. Even though a tool is by definition not a part of an application, but rather a supplemental piece of software, it can make a fundamental difference during the development of an application. Such tools aid application developers in the context of debugging, performance analysis, and code optimization, and therefore make a major contribution to the development of robust and efficient parallel software. This book introduces a selection of the tools presented and discussed at the 9th International Parallel Tools Workshop held in Dresden, Germany, September 2-3, 2015, which offered an established forum for discussing the latest advances in paral...

  16. DIRAC distributed computing services

    International Nuclear Information System (INIS)

    Tsaregorodtsev, A

    2014-01-01

    DIRAC Project provides a general-purpose framework for building distributed computing systems. It is used now in several HEP and astrophysics experiments as well as for user communities in other scientific domains. There is a large interest from smaller user communities to have a simple tool like DIRAC for accessing grid and other types of distributed computing resources. However, small experiments cannot afford to install and maintain dedicated services. Therefore, several grid infrastructure projects are providing DIRAC services for their respective user communities. These services are used for user tutorials as well as to help porting the applications to the grid for a practical day-to-day work. The services are giving access typically to several grid infrastructures as well as to standalone computing clusters accessible by the target user communities. In the paper we will present the experience of running DIRAC services provided by the France-Grilles NGI and other national grid infrastructure projects.

  17. Acceleration of FDTD mode solver by high-performance computing techniques.

    Science.gov (United States)

    Han, Lin; Xi, Yanping; Huang, Wei-Ping

    2010-06-21

    A two-dimensional (2D) compact finite-difference time-domain (FDTD) mode solver is developed based on wave equation formalism in combination with the matrix pencil method (MPM). The method is validated for calculation of both real guided and complex leaky modes of typical optical waveguides against the bench-mark finite-difference (FD) eigen mode solver. By taking advantage of the inherent parallel nature of the FDTD algorithm, the mode solver is implemented on graphics processing units (GPUs) using the compute unified device architecture (CUDA). It is demonstrated that the high-performance computing technique leads to significant acceleration of the FDTD mode solver with more than 30 times improvement in computational efficiency in comparison with the conventional FDTD mode solver running on CPU of a standard desktop computer. The computational efficiency of the accelerated FDTD method is in the same order of magnitude of the standard finite-difference eigen mode solver and yet require much less memory (e.g., less than 10%). Therefore, the new method may serve as an efficient, accurate and robust tool for mode calculation of optical waveguides even when the conventional eigen value mode solvers are no longer applicable due to memory limitation.

  18. Human and Robotic Space Mission Use Cases for High-Performance Spaceflight Computing

    Science.gov (United States)

    Some, Raphael; Doyle, Richard; Bergman, Larry; Whitaker, William; Powell, Wesley; Johnson, Michael; Goforth, Montgomery; Lowry, Michael

    2013-01-01

    Spaceflight computing is a key resource in NASA space missions and a core determining factor of spacecraft capability, with ripple effects throughout the spacecraft, end-to-end system, and mission. Onboard computing can be aptly viewed as a "technology multiplier" in that advances provide direct dramatic improvements in flight functions and capabilities across the NASA mission classes, and enable new flight capabilities and mission scenarios, increasing science and exploration return. Space-qualified computing technology, however, has not advanced significantly in well over ten years and the current state of the practice fails to meet the near- to mid-term needs of NASA missions. Recognizing this gap, the NASA Game Changing Development Program (GCDP), under the auspices of the NASA Space Technology Mission Directorate, commissioned a study on space-based computing needs, looking out 15-20 years. The study resulted in a recommendation to pursue high-performance spaceflight computing (HPSC) for next-generation missions, and a decision to partner with the Air Force Research Lab (AFRL) in this development.

  19. The Centre of High-Performance Scientific Computing, Geoverbund, ABC/J - Geosciences enabled by HPSC

    Science.gov (United States)

    Kollet, Stefan; Görgen, Klaus; Vereecken, Harry; Gasper, Fabian; Hendricks-Franssen, Harrie-Jan; Keune, Jessica; Kulkarni, Ketan; Kurtz, Wolfgang; Sharples, Wendy; Shrestha, Prabhakar; Simmer, Clemens; Sulis, Mauro; Vanderborght, Jan

    2016-04-01

    The Centre of High-Performance Scientific Computing (HPSC TerrSys) was founded 2011 to establish a centre of competence in high-performance scientific computing in terrestrial systems and the geosciences enabling fundamental and applied geoscientific research in the Geoverbund ABC/J (geoscientfic research alliance of the Universities of Aachen, Cologne, Bonn and the Research Centre Jülich, Germany). The specific goals of HPSC TerrSys are to achieve relevance at the national and international level in (i) the development and application of HPSC technologies in the geoscientific community; (ii) student education; (iii) HPSC services and support also to the wider geoscientific community; and in (iv) the industry and public sectors via e.g., useful applications and data products. A key feature of HPSC TerrSys is the Simulation Laboratory Terrestrial Systems, which is located at the Jülich Supercomputing Centre (JSC) and provides extensive capabilities with respect to porting, profiling, tuning and performance monitoring of geoscientific software in JSC's supercomputing environment. We will present a summary of success stories of HPSC applications including integrated terrestrial model development, parallel profiling and its application from watersheds to the continent; massively parallel data assimilation using physics-based models and ensemble methods; quasi-operational terrestrial water and energy monitoring; and convection permitting climate simulations over Europe. The success stories stress the need for a formalized education of students in the application of HPSC technologies in future.

  20. High Performance Computing Facility Operational Assessment, CY 2011 Oak Ridge Leadership Computing Facility

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-02-01

    Oak Ridge National Laboratory's Leadership Computing Facility (OLCF) continues to deliver the most powerful resources in the U.S. for open science. At 2.33 petaflops peak performance, the Cray XT Jaguar delivered more than 1.4 billion core hours in calendar year (CY) 2011 to researchers around the world for computational simulations relevant to national and energy security; advancing the frontiers of knowledge in physical sciences and areas of biological, medical, environmental, and computer sciences; and providing world-class research facilities for the nation's science enterprise. Users reported more than 670 publications this year arising from their use of OLCF resources. Of these we report the 300 in this review that are consistent with guidance provided. Scientific achievements by OLCF users cut across all range scales from atomic to molecular to large-scale structures. At the atomic scale, researchers discovered that the anomalously long half-life of Carbon-14 can be explained by calculating, for the first time, the very complex three-body interactions between all the neutrons and protons in the nucleus. At the molecular scale, researchers combined experimental results from LBL's light source and simulations on Jaguar to discover how DNA replication continues past a damaged site so a mutation can be repaired later. Other researchers combined experimental results from ORNL's Spallation Neutron Source and simulations on Jaguar to reveal the molecular structure of ligno-cellulosic material used in bioethanol production. This year, Jaguar has been used to do billion-cell CFD calculations to develop shock wave compression turbo machinery as a means to meet DOE goals for reducing carbon sequestration costs. General Electric used Jaguar to calculate the unsteady flow through turbo machinery to learn what efficiencies the traditional steady flow assumption is hiding from designers. Even a 1% improvement in turbine design can save the nation

  1. High performance computing system in the framework of the Higgs boson studies

    CERN Document Server

    Belyaev, Nikita; The ATLAS collaboration; Velikhov, Vasily; Konoplich, Rostislav

    2017-01-01

    The Higgs boson physics is one of the most important and promising fields of study in the modern high energy physics. It is important to notice, that GRID computing resources become strictly limited due to increasing amount of statistics, required for physics analyses and unprecedented LHC performance. One of the possibilities to address the shortfall of computing resources is the usage of computer institutes' clusters, commercial computing resources and supercomputers. To perform precision measurements of the Higgs boson properties in these realities, it is also highly required to have effective instruments to simulate kinematic distributions of signal events. In this talk we give a brief description of the modern distribution reconstruction method called Morphing and perform few efficiency tests to demonstrate its potential. These studies have been performed on the WLCG and Kurchatov Institute’s Data Processing Center, including Tier-1 GRID site and supercomputer as well. We also analyze the CPU efficienc...

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

    Science.gov (United States)

    Bielski, Conrad; Lemoine, Guido; Syryczynski, Jacek

    2009-09-01

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

  3. High Performance Computing Facility Operational Assessment, FY 2011 Oak Ridge Leadership Computing Facility

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-08-01

    Oak Ridge National Laboratory's Leadership Computing Facility (OLCF) continues to deliver the most powerful resources in the U.S. for open science. At 2.33 petaflops peak performance, the Cray XT Jaguar delivered more than 1.5 billion core hours in calendar year (CY) 2010 to researchers around the world for computational simulations relevant to national and energy security; advancing the frontiers of knowledge in physical sciences and areas of biological, medical, environmental, and computer sciences; and providing world-class research facilities for the nation's science enterprise. Scientific achievements by OLCF users range from collaboration with university experimentalists to produce a working supercapacitor that uses atom-thick sheets of carbon materials to finely determining the resolution requirements for simulations of coal gasifiers and their components, thus laying the foundation for development of commercial-scale gasifiers. OLCF users are pushing the boundaries with software applications sustaining more than one petaflop of performance in the quest to illuminate the fundamental nature of electronic devices. Other teams of researchers are working to resolve predictive capabilities of climate models, to refine and validate genome sequencing, and to explore the most fundamental materials in nature - quarks and gluons - and their unique properties. Details of these scientific endeavors - not possible without access to leadership-class computing resources - are detailed in Section 4 of this report and in the INCITE in Review. Effective operations of the OLCF play a key role in the scientific missions and accomplishments of its users. This Operational Assessment Report (OAR) will delineate the policies, procedures, and innovations implemented by the OLCF to continue delivering a petaflop-scale resource for cutting-edge research. The 2010 operational assessment of the OLCF yielded recommendations that have been addressed (Reference Section 1) and

  4. Application of High Performance Computing to Earthquake Hazard and Disaster Estimation in Urban Area

    Directory of Open Access Journals (Sweden)

    Muneo Hori

    2018-02-01

    Full Text Available Integrated earthquake simulation (IES is a seamless simulation of analyzing all processes of earthquake hazard and disaster. There are two difficulties in carrying out IES, namely, the requirement of large-scale computation and the requirement of numerous analysis models for structures in an urban area, and they are solved by taking advantage of high performance computing (HPC and by developing a system of automated model construction. HPC is a key element in developing IES, as it needs to analyze wave propagation and amplification processes in an underground structure; a model of high fidelity for the underground structure exceeds a degree-of-freedom larger than 100 billion. Examples of IES for Tokyo Metropolis are presented; the numerical computation is made by using K computer, the supercomputer of Japan. The estimation of earthquake hazard and disaster for a given earthquake scenario is made by the ground motion simulation and the urban area seismic response simulation, respectively, for the target area of 10,000 m × 10,000 m.

  5. Enabling the ATLAS Experiment at the LHC for High Performance Computing

    CERN Document Server

    AUTHOR|(CDS)2091107; Ereditato, Antonio

    In this thesis, I studied the feasibility of running computer data analysis programs from the Worldwide LHC Computing Grid, in particular large-scale simulations of the ATLAS experiment at the CERN LHC, on current general purpose High Performance Computing (HPC) systems. An approach for integrating HPC systems into the Grid is proposed, which has been implemented and tested on the „Todi” HPC machine at the Swiss National Supercomputing Centre (CSCS). Over the course of the test, more than 500000 CPU-hours of processing time have been provided to ATLAS, which is roughly equivalent to the combined computing power of the two ATLAS clusters at the University of Bern. This showed that current HPC systems can be used to efficiently run large-scale simulations of the ATLAS detector and of the detected physics processes. As a first conclusion of my work, one can argue that, in perspective, running large-scale tasks on a few large machines might be more cost-effective than running on relatively small dedicated com...

  6. High-performance computational fluid dynamics: a custom-code approach

    International Nuclear Information System (INIS)

    Fannon, James; Náraigh, Lennon Ó; Loiseau, Jean-Christophe; Valluri, Prashant; Bethune, Iain

    2016-01-01

    We introduce a modified and simplified version of the pre-existing fully parallelized three-dimensional Navier–Stokes flow solver known as TPLS. We demonstrate how the simplified version can be used as a pedagogical tool for the study of computational fluid dynamics (CFDs) and parallel computing. TPLS is at its heart a two-phase flow solver, and uses calls to a range of external libraries to accelerate its performance. However, in the present context we narrow the focus of the study to basic hydrodynamics and parallel computing techniques, and the code is therefore simplified and modified to simulate pressure-driven single-phase flow in a channel, using only relatively simple Fortran 90 code with MPI parallelization, but no calls to any other external libraries. The modified code is analysed in order to both validate its accuracy and investigate its scalability up to 1000 CPU cores. Simulations are performed for several benchmark cases in pressure-driven channel flow, including a turbulent simulation, wherein the turbulence is incorporated via the large-eddy simulation technique. The work may be of use to advanced undergraduate and graduate students as an introductory study in CFDs, while also providing insight for those interested in more general aspects of high-performance computing. (paper)

  7. High-performance computational fluid dynamics: a custom-code approach

    Science.gov (United States)

    Fannon, James; Loiseau, Jean-Christophe; Valluri, Prashant; Bethune, Iain; Náraigh, Lennon Ó.

    2016-07-01

    We introduce a modified and simplified version of the pre-existing fully parallelized three-dimensional Navier-Stokes flow solver known as TPLS. We demonstrate how the simplified version can be used as a pedagogical tool for the study of computational fluid dynamics (CFDs) and parallel computing. TPLS is at its heart a two-phase flow solver, and uses calls to a range of external libraries to accelerate its performance. However, in the present context we narrow the focus of the study to basic hydrodynamics and parallel computing techniques, and the code is therefore simplified and modified to simulate pressure-driven single-phase flow in a channel, using only relatively simple Fortran 90 code with MPI parallelization, but no calls to any other external libraries. The modified code is analysed in order to both validate its accuracy and investigate its scalability up to 1000 CPU cores. Simulations are performed for several benchmark cases in pressure-driven channel flow, including a turbulent simulation, wherein the turbulence is incorporated via the large-eddy simulation technique. The work may be of use to advanced undergraduate and graduate students as an introductory study in CFDs, while also providing insight for those interested in more general aspects of high-performance computing.

  8. High performance parallel computing of flows in complex geometries: II. Applications

    International Nuclear Information System (INIS)

    Gourdain, N; Gicquel, L; Staffelbach, G; Vermorel, O; Duchaine, F; Boussuge, J-F; Poinsot, T

    2009-01-01

    Present regulations in terms of pollutant emissions, noise and economical constraints, require new approaches and designs in the fields of energy supply and transportation. It is now well established that the next breakthrough will come from a better understanding of unsteady flow effects and by considering the entire system and not only isolated components. However, these aspects are still not well taken into account by the numerical approaches or understood whatever the design stage considered. The main challenge is essentially due to the computational requirements inferred by such complex systems if it is to be simulated by use of supercomputers. This paper shows how new challenges can be addressed by using parallel computing platforms for distinct elements of a more complex systems as encountered in aeronautical applications. Based on numerical simulations performed with modern aerodynamic and reactive flow solvers, this work underlines the interest of high-performance computing for solving flow in complex industrial configurations such as aircrafts, combustion chambers and turbomachines. Performance indicators related to parallel computing efficiency are presented, showing that establishing fair criterions is a difficult task for complex industrial applications. Examples of numerical simulations performed in industrial systems are also described with a particular interest for the computational time and the potential design improvements obtained with high-fidelity and multi-physics computing methods. These simulations use either unsteady Reynolds-averaged Navier-Stokes methods or large eddy simulation and deal with turbulent unsteady flows, such as coupled flow phenomena (thermo-acoustic instabilities, buffet, etc). Some examples of the difficulties with grid generation and data analysis are also presented when dealing with these complex industrial applications.

  9. BEAGLE: an application programming interface and high-performance computing library for statistical phylogenetics.

    Science.gov (United States)

    Ayres, Daniel L; Darling, Aaron; Zwickl, Derrick J; Beerli, Peter; Holder, Mark T; Lewis, Paul O; Huelsenbeck, John P; Ronquist, Fredrik; Swofford, David L; Cummings, Michael P; Rambaut, Andrew; Suchard, Marc A

    2012-01-01

    Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a common library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an application programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently exploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software.

  10. Low-cost, high-performance and efficiency computational photometer design

    Science.gov (United States)

    Siewert, Sam B.; Shihadeh, Jeries; Myers, Randall; Khandhar, Jay; Ivanov, Vitaly

    2014-05-01

    Researchers at the University of Alaska Anchorage and University of Colorado Boulder have built a low cost high performance and efficiency drop-in-place Computational Photometer (CP) to test in field applications ranging from port security and safety monitoring to environmental compliance monitoring and surveying. The CP integrates off-the-shelf visible spectrum cameras with near to long wavelength infrared detectors and high resolution digital snapshots in a single device. The proof of concept combines three or more detectors into a single multichannel imaging system that can time correlate read-out, capture, and image process all of the channels concurrently with high performance and energy efficiency. The dual-channel continuous read-out is combined with a third high definition digital snapshot capability and has been designed using an FPGA (Field Programmable Gate Array) to capture, decimate, down-convert, re-encode, and transform images from two standard definition CCD (Charge Coupled Device) cameras at 30Hz. The continuous stereo vision can be time correlated to megapixel high definition snapshots. This proof of concept has been fabricated as a fourlayer PCB (Printed Circuit Board) suitable for use in education and research for low cost high efficiency field monitoring applications that need multispectral and three dimensional imaging capabilities. Initial testing is in progress and includes field testing in ports, potential test flights in un-manned aerial systems, and future planned missions to image harsh environments in the arctic including volcanic plumes, ice formation, and arctic marine life.

  11. Cactus and Visapult: A case study of ultra-high performance distributed visualization using connectionless protocols

    Energy Technology Data Exchange (ETDEWEB)

    Shalf, John; Bethel, E. Wes

    2002-05-07

    This past decade has seen rapid growth in the size, resolution, and complexity of Grand Challenge simulation codes. Many such problems still require interactive visualization tools to make sense of multi-terabyte data stores. Visapult is a parallel volume rendering tool that employs distributed components, latency tolerant algorithms, and high performance network I/O for effective remote visualization of massive datasets. In this paper we discuss using connectionless protocols to accelerate Visapult network I/O and interfacing Visapult to the Cactus General Relativity code to enable scalable remote monitoring and steering capabilities. With these modifications, network utilization has moved from 25 percent of line-rate using tuned multi-streamed TCP to sustaining 88 percent of line rate using the new UDP-based transport protocol.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-01-01

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

  13. A C++11 implementation of arbitrary-rank tensors for high-performance computing

    Science.gov (United States)

    Aragón, Alejandro M.

    2014-11-01

    This article discusses an efficient implementation of tensors of arbitrary rank by using some of the idioms introduced by the recently published C++ ISO Standard (C++11). With the aims at providing a basic building block for high-performance computing, a single Array class template is carefully crafted, from which vectors, matrices, and even higher-order tensors can be created. An expression template facility is also built around the array class template to provide convenient mathematical syntax. As a result, by using templates, an extra high-level layer is added to the C++ language when dealing with algebraic objects and their operations, without compromising performance. The implementation is tested running on both CPU and GPU.

  14. Additive Manufacturing and High-Performance Computing: a Disruptive Latent Technology

    Science.gov (United States)

    Goodwin, Bruce

    2015-03-01

    This presentation will discuss the relationship between recent advances in Additive Manufacturing (AM) technology, High-Performance Computing (HPC) simulation and design capabilities, and related advances in Uncertainty Quantification (UQ), and then examines their impacts upon national and international security. The presentation surveys how AM accelerates the fabrication process, while HPC combined with UQ provides a fast track for the engineering design cycle. The combination of AM and HPC/UQ almost eliminates the engineering design and prototype iterative cycle, thereby dramatically reducing cost of production and time-to-market. These methods thereby present significant benefits for US national interests, both civilian and military, in an age of austerity. Finally, considering cyber security issues and the advent of the ``cloud,'' these disruptive, currently latent technologies may well enable proliferation and so challenge both nuclear and non-nuclear aspects of international security.

  15. 7th International Workshop on Parallel Tools for High Performance Computing

    CERN Document Server

    Gracia, José; Nagel, Wolfgang; Resch, Michael

    2014-01-01

    Current advances in High Performance Computing (HPC) increasingly impact efficient software development workflows. Programmers for HPC applications need to consider trends such as increased core counts, multiple levels of parallelism, reduced memory per core, and I/O system challenges in order to derive well performing and highly scalable codes. At the same time, the increasing complexity adds further sources of program defects. While novel programming paradigms and advanced system libraries provide solutions for some of these challenges, appropriate supporting tools are indispensable. Such tools aid application developers in debugging, performance analysis, or code optimization and therefore make a major contribution to the development of robust and efficient parallel software. This book introduces a selection of the tools presented and discussed at the 7th International Parallel Tools Workshop, held in Dresden, Germany, September 3-4, 2013.  

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-11-11

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

  17. 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.

  18. Cloud CPFP: a shotgun proteomics data analysis pipeline using cloud and high performance computing.

    Science.gov (United States)

    Trudgian, David C; Mirzaei, Hamid

    2012-12-07

    We have extended the functionality of the Central Proteomics Facilities Pipeline (CPFP) to allow use of remote cloud and high performance computing (HPC) resources for shotgun proteomics data processing. CPFP has been modified to include modular local and remote scheduling for data processing jobs. The pipeline can now be run on a single PC or server, a local cluster, a remote HPC cluster, and/or the Amazon Web Services (AWS) cloud. We provide public images that allow easy deployment of CPFP in its entirety in the AWS cloud. This significantly reduces the effort necessary to use the software, and allows proteomics laboratories to pay for compute time ad hoc, rather than obtaining and maintaining expensive local server clusters. Alternatively the Amazon cloud can be used to increase the throughput of a local installation of CPFP as necessary. We demonstrate that cloud CPFP allows users to process data at higher speed than local installations but with similar cost and lower staff requirements. In addition to the computational improvements, the web interface to CPFP is simplified, and other functionalities are enhanced. The software is under active development at two leading institutions and continues to be released under an open-source license at http://cpfp.sourceforge.net.

  19. High-performance implementation of Chebyshev filter diagonalization for interior eigenvalue computations

    Energy Technology Data Exchange (ETDEWEB)

    Pieper, Andreas [Ernst-Moritz-Arndt-Universität Greifswald (Germany); Kreutzer, Moritz [Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany); Alvermann, Andreas, E-mail: alvermann@physik.uni-greifswald.de [Ernst-Moritz-Arndt-Universität Greifswald (Germany); Galgon, Martin [Bergische Universität Wuppertal (Germany); Fehske, Holger [Ernst-Moritz-Arndt-Universität Greifswald (Germany); Hager, Georg [Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany); Lang, Bruno [Bergische Universität Wuppertal (Germany); Wellein, Gerhard [Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)

    2016-11-15

    We study Chebyshev filter diagonalization as a tool for the computation of many interior eigenvalues of very large sparse symmetric matrices. In this technique the subspace projection onto the target space of wanted eigenvectors is approximated with filter polynomials obtained from Chebyshev expansions of window functions. After the discussion of the conceptual foundations of Chebyshev filter diagonalization we analyze the impact of the choice of the damping kernel, search space size, and filter polynomial degree on the computational accuracy and effort, before we describe the necessary steps towards a parallel high-performance implementation. Because Chebyshev filter diagonalization avoids the need for matrix inversion it can deal with matrices and problem sizes that are presently not accessible with rational function methods based on direct or iterative linear solvers. To demonstrate the potential of Chebyshev filter diagonalization for large-scale problems of this kind we include as an example the computation of the 10{sup 2} innermost eigenpairs of a topological insulator matrix with dimension 10{sup 9} derived from quantum physics applications.

  20. High performance parallel computing of flows in complex geometries: I. Methods

    International Nuclear Information System (INIS)

    Gourdain, N; Gicquel, L; Montagnac, M; Vermorel, O; Staffelbach, G; Garcia, M; Boussuge, J-F; Gazaix, M; Poinsot, T

    2009-01-01

    Efficient numerical tools coupled with high-performance computers, have become a key element of the design process in the fields of energy supply and transportation. However flow phenomena that occur in complex systems such as gas turbines and aircrafts are still not understood mainly because of the models that are needed. In fact, most computational fluid dynamics (CFD) predictions as found today in industry focus on a reduced or simplified version of the real system (such as a periodic sector) and are usually solved with a steady-state assumption. This paper shows how to overcome such barriers and how such a new challenge can be addressed by developing flow solvers running on high-end computing platforms, using thousands of computing cores. Parallel strategies used by modern flow solvers are discussed with particular emphases on mesh-partitioning, load balancing and communication. Two examples are used to illustrate these concepts: a multi-block structured code and an unstructured code. Parallel computing strategies used with both flow solvers are detailed and compared. This comparison indicates that mesh-partitioning and load balancing are more straightforward with unstructured grids than with multi-block structured meshes. However, the mesh-partitioning stage can be challenging for unstructured grids, mainly due to memory limitations of the newly developed massively parallel architectures. Finally, detailed investigations show that the impact of mesh-partitioning on the numerical CFD solutions, due to rounding errors and block splitting, may be of importance and should be accurately addressed before qualifying massively parallel CFD tools for a routine industrial use.

  1. Performance management of high performance computing for medical image processing in Amazon Web Services

    Science.gov (United States)

    Bao, Shunxing; Damon, Stephen M.; Landman, Bennett A.; Gokhale, Aniruddha

    2016-03-01

    Adopting high performance cloud computing for medical image processing is a popular trend given the pressing needs of large studies. Amazon Web Services (AWS) provide reliable, on-demand, and inexpensive cloud computing services. Our research objective is to implement an affordable, scalable and easy-to-use AWS framework for the Java Image Science Toolkit (JIST). JIST is a plugin for Medical- Image Processing, Analysis, and Visualization (MIPAV) that provides a graphical pipeline implementation allowing users to quickly test and develop pipelines. JIST is DRMAA-compliant allowing it to run on portable batch system grids. However, as new processing methods are implemented and developed, memory may often be a bottleneck for not only lab computers, but also possibly some local grids. Integrating JIST with the AWS cloud alleviates these possible restrictions and does not require users to have deep knowledge of programming in Java. Workflow definition/management and cloud configurations are two key challenges in this research. Using a simple unified control panel, users have the ability to set the numbers of nodes and select from a variety of pre-configured AWS EC2 nodes with different numbers of processors and memory storage. Intuitively, we configured Amazon S3 storage to be mounted by pay-for- use Amazon EC2 instances. Hence, S3 storage is recognized as a shared cloud resource. The Amazon EC2 instances provide pre-installs of all necessary packages to run JIST. This work presents an implementation that facilitates the integration of JIST with AWS. We describe the theoretical cost/benefit formulae to decide between local serial execution versus cloud computing and apply this analysis to an empirical diffusion tensor imaging pipeline.

  2. Performance Management of High Performance Computing for Medical Image Processing in Amazon Web Services.

    Science.gov (United States)

    Bao, Shunxing; Damon, Stephen M; Landman, Bennett A; Gokhale, Aniruddha

    2016-02-27

    Adopting high performance cloud computing for medical image processing is a popular trend given the pressing needs of large studies. Amazon Web Services (AWS) provide reliable, on-demand, and inexpensive cloud computing services. Our research objective is to implement an affordable, scalable and easy-to-use AWS framework for the Java Image Science Toolkit (JIST). JIST is a plugin for Medical-Image Processing, Analysis, and Visualization (MIPAV) that provides a graphical pipeline implementation allowing users to quickly test and develop pipelines. JIST is DRMAA-compliant allowing it to run on portable batch system grids. However, as new processing methods are implemented and developed, memory may often be a bottleneck for not only lab computers, but also possibly some local grids. Integrating JIST with the AWS cloud alleviates these possible restrictions and does not require users to have deep knowledge of programming in Java. Workflow definition/management and cloud configurations are two key challenges in this research. Using a simple unified control panel, users have the ability to set the numbers of nodes and select from a variety of pre-configured AWS EC2 nodes with different numbers of processors and memory storage. Intuitively, we configured Amazon S3 storage to be mounted by pay-for-use Amazon EC2 instances. Hence, S3 storage is recognized as a shared cloud resource. The Amazon EC2 instances provide pre-installs of all necessary packages to run JIST. This work presents an implementation that facilitates the integration of JIST with AWS. We describe the theoretical cost/benefit formulae to decide between local serial execution versus cloud computing and apply this analysis to an empirical diffusion tensor imaging pipeline.

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

    Directory of Open Access Journals (Sweden)

    Alberto Cocaña-Fernández

    2016-03-01

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

  4. Peer-to-peer computing for secure high performance data copying

    International Nuclear Information System (INIS)

    Hanushevsky, A.; Trunov, A.; Cottrell, L.

    2001-01-01

    The BaBar Copy Program (bbcp) is an excellent representative of peer-to-peer (P2P) computing. It is also a pioneering application of its type in the P2P arena. Built upon the foundation of its predecessor, Secure Fast Copy (sfcp), bbcp incorporates significant improvements performance and usability. As with sfcp, bbcp uses ssh for authentication; providing an elegant and simple working model--if you can ssh to a location, you can copy files to or from that location. To fully support this notion, bbcp transparently supports 3rd party copy operations. The program also incorporates several mechanism to deal with firewall security; the bane of P2P computing. To achieve high performance in a wide area network, bbcp allows a user to independently specify, the number of parallel network streams, tcp window size, and the file I/O blocking factor. Using these parameters, data is pipelined from source to target to provide a uniform traffic pattern that maximizes router efficiency. For improved recoverability, bbcp also keeps track of copy operations so that an operation can be restarted from the point of failure at a later time; minimizing the amount of network traffic in the event of a copy failure. Here, the authors present the bbcp architecture, it's various features, and the reasons for their inclusion

  5. Accelerated Synchrotron X-ray Diffraction Data Analysis on a Heterogeneous High Performance Computing System

    Energy Technology Data Exchange (ETDEWEB)

    Qin, J; Bauer, M A, E-mail: qin.jinhui@gmail.com, E-mail: bauer@uwo.ca [Computer Science Department, University of Western Ontario, London, ON N6A 5B7 (Canada)

    2010-11-01

    The analysis of synchrotron X-ray Diffraction (XRD) data has been used by scientists and engineers to understand and predict properties of materials. However, the large volume of XRD image data and the intensive computations involved in the data analysis makes it hard for researchers to quickly reach any conclusions about the images from an experiment when using conventional XRD data analysis software. Synchrotron time is valuable and delays in XRD data analysis can impact decisions about subsequent experiments or about materials that they are investigating. In order to improve the data analysis performance, ideally to achieve near real time data analysis during an XRD experiment, we designed and implemented software for accelerated XRD data analysis. The software has been developed for a heterogeneous high performance computing (HPC) system, comprised of IBM PowerXCell 8i processors and Intel quad-core Xeon processors. This paper describes the software and reports on the improved performance. The results indicate that it is possible for XRD data to be analyzed at the rate it is being produced.

  6. Accelerated Synchrotron X-ray Diffraction Data Analysis on a Heterogeneous High Performance Computing System

    International Nuclear Information System (INIS)

    Qin, J; Bauer, M A

    2010-01-01

    The analysis of synchrotron X-ray Diffraction (XRD) data has been used by scientists and engineers to understand and predict properties of materials. However, the large volume of XRD image data and the intensive computations involved in the data analysis makes it hard for researchers to quickly reach any conclusions about the images from an experiment when using conventional XRD data analysis software. Synchrotron time is valuable and delays in XRD data analysis can impact decisions about subsequent experiments or about materials that they are investigating. In order to improve the data analysis performance, ideally to achieve near real time data analysis during an XRD experiment, we designed and implemented software for accelerated XRD data analysis. The software has been developed for a heterogeneous high performance computing (HPC) system, comprised of IBM PowerXCell 8i processors and Intel quad-core Xeon processors. This paper describes the software and reports on the improved performance. The results indicate that it is possible for XRD data to be analyzed at the rate it is being produced.

  7. Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

    Science.gov (United States)

    Ganguly, S.; Kumar, U.; Nemani, R. R.; Kalia, S.; Michaelis, A.

    2017-12-01

    In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS - national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91% was achieved, which is a 6% improvement in unmixing based classification relative to per-pixel based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.

  8. Development of high performance scientific components for interoperability of computing packages

    Energy Technology Data Exchange (ETDEWEB)

    Gulabani, Teena Pratap [Iowa State Univ., Ames, IA (United States)

    2008-01-01

    Three major high performance quantum chemistry computational packages, NWChem, GAMESS and MPQC have been developed by different research efforts following different design patterns. The goal is to achieve interoperability among these packages by overcoming the challenges caused by the different communication patterns and software design of each of these packages. A chemistry algorithm is hard to develop as well as being a time consuming process; integration of large quantum chemistry packages will allow resource sharing and thus avoid reinvention of the wheel. Creating connections between these incompatible packages is the major motivation of the proposed work. This interoperability is achieved by bringing the benefits of Component Based Software Engineering through a plug-and-play component framework called Common Component Architecture (CCA). In this thesis, I present a strategy and process used for interfacing two widely used and important computational chemistry methodologies: Quantum Mechanics and Molecular Mechanics. To show the feasibility of the proposed approach the Tuning and Analysis Utility (TAU) has been coupled with NWChem code and its CCA components. Results show that the overhead is negligible when compared to the ease and potential of organizing and coping with large-scale software applications.

  9. Peer-to-Peer Computing for Secure High Performance Data Copying

    International Nuclear Information System (INIS)

    2002-01-01

    The BaBar Copy Program (bbcp) is an excellent representative of peer-to-peer (P2P) computing. It is also a pioneering application of its type in the P2P arena. Built upon the foundation of its predecessor, Secure Fast Copy (sfcp), bbcp incorporates significant improvements performance and usability. As with sfcp, bbcp uses ssh for authentication; providing an elegant and simple working model -- if you can ssh to a location, you can copy files to or from that location. To fully support this notion, bbcp transparently supports 3rd party copy operations. The program also incorporates several mechanism to deal with firewall security; the bane of P2P computing. To achieve high performance in a wide area network, bbcp allows a user to independently specify, the number of parallel network streams, tcp window size, and the file I/O blocking factor. Using these parameters, data is pipelined from source to target to provide a uniform traffic pattern that maximizes router efficiency. For improved recoverability, bbcp also keeps track of copy operations so that an operation can be restarted from the point of failure at a later time; minimizing the amount of network traffic in the event of a copy failure. Here, we preset the bbcp architecture, it's various features, and the reasons for their inclusion

  10. Scalable domain decomposition solvers for stochastic PDEs in high performance computing

    International Nuclear Information System (INIS)

    Desai, Ajit; Pettit, Chris; Poirel, Dominique; Sarkar, Abhijit

    2017-01-01

    Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolution in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.

  11. High performance optical encryption based on computational ghost imaging with QR code and compressive sensing technique

    Science.gov (United States)

    Zhao, Shengmei; Wang, Le; Liang, Wenqiang; Cheng, Weiwen; Gong, Longyan

    2015-10-01

    In this paper, we propose a high performance optical encryption (OE) scheme based on computational ghost imaging (GI) with QR code and compressive sensing (CS) technique, named QR-CGI-OE scheme. N random phase screens, generated by Alice, is a secret key and be shared with its authorized user, Bob. The information is first encoded by Alice with QR code, and the QR-coded image is then encrypted with the aid of computational ghost imaging optical system. Here, measurement results from the GI optical system's bucket detector are the encrypted information and be transmitted to Bob. With the key, Bob decrypts the encrypted information to obtain the QR-coded image with GI and CS techniques, and further recovers the information by QR decoding. The experimental and numerical simulated results show that the authorized users can recover completely the original image, whereas the eavesdroppers can not acquire any information about the image even the eavesdropping ratio (ER) is up to 60% at the given measurement times. For the proposed scheme, the number of bits sent from Alice to Bob are reduced considerably and the robustness is enhanced significantly. Meantime, the measurement times in GI system is reduced and the quality of the reconstructed QR-coded image is improved.

  12. Towards the development of run times leveraging virtualization for high performance computing

    International Nuclear Information System (INIS)

    Diakhate, F.

    2010-12-01

    In recent years, there has been a growing interest in using virtualization to improve the efficiency of data centers. This success is rooted in virtualization's excellent fault tolerance and isolation properties, in the overall flexibility it brings, and in its ability to exploit multi-core architectures efficiently. These characteristics also make virtualization an ideal candidate to tackle issues found in new compute cluster architectures. However, in spite of recent improvements in virtualization technology, overheads in the execution of parallel applications remain, which prevent its use in the field of high performance computing. In this thesis, we propose a virtual device dedicated to message passing between virtual machines, so as to improve the performance of parallel applications executed in a cluster of virtual machines. We also introduce a set of techniques facilitating the deployment of virtualized parallel applications. These functionalities have been implemented as part of a runtime system which allows to benefit from virtualization's properties in a way that is as transparent as possible to the user while minimizing performance overheads. (author)

  13. Applying Machine Learning and High Performance Computing to Water Quality Assessment and Prediction

    Directory of Open Access Journals (Sweden)

    Ruijian Zhang

    2017-12-01

    Full Text Available Water quality assessment and prediction is a more and more important issue. Traditional ways either take lots of time or they can only do assessments. In this research, by applying machine learning algorithm to a long period time of water attributes’ data; we can generate a decision tree so that it can predict the future day’s water quality in an easy and efficient way. The idea is to combine the traditional ways and the computer algorithms together. Using machine learning algorithms, the assessment of water quality will be far more efficient, and by generating the decision tree, the prediction will be quite accurate. The drawback of the machine learning modeling is that the execution takes quite long time, especially when we employ a better accuracy but more time-consuming algorithm in clustering. Therefore, we applied the high performance computing (HPC System to deal with this problem. Up to now, the pilot experiments have achieved very promising preliminary results. The visualized water quality assessment and prediction obtained from this project would be published in an interactive website so that the public and the environmental managers could use the information for their decision making.

  14. Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation/Completion of Episodic Information.

    Energy Technology Data Exchange (ETDEWEB)

    Aimone, James Bradley [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Betty, Rita [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-03-01

    Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation/Completion of Episodic Information - Sandia researchers developed novel methods and metrics for studying the computational function of neurogenesis, thus generating substantial impact to the neuroscience and neural computing communities. This work could benefit applications in machine learning and other analysis activities.

  15. 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.

  16. A high performance computing framework for physics-based modeling and simulation of military ground vehicles

    Science.gov (United States)

    Negrut, Dan; Lamb, David; Gorsich, David

    2011-06-01

    This paper describes a software infrastructure made up of tools and libraries designed to assist developers in implementing computational dynamics applications running on heterogeneous and distributed computing environments. Together, these tools and libraries compose a so called Heterogeneous Computing Template (HCT). The heterogeneous and distributed computing hardware infrastructure is assumed herein to be made up of a combination of CPUs and Graphics Processing Units (GPUs). The computational dynamics applications targeted to execute on such a hardware topology include many-body dynamics, smoothed-particle hydrodynamics (SPH) fluid simulation, and fluid-solid interaction analysis. The underlying theme of the solution approach embraced by HCT is that of partitioning the domain of interest into a number of subdomains that are each managed by a separate core/accelerator (CPU/GPU) pair. Five components at the core of HCT enable the envisioned distributed computing approach to large-scale dynamical system simulation: (a) the ability to partition the problem according to the one-to-one mapping; i.e., spatial subdivision, discussed above (pre-processing); (b) a protocol for passing data between any two co-processors; (c) algorithms for element proximity computation; and (d) the ability to carry out post-processing in a distributed fashion. In this contribution the components (a) and (b) of the HCT are demonstrated via the example of the Discrete Element Method (DEM) for rigid body dynamics with friction and contact. The collision detection task required in frictional-contact dynamics (task (c) above), is shown to benefit on the GPU of a two order of magnitude gain in efficiency when compared to traditional sequential implementations. Note: Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not imply its endorsement, recommendation, or favoring by the United States Army. The views and

  17. Confabulation Based Real-time Anomaly Detection for Wide-area Surveillance Using Heterogeneous High Performance Computing Architecture

    Science.gov (United States)

    2015-06-01

    CONFABULATION BASED REAL-TIME ANOMALY DETECTION FOR WIDE-AREA SURVEILLANCE USING HETEROGENEOUS HIGH PERFORMANCE COMPUTING ARCHITECTURE SYRACUSE...DETECTION FOR WIDE-AREA SURVEILLANCE USING HETEROGENEOUS HIGH PERFORMANCE COMPUTING ARCHITECTURE 5a. CONTRACT NUMBER FA8750-12-1-0251 5b. GRANT...processors including graphic processor units (GPUs) and Intel Xeon Phi processors. Experimental results showed significant speedups, which can enable

  18. 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.

  19. Strengthening LLNL Missions through Laboratory Directed Research and Development in High Performance Computing

    Energy Technology Data Exchange (ETDEWEB)

    Willis, D. K. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-12-01

    High performance computing (HPC) has been a defining strength of Lawrence Livermore National Laboratory (LLNL) since its founding. Livermore scientists have designed and used some of the world’s most powerful computers to drive breakthroughs in nearly every mission area. Today, the Laboratory is recognized as a world leader in the application of HPC to complex science, technology, and engineering challenges. Most importantly, HPC has been integral to the National Nuclear Security Administration’s (NNSA’s) Stockpile Stewardship Program—designed to ensure the safety, security, and reliability of our nuclear deterrent without nuclear testing. A critical factor behind Lawrence Livermore’s preeminence in HPC is the ongoing investments made by the Laboratory Directed Research and Development (LDRD) Program in cutting-edge concepts to enable efficient utilization of these powerful machines. Congress established the LDRD Program in 1991 to maintain the technical vitality of the Department of Energy (DOE) national laboratories. Since then, LDRD has been, and continues to be, an essential tool for exploring anticipated needs that lie beyond the planning horizon of our programs and for attracting the next generation of talented visionaries. Through LDRD, Livermore researchers can examine future challenges, propose and explore innovative solutions, and deliver creative approaches to support our missions. The present scientific and technical strengths of the Laboratory are, in large part, a product of past LDRD investments in HPC. Here, we provide seven examples of LDRD projects from the past decade that have played a critical role in building LLNL’s HPC, computer science, mathematics, and data science research capabilities, and describe how they have impacted LLNL’s mission.

  20. Direct numerical simulation of reactor two-phase flows enabled by high-performance computing

    Energy Technology Data Exchange (ETDEWEB)

    Fang, Jun; Cambareri, Joseph J.; Brown, Cameron S.; Feng, Jinyong; Gouws, Andre; Li, Mengnan; Bolotnov, Igor A.

    2018-04-01

    Nuclear reactor two-phase flows remain a great engineering challenge, where the high-resolution two-phase flow database which can inform practical model development is still sparse due to the extreme reactor operation conditions and measurement difficulties. Owing to the rapid growth of computing power, the direct numerical simulation (DNS) is enjoying a renewed interest in investigating the related flow problems. A combination between DNS and an interface tracking method can provide a unique opportunity to study two-phase flows based on first principles calculations. More importantly, state-of-the-art high-performance computing (HPC) facilities are helping unlock this great potential. This paper reviews the recent research progress of two-phase flow DNS related to reactor applications. The progress in large-scale bubbly flow DNS has been focused not only on the sheer size of those simulations in terms of resolved Reynolds number, but also on the associated advanced modeling and analysis techniques. Specifically, the current areas of active research include modeling of sub-cooled boiling, bubble coalescence, as well as the advanced post-processing toolkit for bubbly flow simulations in reactor geometries. A novel bubble tracking method has been developed to track the evolution of bubbles in two-phase bubbly flow. Also, spectral analysis of DNS database in different geometries has been performed to investigate the modulation of the energy spectrum slope due to bubble-induced turbulence. In addition, the single-and two-phase analysis results are presented for turbulent flows within the pressurized water reactor (PWR) core geometries. The related simulations are possible to carry out only with the world leading HPC platforms. These simulations are allowing more complex turbulence model development and validation for use in 3D multiphase computational fluid dynamics (M-CFD) codes.

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

    Science.gov (United States)

    Khosronejad, A.

    2016-12-01

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

  2. 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.

  3. A Lightweight, High-performance I/O Management Package for Data-intensive Computing

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Jun

    2011-06-22

    Our group has been working with ANL collaborators on the topic bridging the gap between parallel file system and local file system during the course of this project period. We visited Argonne National Lab -- Dr. Robert Ross's group for one week in the past summer 2007. We looked over our current project progress and planned the activities for the incoming years 2008-09. The PI met Dr. Robert Ross several times such as HEC FSIO workshop 08, SC08 and SC10. We explored the opportunities to develop a production system by leveraging our current prototype to (SOGP+PVFS) a new PVFS version. We delivered SOGP+PVFS codes to ANL PVFS2 group in 2008.We also talked about exploring a potential project on developing new parallel programming models and runtime systems for data-intensive scalable computing (DISC). The methodology is to evolve MPI towards DISC by incorporating some functions of Google MapReduce parallel programming model. More recently, we are together exploring how to leverage existing works to perform (1) coordination/aggregation of local I/O operations prior to movement over the WAN, (2) efficient bulk data movement over the WAN, (3) latency hiding techniques for latency-intensive operations. Since 2009, we start applying Hadoop/MapReduce to some HEC applications with LANL scientists John Bent and Salman Habib. Another on-going work is to improve checkpoint performance at I/O forwarding Layer for the Road Runner super computer with James Nuetz and Gary Gridder at LANL. Two senior undergraduates from our research group did summer internships about high-performance file and storage system projects in LANL since 2008 for consecutive three years. Both of them are now pursuing Ph.D. degree in our group and will be 4th year in the PhD program in Fall 2011 and go to LANL to advance two above-mentioned works during this winter break. Since 2009, we have been collaborating with several computer scientists (Gary Grider, John bent, Parks Fields, James Nunez, Hsing

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

    Energy Technology Data Exchange (ETDEWEB)

    Hamlet, Jason R.; Keliiaa, Curtis M.

    2010-09-01

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

  5. High-Performance Computer Modeling of the Cosmos-Iridium Collision

    Energy Technology Data Exchange (ETDEWEB)

    Olivier, S; Cook, K; Fasenfest, B; Jefferson, D; Jiang, M; Leek, J; Levatin, J; Nikolaev, S; Pertica, A; Phillion, D; Springer, K; De Vries, W

    2009-08-28

    This paper describes the application of a new, integrated modeling and simulation framework, encompassing the space situational awareness (SSA) enterprise, to the recent Cosmos-Iridium collision. This framework is based on a flexible, scalable architecture to enable efficient simulation of the current SSA enterprise, and to accommodate future advancements in SSA systems. In particular, the code is designed to take advantage of massively parallel, high-performance computer systems available, for example, at Lawrence Livermore National Laboratory. We will describe the application of this framework to the recent collision of the Cosmos and Iridium satellites, including (1) detailed hydrodynamic modeling of the satellite collision and resulting debris generation, (2) orbital propagation of the simulated debris and analysis of the increased risk to other satellites (3) calculation of the radar and optical signatures of the simulated debris and modeling of debris detection with space surveillance radar and optical systems (4) determination of simulated debris orbits from modeled space surveillance observations and analysis of the resulting orbital accuracy, (5) comparison of these modeling and simulation results with Space Surveillance Network observations. We will also discuss the use of this integrated modeling and simulation framework to analyze the risks and consequences of future satellite collisions and to assess strategies for mitigating or avoiding future incidents, including the addition of new sensor systems, used in conjunction with the Space Surveillance Network, for improving space situational awareness.

  6. Analysis of Application Power and Schedule Composition in a High Performance Computing Environment

    Energy Technology Data Exchange (ETDEWEB)

    Elmore, Ryan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gruchalla, Kenny [National Renewable Energy Lab. (NREL), Golden, CO (United States); Phillips, Caleb [National Renewable Energy Lab. (NREL), Golden, CO (United States); Purkayastha, Avi [National Renewable Energy Lab. (NREL), Golden, CO (United States); Wunder, Nick [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2016-01-05

    As the capacity of high performance computing (HPC) systems continues to grow, small changes in energy management have the potential to produce significant energy savings. In this paper, we employ an extensive informatics system for aggregating and analyzing real-time performance and power use data to evaluate energy footprints of jobs running in an HPC data center. We look at the effects of algorithmic choices for a given job on the resulting energy footprints, and analyze application-specific power consumption, and summarize average power use in the aggregate. All of these views reveal meaningful power variance between classes of applications as well as chosen methods for a given job. Using these data, we discuss energy-aware cost-saving strategies based on reordering the HPC job schedule. Using historical job and power data, we present a hypothetical job schedule reordering that: (1) reduces the facility's peak power draw and (2) manages power in conjunction with a large-scale photovoltaic array. Lastly, we leverage this data to understand the practical limits on predicting key power use metrics at the time of submission.

  7. Performance Analysis of Ivshmem for High-Performance Computing in Virtual Machines

    Science.gov (United States)

    Ivanovic, Pavle; Richter, Harald

    2018-01-01

    High-Performance computing (HPC) is rarely accomplished via virtual machines (VMs). In this paper, we present a remake of ivshmem which can change this. Ivshmem was a shared memory (SHM) between virtual machines on the same server, with SHM-access synchronization included, until about 5 years ago when newer versions of Linux and its virtualization library libvirt evolved. We restored that SHM-access synchronization feature because it is indispensable for HPC and made ivshmem runnable with contemporary versions of Linux, libvirt, KVM, QEMU and especially MPICH, which is an implementation of MPI - the standard HPC communication library. Additionally, MPICH was transparently modified by us to get ivshmem included, resulting in a three to ten times performance improvement compared to TCP/IP. Furthermore, we have transparently replaced MPI_PUT, a single-side MPICH communication mechanism, by an own MPI_PUT wrapper. As a result, our ivshmem even surpasses non-virtualized SHM data transfers for block lengths greater than 512 KBytes, showing the benefits of virtualization. All improvements were possible without using SR-IOV.

  8. ABINIT: Plane-Wave-Based Density-Functional Theory on High Performance Computers

    Science.gov (United States)

    Torrent, Marc

    2014-03-01

    For several years, a continuous effort has been produced to adapt electronic structure codes based on Density-Functional Theory to the future computing architectures. Among these codes, ABINIT is based on a plane-wave description of the wave functions which allows to treat systems of any kind. Porting such a code on petascale architectures pose difficulties related to the many-body nature of the DFT equations. To improve the performances of ABINIT - especially for what concerns standard LDA/GGA ground-state and response-function calculations - several strategies have been followed: A full multi-level parallelisation MPI scheme has been implemented, exploiting all possible levels and distributing both computation and memory. It allows to increase the number of distributed processes and could not be achieved without a strong restructuring of the code. The core algorithm used to solve the eigen problem (``Locally Optimal Blocked Congugate Gradient''), a Blocked-Davidson-like algorithm, is based on a distribution of processes combining plane-waves and bands. In addition to the distributed memory parallelization, a full hybrid scheme has been implemented, using standard shared-memory directives (openMP/openACC) or porting some comsuming code sections to Graphics Processing Units (GPU). As no simple performance model exists, the complexity of use has been increased; the code efficiency strongly depends on the distribution of processes among the numerous levels. ABINIT is able to predict the performances of several process distributions and automatically choose the most favourable one. On the other hand, a big effort has been carried out to analyse the performances of the code on petascale architectures, showing which sections of codes have to be improved; they all are related to Matrix Algebra (diagonalisation, orthogonalisation). The different strategies employed to improve the code scalability will be described. They are based on an exploration of new diagonalization

  9. Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

    Science.gov (United States)

    Hadjidoukas, P. E.; Angelikopoulos, P.; Papadimitriou, C.; Koumoutsakos, P.

    2015-03-01

    We present Π4U, an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

  10. Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

    International Nuclear Information System (INIS)

    Hadjidoukas, P.E.; Angelikopoulos, P.; Papadimitriou, C.; Koumoutsakos, P.

    2015-01-01

    We present Π4U, 1 an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow

  11. Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

    Energy Technology Data Exchange (ETDEWEB)

    Hadjidoukas, P.E.; Angelikopoulos, P. [Computational Science and Engineering Laboratory, ETH Zürich, CH-8092 (Switzerland); Papadimitriou, C. [Department of Mechanical Engineering, University of Thessaly, GR-38334 Volos (Greece); Koumoutsakos, P., E-mail: petros@ethz.ch [Computational Science and Engineering Laboratory, ETH Zürich, CH-8092 (Switzerland)

    2015-03-01

    We present Π4U,{sup 1} an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The framework accommodates scheduling of multiple physical model evaluations based on an adaptive load balancing library and shows excellent scalability. In addition to the software framework, we also provide guidelines as to the applicability and efficiency of Bayesian tools when applied to computationally demanding physical models. Theoretical and computational developments are demonstrated with applications drawn from molecular dynamics, structural dynamics and granular flow.

  12. Heterogeneous Gpu&Cpu Cluster For High Performance Computing In Cryptography

    Directory of Open Access Journals (Sweden)

    Michał Marks

    2012-01-01

    Full Text Available This paper addresses issues associated with distributed computing systems andthe application of mixed GPU&CPU technology to data encryption and decryptionalgorithms. We describe a heterogenous cluster HGCC formed by twotypes of nodes: Intel processor with NVIDIA graphics processing unit and AMDprocessor with AMD graphics processing unit (formerly ATI, and a novel softwareframework that hides the heterogeneity of our cluster and provides toolsfor solving complex scientific and engineering problems. Finally, we present theresults of numerical experiments. The considered case study is concerned withparallel implementations of selected cryptanalysis algorithms. The main goal ofthe paper is to show the wide applicability of the GPU&CPU technology tolarge scale computation and data processing.

  13. 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.

  14. High performance computing, supercomputing, náročné počítání

    Czech Academy of Sciences Publication Activity Database

    Okrouhlík, Miloslav

    2003-01-01

    Roč. 10, č. 5 (2003), s. 429-438 ISSN 1210-2717 R&D Projects: GA ČR GA101/02/0072 Institutional research plan: CEZ:AV0Z2076919 Keywords : high performance computing * vector and parallel computers * programing tools for parellelization Subject RIV: BI - Acoustics

  15. A High Performance Frequency Standard and Distribution System for Cassini Ka-Band Experiment

    National Research Council Canada - National Science Library

    Wang, R. T; Calhoun, M. D; Kirk, A; Diener, W. A; Dick, G. J; Tjoelker, R. L

    2005-01-01

    ...), and 10 Kelvin Cryocooled Sapphire Oscillator (10K CSO) and frequency-lock-loop, are integrated to achieve the very high performance, ground based frequency reference at a remote antenna site located 16 km from the hydrogen maser...

  16. High-performance floating-point image computing workstation for medical applications

    Science.gov (United States)

    Mills, Karl S.; Wong, Gilman K.; Kim, Yongmin

    1990-07-01

    The medical imaging field relies increasingly on imaging and graphics techniques in diverse applications with needs similar to (or more stringent than) those of the military, industrial and scientific communities. However, most image processing and graphics systems available for use in medical imaging today are either expensive, specialized, or in most cases both. High performance imaging and graphics workstations which can provide real-time results for a number of applications, while maintaining affordability and flexibility, can facilitate the application of digital image computing techniques in many different areas. This paper describes the hardware and software architecture of a medium-cost floating-point image processing and display subsystem for the NeXT computer, and its applications as a medical imaging workstation. Medical imaging applications of the workstation include use in a Picture Archiving and Communications System (PACS), in multimodal image processing and 3-D graphics workstation for a broad range of imaging modalities, and as an electronic alternator utilizing its multiple monitor display capability and large and fast frame buffer. The subsystem provides a 2048 x 2048 x 32-bit frame buffer (16 Mbytes of image storage) and supports both 8-bit gray scale and 32-bit true color images. When used to display 8-bit gray scale images, up to four different 256-color palettes may be used for each of four 2K x 2K x 8-bit image frames. Three of these image frames can be used simultaneously to provide pixel selectable region of interest display. A 1280 x 1024 pixel screen with 1: 1 aspect ratio can be windowed into the frame buffer for display of any portion of the processed image or images. In addition, the system provides hardware support for integer zoom and an 82-color cursor. This subsystem is implemented on an add-in board occupying a single slot in the NeXT computer. Up to three boards may be added to the NeXT for multiple display capability (e

  17. Leveraging High Performance Computing for Managing Large and Evolving Data Collections

    Directory of Open Access Journals (Sweden)

    Ritu Arora

    2014-10-01

    Full Text Available The process of developing a digital collection in the context of a research project often involves a pipeline pattern during which data growth, data types, and data authenticity need to be assessed iteratively in relation to the different research steps and in the interest of archiving. Throughout a project’s lifecycle curators organize newly generated data while cleaning and integrating legacy data when it exists, and deciding what data will be preserved for the long term. Although these actions should be part of a well-oiled data management workflow, there are practical challenges in doing so if the collection is very large and heterogeneous, or is accessed by several researchers contemporaneously. There is a need for data management solutions that can help curators with efficient and on-demand analyses of their collection so that they remain well-informed about its evolving characteristics. In this paper, we describe our efforts towards developing a workflow to leverage open science High Performance Computing (HPC resources for routinely and efficiently conducting data management tasks on large collections. We demonstrate that HPC resources and techniques can significantly reduce the time for accomplishing critical data management tasks, and enable a dynamic archiving throughout the research process. We use a large archaeological data collection with a long and complex formation history as our test case. We share our experiences in adopting open science HPC resources for large-scale data management, which entails understanding usage of the open source HPC environment and training users. These experiences can be generalized to meet the needs of other data curators working with large collections.

  18. High performance communication by people with paralysis using an intracortical brain-computer interface

    Science.gov (United States)

    Pandarinath, Chethan; Nuyujukian, Paul; Blabe, Christine H; Sorice, Brittany L; Saab, Jad; Willett, Francis R; Hochberg, Leigh R

    2017-01-01

    Brain-computer interfaces (BCIs) have the potential to restore communication for people with tetraplegia and anarthria by translating neural activity into control signals for assistive communication devices. While previous pre-clinical and clinical studies have demonstrated promising proofs-of-concept (Serruya et al., 2002; Simeral et al., 2011; Bacher et al., 2015; Nuyujukian et al., 2015; Aflalo et al., 2015; Gilja et al., 2015; Jarosiewicz et al., 2015; Wolpaw et al., 1998; Hwang et al., 2012; Spüler et al., 2012; Leuthardt et al., 2004; Taylor et al., 2002; Schalk et al., 2008; Moran, 2010; Brunner et al., 2011; Wang et al., 2013; Townsend and Platsko, 2016; Vansteensel et al., 2016; Nuyujukian et al., 2016; Carmena et al., 2003; Musallam et al., 2004; Santhanam et al., 2006; Hochberg et al., 2006; Ganguly et al., 2011; O’Doherty et al., 2011; Gilja et al., 2012), the performance of human clinical BCI systems is not yet high enough to support widespread adoption by people with physical limitations of speech. Here we report a high-performance intracortical BCI (iBCI) for communication, which was tested by three clinical trial participants with paralysis. The system leveraged advances in decoder design developed in prior pre-clinical and clinical studies (Gilja et al., 2015; Kao et al., 2016; Gilja et al., 2012). For all three participants, performance exceeded previous iBCIs (Bacher et al., 2015; Jarosiewicz et al., 2015) as measured by typing rate (by a factor of 1.4–4.2) and information throughput (by a factor of 2.2–4.0). This high level of performance demonstrates the potential utility of iBCIs as powerful assistive communication devices for people with limited motor function. Clinical Trial No: NCT00912041 DOI: http://dx.doi.org/10.7554/eLife.18554.001 PMID:28220753

  19. LIAR -- A computer program for the modeling and simulation of high performance linacs

    International Nuclear Information System (INIS)

    Assmann, R.; Adolphsen, C.; Bane, K.; Emma, P.; Raubenheimer, T.; Siemann, R.; Thompson, K.; Zimmermann, F.

    1997-04-01

    The computer program LIAR (LInear Accelerator Research Code) is a numerical modeling and simulation tool for high performance linacs. Amongst others, it addresses the needs of state-of-the-art linear colliders where low emittance, high-intensity beams must be accelerated to energies in the 0.05-1 TeV range. LIAR is designed to be used for a variety of different projects. LIAR allows the study of single- and multi-particle beam dynamics in linear accelerators. It calculates emittance dilutions due to wakefield deflections, linear and non-linear dispersion and chromatic effects in the presence of multiple accelerator imperfections. Both single-bunch and multi-bunch beams can be simulated. Several basic and advanced optimization schemes are implemented. Present limitations arise from the incomplete treatment of bending magnets and sextupoles. A major objective of the LIAR project is to provide an open programming platform for the accelerator physics community. Due to its design, LIAR allows straight-forward access to its internal FORTRAN data structures. The program can easily be extended and its interactive command language ensures maximum ease of use. Presently, versions of LIAR are compiled for UNIX and MS Windows operating systems. An interface for the graphical visualization of results is provided. Scientific graphs can be saved in the PS and EPS file formats. In addition a Mathematica interface has been developed. LIAR now contains more than 40,000 lines of source code in more than 130 subroutines. This report describes the theoretical basis of the program, provides a reference for existing features and explains how to add further commands. The LIAR home page and the ONLINE version of this manual can be accessed under: http://www.slac.stanford.edu/grp/arb/rwa/liar.htm

  20. High performance computation of landscape genomic models including local indicators of spatial association.

    Science.gov (United States)

    Stucki, S; Orozco-terWengel, P; Forester, B R; Duruz, S; Colli, L; Masembe, C; Negrini, R; Landguth, E; Jones, M R; Bruford, M W; Taberlet, P; Joost, S

    2017-09-01

    With the increasing availability of both molecular and topo-climatic data, the main challenges facing landscape genomics - that is the combination of landscape ecology with population genomics - include processing large numbers of models and distinguishing between selection and demographic processes (e.g. population structure). Several methods address the latter, either by estimating a null model of population history or by simultaneously inferring environmental and demographic effects. Here we present samβada, an approach designed to study signatures of local adaptation, with special emphasis on high performance computing of large-scale genetic and environmental data sets. samβada identifies candidate loci using genotype-environment associations while also incorporating multivariate analyses to assess the effect of many environmental predictor variables. This enables the inclusion of explanatory variables representing population structure into the models to lower the occurrences of spurious genotype-environment associations. In addition, samβada calculates local indicators of spatial association for candidate loci to provide information on whether similar genotypes tend to cluster in space, which constitutes a useful indication of the possible kinship between individuals. To test the usefulness of this approach, we carried out a simulation study and analysed a data set from Ugandan cattle to detect signatures of local adaptation with samβada, bayenv, lfmm and an F ST outlier method (FDIST approach in arlequin) and compare their results. samβada - an open source software for Windows, Linux and Mac OS X available at http://lasig.epfl.ch/sambada - outperforms other approaches and better suits whole-genome sequence data processing. © 2016 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.

  1. Statistical physics of fracture: scientific discovery through high-performance computing

    International Nuclear Information System (INIS)

    Kumar, Phani; Nukala, V V; Simunovic, Srdan; Mills, Richard T

    2006-01-01

    The paper presents the state-of-the-art algorithmic developments for simulating the fracture of disordered quasi-brittle materials using discrete lattice systems. Large scale simulations are often required to obtain accurate scaling laws; however, due to computational complexity, the simulations using the traditional algorithms were limited to small system sizes. We have developed two algorithms: a multiple sparse Cholesky downdating scheme for simulating 2D random fuse model systems, and a block-circulant preconditioner for simulating 2D random fuse model systems. Using these algorithms, we were able to simulate fracture of largest ever lattice system sizes (L = 1024 in 2D, and L = 64 in 3D) with extensive statistical sampling. Our recent simulations on 1024 processors of Cray-XT3 and IBM Blue-Gene/L have further enabled us to explore fracture of 3D lattice systems of size L = 200, which is a significant computational achievement. These largest ever numerical simulations have enhanced our understanding of physics of fracture; in particular, we analyze damage localization and its deviation from percolation behavior, scaling laws for damage density, universality of fracture strength distribution, size effect on the mean fracture strength, and finally the scaling of crack surface roughness

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

    Energy Technology Data Exchange (ETDEWEB)

    Karthik, Rajasekar [ORNL

    2014-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-10-15

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

  4. Operational mesoscale atmospheric dispersion prediction using high performance parallel computing cluster for emergency response

    International Nuclear Information System (INIS)

    Srinivas, C.V.; Venkatesan, R.; Muralidharan, N.V.; Das, Someshwar; Dass, Hari; Eswara Kumar, P.

    2005-08-01

    An operational atmospheric dispersion prediction system is implemented on a cluster super computer for 'Online Emergency Response' for Kalpakkam nuclear site. The numerical system constitutes a parallel version of a nested grid meso-scale meteorological model MM5 coupled to a random walk particle dispersion model FLEXPART. The system provides 48 hour forecast of the local weather and radioactive plume dispersion due to hypothetical air borne releases in a range of 100 km around the site. The parallel code was implemented on different cluster configurations like distributed and shared memory systems. Results of MM5 run time performance for 1-day prediction are reported on all the machines available for testing. A reduction of 5 times in runtime is achieved using 9 dual Xeon nodes (18 physical/36 logical processors) compared to a single node sequential run. Based on the above run time results a cluster computer facility with 9-node Dual Xeon is commissioned at IGCAR for model operation. The run time of a triple nested domain MM5 is about 4 h for 24 h forecast. The system has been operated continuously for a few months and results were ported on the IMSc home page. Initial and periodic boundary condition data for MM5 are provided by NCMRWF, New Delhi. An alternative source is found to be NCEP, USA. These two sources provide the input data to the operational models at different spatial and temporal resolutions and using different assimilation methods. A comparative study on the results of forecast is presented using these two data sources for present operational use. Slight improvement is noticed in rainfall, winds, geopotential heights and the vertical atmospheric structure while using NCEP data probably because of its high spatial and temporal resolution. (author)

  5. Simulation and high performance computing-Building a predictive capability for fusion

    International Nuclear Information System (INIS)

    Strand, P.I.; Coelho, R.; Coster, D.; Eriksson, L.-G.; Imbeaux, F.; Guillerminet, Bernard

    2010-01-01

    The Integrated Tokamak Modelling Task Force (ITM-TF) is developing an infrastructure where the validation needs, as being formulated in terms of multi-device data access and detailed physics comparisons aiming for inclusion of synthetic diagnostics in the simulation chain, are key components. As the activity and the modelling tools are aimed for general use, although focused on ITER plasmas, a device independent approach to data transport and a standardized approach to data management (data structures, naming, and access) is being developed in order to allow cross-validation between different fusion devices using a single toolset. Extensive work has already gone into, and is continuing to go into, the development of standardized descriptions of the data (Consistent Physical Objects). The longer term aim is a complete simulation platform which is expected to last and be extended in different ways for the coming 30 years. The technical underpinning is therefore of vital importance. In particular the platform needs to be extensible and open-ended to be able to take full advantage of not only today's most advanced technologies but also be able to marshal future developments. As a full level comprehensive prediction of ITER physics rapidly becomes expensive in terms of computing resources, the simulation framework needs to be able to use both grid and HPC computing facilities. Hence data access and code coupling technologies are required to be available for a heterogeneous, possibly distributed, environment. The developments in this area are pursued in a separate project-EUFORIA (EU Fusion for ITER Applications) which is providing about 15 professional person year (ppy) per annum from 14 different institutes. The range and size of the activity is not only technically challenging but is providing some unique management challenges in that a large and geographically distributed team (a truly pan-European set of researchers) need to be coordinated on a fairly detailed

  6. Implementing a High Performance Work Place in the Distribution and Logistics Industry: Recommendations for Leadership & Team Member Development

    Science.gov (United States)

    McCann, Laura Harding

    2012-01-01

    Leadership development and employee engagement are two elements critical to the success of organizations. In response to growth opportunities, our Distribution and Logistics company set on a course to implement High Performance Work Place to meet the leadership and employee engagement needs, and to find methods for improving work processes. This…

  7. High performance computing and quantum trajectory method in CPU and GPU systems

    International Nuclear Information System (INIS)

    Wiśniewska, Joanna; Sawerwain, Marek; Leoński, Wiesław

    2015-01-01

    Nowadays, a dynamic progress in computational techniques allows for development of various methods, which offer significant speed-up of computations, especially those related to the problems of quantum optics and quantum computing. In this work, we propose computational solutions which re-implement the quantum trajectory method (QTM) algorithm in modern parallel computation environments in which multi-core CPUs and modern many-core GPUs can be used. In consequence, new computational routines are developed in more effective way than those applied in other commonly used packages, such as Quantum Optics Toolbox (QOT) for Matlab or QuTIP for Python

  8. A high-performance model for shallow-water simulations in distributed and heterogeneous architectures

    Science.gov (United States)

    Conde, Daniel; Canelas, Ricardo B.; Ferreira, Rui M. L.

    2017-04-01

    One of the most common challenges in hydrodynamic modelling is the trade off one must make between highly resolved simulations and the time required for their computation. In the particular case of urban floods, modelers are often forced to simplify the complex geometries of the problem, or to implicitly include some of its hydrodynamic effects, due to the typically very large spatial scales involved and limited computational resources. At CEris - Instituto Superior Técnico, Universidade de Lisboa - the STAV-2D shallow-water model, particularly suited for strong transient flows in complex and dynamic geometries, has been under development for the past recent years (Canelas et al., 2013 & Conde et al., 2013). The model is based on an explicit, first-order 2DH finite-volume discretization scheme for unstructured triangular meshes, in which a flux-splitting technique is paired with a reviewed Roe-Riemann solver, yielding a model applicable to discontinuous flows over time-evolving geometries. STAV-2D features solid transport in both Euleran and Lagrangian forms, with the first aiming at describing the transport of fine natural sediments and the latter aimed at large individual debris. The model has been validated with theoretical solutions and laboratory experiments (Canelas et al., 2013 & Conde et al., 2015). This work presents our most recent effort in STAV-2D: the re-design of the code in a modern Object-Oriented parallel framework for heterogeneous computations in CPUs and GPUs. The programming language of choice for this re-design was C++, due to its wide support of established and emerging parallel programming interfaces. The current implementation of STAV-2D provides two different levels of parallel granularity: inter-node and intra-node. Inter-node parallelism is achieved by distributing a simulation across a set of worker nodes, with communication between nodes being explicitly managed through MPI. At this level, the main difficulty is associated with the

  9. WinSCP for Windows File Transfers | High-Performance Computing | NREL

    Science.gov (United States)

    WinSCP for Windows File Transfers WinSCP for Windows File Transfers WinSCP for can used to securely transfer files between your local computer running Microsoft Windows and a remote computer running Linux

  10. The computer program LIAR for the simulation and modeling of high performance linacs

    International Nuclear Information System (INIS)

    Assmann, R.; Adolphsen, C.; Bane, K.; Emma, P.; Raubenheimer, T.O.; Siemann, R.; Thompson, K.; Zimmermann, F.

    1997-07-01

    High performance linear accelerators are the central components of the proposed next generation of linear colliders. They must provide acceleration of up to 750 GeV per beam while maintaining small normalized emittances. Standard simulation programs, mainly developed for storage rings, did not meet the specific requirements for high performance linacs with high bunch charges and strong wakefields. The authors present the program. LIAR (LInear Accelerator Research code) that includes single and multi-bunch wakefield effects, a 6D coupled beam description, specific optimization algorithms and other advanced features. LIAR has been applied to and checked against the existing Stanford Linear Collider (SLC), the linacs of the proposed Next Linear Collider (NLC) and the proposed Linac Coherent Light Source (LCLS) at SLAC. Its modular structure allows easy extension for different purposes. The program is available for UNIX workstations and Windows PC's

  11. Energy Efficiency Evaluation and Benchmarking of AFRL’s Condor High Performance Computer

    Science.gov (United States)

    2011-08-01

    PlayStation 3 nodes executing the HPL benchmark. When idle, the two PS3s consume 188.49 W on average. At peak HPL performance, the nodes draw an average of...AUG 2011 2. REPORT TYPE CONFERENCE PAPER (Post Print) 3. DATES COVERED (From - To) JAN 2011 – JUN 2011 4 . TITLE AND SUBTITLE ENERGY EFFICIENCY...the High Performance LINPACK (HPL) benchmark while also measuring the energy consumed to achieve such performance. Supercomputers are ranked by

  12. A high-performance data acquisition system for computer-based multichannel analyzer

    International Nuclear Information System (INIS)

    Zhou Xinzhi; Bai Rongsheng; Wen Liangbi; Huang Yanwen

    1996-01-01

    A high-performance data acquisition system applied in the multichannel analyzer is designed with single-chip microcomputer system. The paper proposes the principle and the method of realizing the simultaneous data acquisition, the data pre-processing, and the fast bidirectional data transfer by means of direct memory access based on dual-port RAM as well. The measurement for dead or live time of ADC system can also be implemented efficiently by using it

  13. 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.

  14. Distributed computing for global health

    CERN Multimedia

    CERN. Geneva; Schwede, Torsten; Moore, Celia; Smith, Thomas E; Williams, Brian; Grey, François

    2005-01-01

    Distributed computing harnesses the power of thousands of computers within organisations or over the Internet. In order to tackle global health problems, several groups of researchers have begun to use this approach to exceed by far the computing power of a single lab. This event illustrates how companies, research institutes and the general public are contributing their computing power to these efforts, and what impact this may have on a range of world health issues. Grids for neglected diseases Vincent Breton, CNRS/EGEE This talk introduces the topic of distributed computing, explaining the similarities and differences between Grid computing, volunteer computing and supercomputing, and outlines the potential of Grid computing for tackling neglected diseases where there is little economic incentive for private R&D efforts. Recent results on malaria drug design using the Grid infrastructure of the EU-funded EGEE project, which is coordinated by CERN and involves 70 partners in Europe, the US and Russi...

  15. FLASHRAD: A 3D Rad Hard Memory Module For High Performance Space Computers, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The computing capabilities of onboard spacecraft are a major limiting factor for accomplishing many classes of future missions. Although technology development...

  16. Very High-Performance Embedded Computing Will Allow Ambitious Space Science Investigation

    National Research Council Canada - National Science Library

    Pignol, Michel

    2005-01-01

    .... developed on radiation tolerant technologies. Unfortunately, the microprocessors today available on such technologies have the computing throughput which was available about 10 years ago on the commercial market...

  17. High Performance Computing and Storage Requirements for Biological and Environmental Research Target 2017

    Energy Technology Data Exchange (ETDEWEB)

    Gerber, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Wasserman, Harvey [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)

    2013-05-01

    The National Energy Research Scientific Computing Center (NERSC) is the primary computing center for the DOE Office of Science, serving approximately 4,500 users working on some 650 projects that involve nearly 600 codes in a wide variety of scientific disciplines. In addition to large-­scale computing and storage resources NERSC provides support and expertise that help scientists make efficient use of its systems. The latest review revealed several key requirements, in addition to achieving its goal of characterizing BER computing and storage needs.

  18. Tunable Laser for High-Performance, Low-Cost Distributed Sensing Platform, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed effort will establish technical feasibility of an approach to optimizing a low-cost, fast-sweeping tunable laser for distributed sensing. Multiple...

  19. FY 2000 Blue Book: High Performance Computing and Communications: Information Technology Frontiers for a New Millennium

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — As we near the dawn of a new millennium, advances made possible by computing, information, and communications research and development R and D ? once barely...

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

    Data.gov (United States)

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

  1. Topic 14+16: High-performance and scientific applications and extreme-scale computing (Introduction)

    KAUST Repository

    Downes, Turlough P.; Roller, Sabine P.; Seitsonen, Ari Paavo; Valcke, Sophie; Keyes, David E.; Sawley, Marie Christine; Schulthess, Thomas C.; Shalf, John M.

    2013-01-01

    and algorithms to address the varied, complex and increasing challenges of modern research throughout both the "hard" and "soft" sciences. This necessitates being able to use large numbers of compute nodes, many of which are equipped with accelerators

  2. JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing.

    Directory of Open Access Journals (Sweden)

    David K Brown

    Full Text Available Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS, a workflow management system and web interface for high performance computing (HPC. JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS.

  3. JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing.

    Science.gov (United States)

    Brown, David K; Penkler, David L; Musyoka, Thommas M; Bishop, Özlem Tastan

    2015-01-01

    Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS.

  4. JMS: An Open Source Workflow Management System and Web-Based Cluster Front-End for High Performance Computing

    Science.gov (United States)

    Brown, David K.; Penkler, David L.; Musyoka, Thommas M.; Bishop, Özlem Tastan

    2015-01-01

    Complex computational pipelines are becoming a staple of modern scientific research. Often these pipelines are resource intensive and require days of computing time. In such cases, it makes sense to run them over high performance computing (HPC) clusters where they can take advantage of the aggregated resources of many powerful computers. In addition to this, researchers often want to integrate their workflows into their own web servers. In these cases, software is needed to manage the submission of jobs from the web interface to the cluster and then return the results once the job has finished executing. We have developed the Job Management System (JMS), a workflow management system and web interface for high performance computing (HPC). JMS provides users with a user-friendly web interface for creating complex workflows with multiple stages. It integrates this workflow functionality with the resource manager, a tool that is used to control and manage batch jobs on HPC clusters. As such, JMS combines workflow management functionality with cluster administration functionality. In addition, JMS provides developer tools including a code editor and the ability to version tools and scripts. JMS can be used by researchers from any field to build and run complex computational pipelines and provides functionality to include these pipelines in external interfaces. JMS is currently being used to house a number of bioinformatics pipelines at the Research Unit in Bioinformatics (RUBi) at Rhodes University. JMS is an open-source project and is freely available at https://github.com/RUBi-ZA/JMS. PMID:26280450

  5. A Distributed Computational Infrastructure for Science and Education

    Directory of Open Access Journals (Sweden)

    Rustam K. Bazarov

    2014-06-01

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

  6. Money for Research, Not for Energy Bills: Finding Energy and Cost Savings in High Performance Computer Facility Designs

    Energy Technology Data Exchange (ETDEWEB)

    Drewmark Communications; Sartor, Dale; Wilson, Mark

    2010-07-01

    High-performance computing facilities in the United States consume an enormous amount of electricity, cutting into research budgets and challenging public- and private-sector efforts to reduce energy consumption and meet environmental goals. However, these facilities can greatly reduce their energy demand through energy-efficient design of the facility itself. Using a case study of a facility under design, this article discusses strategies and technologies that can be used to help achieve energy reductions.

  7. High-Bandwidth Tactical-Network Data Analysis in a High-Performance-Computing (HPC) Environment: Packet-Level Analysis

    Science.gov (United States)

    2015-09-01

    individual fragments using the hash-based method. In general, fragments 6 appear in order and relatively close to each other in the file. A fragment...data product derived from the data model is shown in Fig. 5, a Google Earth12 Keyhole Markup Language (KML) file. This product includes aggregate...System BLOb binary large object FPGA field-programmable gate array HPC high-performance computing IP Internet Protocol KML Keyhole Markup Language

  8. Implementation of the Principal Component Analysis onto High-Performance Computer Facilities for Hyperspectral Dimensionality Reduction: Results and Comparisons

    Directory of Open Access Journals (Sweden)

    Ernestina Martel

    2018-06-01

    Full Text Available Dimensionality reduction represents a critical preprocessing step in order to increase the efficiency and the performance of many hyperspectral imaging algorithms. However, dimensionality reduction algorithms, such as the Principal Component Analysis (PCA, suffer from their computationally demanding nature, becoming advisable for their implementation onto high-performance computer architectures for applications under strict latency constraints. This work presents the implementation of the PCA algorithm onto two different high-performance devices, namely, an NVIDIA Graphics Processing Unit (GPU and a Kalray manycore, uncovering a highly valuable set of tips and tricks in order to take full advantage of the inherent parallelism of these high-performance computing platforms, and hence, reducing the time that is required to process a given hyperspectral image. Moreover, the achieved results obtained with different hyperspectral images have been compared with the ones that were obtained with a field programmable gate array (FPGA-based implementation of the PCA algorithm that has been recently published, providing, for the first time in the literature, a comprehensive analysis in order to highlight the pros and cons of each option.

  9. Implementation of the Two-Point Angular Correlation Function on a High-Performance Reconfigurable Computer

    Directory of Open Access Journals (Sweden)

    Volodymyr V. Kindratenko

    2009-01-01

    Full Text Available We present a parallel implementation of an algorithm for calculating the two-point angular correlation function as applied in the field of computational cosmology. The algorithm has been specifically developed for a reconfigurable computer. Our implementation utilizes a microprocessor and two reconfigurable processors on a dual-MAP SRC-6 system. The two reconfigurable processors are used as two application-specific co-processors. Two independent computational kernels are simultaneously executed on the reconfigurable processors while data pre-fetching from disk and initial data pre-processing are executed on the microprocessor. The overall end-to-end algorithm execution speedup achieved by this implementation is over 90× as compared to a sequential implementation of the algorithm executed on a single 2.8 GHz Intel Xeon microprocessor.

  10. Computer-Aided Chemical Product Design Framework: Design of High Performance and Environmentally Friendly Refrigerants

    DEFF Research Database (Denmark)

    Cignitti, Stefano; Zhang, Lei; Gani, Rafiqul

    properties and needs should carefully be selected for a given heat pump cycle to ensure that an optimum refrigerant is found? How can cycle performance and environmental criteria be integrated at the product design stage and not in post-design analysis? Computer-aided product design methods enable...... the possibility of designing novel molecules, mixtures and blends, such as refrigerants through a systematic framework (Cignitti et al., 2015; Yunus et al., 2014). In this presentation a computer-aided framework is presented for chemical product design through mathematical optimization. Here, molecules, mixtures...... and blends, are systematically designed through a decomposition based solution method. Given a problem definition, computer-aided molecular design (CAMD) problem is defined, which is formulated into a mixed integer nonlinear program (MINLP). The decomposed solution method then sequentially divides the MINLP...

  11. A Protocol for Provably Secure Authentication of a Tiny Entity to a High Performance Computing One

    Directory of Open Access Journals (Sweden)

    Siniša Tomović

    2016-01-01

    Full Text Available The problem of developing authentication protocols dedicated to a specific scenario where an entity with limited computational capabilities should prove the identity to a computationally powerful Verifier is addressed. An authentication protocol suitable for the considered scenario which jointly employs the learning parity with noise (LPN problem and a paradigm of random selection is proposed. It is shown that the proposed protocol is secure against active attacking scenarios and so called GRS man-in-the-middle (MIM attacking scenarios. In comparison with the related previously reported authentication protocols the proposed one provides reduction of the implementation complexity and at least the same level of the cryptographic security.

  12. High-performance secure multi-party computation for data mining applications

    DEFF Research Database (Denmark)

    Bogdanov, Dan; Niitsoo, Margus; Toft, Tomas

    2012-01-01

    Secure multi-party computation (MPC) is a technique well suited for privacy-preserving data mining. Even with the recent progress in two-party computation techniques such as fully homomorphic encryption, general MPC remains relevant as it has shown promising performance metrics in real...... operations such as multiplication and comparison. Secondly, the confidential processing of financial data requires the use of more complex primitives, including a secure division operation. This paper describes new protocols in the Sharemind model for secure multiplication, share conversion, equality, bit...

  13. The Use of High Performance Computing (HPC) to Strengthen the Development of Army Systems

    Science.gov (United States)

    2011-11-01

    changes in what the warfighter wants – in the middle of an acquisition cycle such changes create havoc in terms of delays, recycling of the research...A little bit later the first personal computers (PCs) came on the market, mostly as curiosities . The operating systems were either ms-dos or cp/m

  14. A High Performance Computing Framework for Physics-based Modeling and Simulation of Military Ground Vehicles

    Science.gov (United States)

    2011-03-25

    cluster. The co-processing idea is the enabler of the heterogeneous computing concept advertised recently as the paradigm capable of delivering exascale ...Petascale to Exascale : Extending Intel’s HPC Commitment: http://download.intel.com/pressroom/archive/reference/ISC_2010_Skaugen_keynote.pdf in

  15. Achieving high performance in numerical computations on RISC workstations and parallel systems

    Energy Technology Data Exchange (ETDEWEB)

    Goedecker, S. [Max-Planck Inst. for Solid State Research, Stuttgart (Germany); Hoisie, A. [Los Alamos National Lab., NM (United States)

    1997-08-20

    The nominal peak speeds of both serial and parallel computers is raising rapidly. At the same time however it is becoming increasingly difficult to get out a significant fraction of this high peak speed from modern computer architectures. In this tutorial the authors give the scientists and engineers involved in numerically demanding calculations and simulations the necessary basic knowledge to write reasonably efficient programs. The basic principles are rather simple and the possible rewards large. Writing a program by taking into account optimization techniques related to the computer architecture can significantly speedup your program, often by factors of 10--100. As such, optimizing a program can for instance be a much better solution than buying a faster computer. If a few basic optimization principles are applied during program development, the additional time needed for obtaining an efficient program is practically negligible. In-depth optimization is usually only needed for a few subroutines or kernels and the effort involved is therefore also acceptable.

  16. High Performance Parallel Processing Project: Industrial computing initiative. Progress reports for fiscal year 1995

    Energy Technology Data Exchange (ETDEWEB)

    Koniges, A.

    1996-02-09

    This project is a package of 11 individual CRADA`s plus hardware. This innovative project established a three-year multi-party collaboration that is significantly accelerating the availability of commercial massively parallel processing computing software technology to U.S. government, academic, and industrial end-users. This report contains individual presentations from nine principal investigators along with overall program information.

  17. Department of Defense High Performance Computing Modernization Program. 2008 Annual Report

    Science.gov (United States)

    2009-04-01

    Environment, Doug Post and the CREATE Team (K. Hill, D. van Veldhuizen , G. Zelinski, AFRL; S. Arevalo, T. Blacker, D. Fisher, P. Genalis, A. Harris, M...RF Antenna Group, David van Veldhuizen Computational Research and Engineering Acquisition Tools and Environments (CREATE), David Fisher and

  18. High-performance parallel computing in the classroom using the public goods game as an example

    Science.gov (United States)

    Perc, Matjaž

    2017-07-01

    The use of computers in statistical physics is common because the sheer number of equations that describe the behaviour of an entire system particle by particle often makes it impossible to solve them exactly. Monte Carlo methods form a particularly important class of numerical methods for solving problems in statistical physics. Although these methods are simple in principle, their proper use requires a good command of statistical mechanics, as well as considerable computational resources. The aim of this paper is to demonstrate how the usage of widely accessible graphics cards on personal computers can elevate the computing power in Monte Carlo simulations by orders of magnitude, thus allowing live classroom demonstration of phenomena that would otherwise be out of reach. As an example, we use the public goods game on a square lattice where two strategies compete for common resources in a social dilemma situation. We show that the second-order phase transition to an absorbing phase in the system belongs to the directed percolation universality class, and we compare the time needed to arrive at this result by means of the main processor and by means of a suitable graphics card. Parallel computing on graphics processing units has been developed actively during the last decade, to the point where today the learning curve for entry is anything but steep for those familiar with programming. The subject is thus ripe for inclusion in graduate and advanced undergraduate curricula, and we hope that this paper will facilitate this process in the realm of physics education. To that end, we provide a documented source code for an easy reproduction of presented results and for further development of Monte Carlo simulations of similar systems.

  19. High performance organic distributed Bragg reflector lasers fabricated by dot matrix holography.

    Science.gov (United States)

    Wan, Wenqiang; Huang, Wenbin; Pu, Donglin; Qiao, Wen; Ye, Yan; Wei, Guojun; Fang, Zongbao; Zhou, Xiaohong; Chen, Linsen

    2015-12-14

    We report distributed Bragg reflector (DBR) polymer lasers fabricated using dot matrix holography. Pairs of distributed Bragg reflector mirrors with variable mirror separations are fabricated and a novel energy transfer blend consisting of a blue-emitting conjugated polymer and a red-emitting one is spin-coated onto the patterned substrate to complete the device. Under optical pumping, the device emits sing-mode lasing around 622 nm with a bandwidth of 0.41 nm. The working threshold is as low as 13.5 μJ/cm² (~1.68 kW/cm²) and the measured slope efficiency reaches 5.2%. The distributed feedback (DFB) cavity and the DBR cavity resonate at the same lasing wavelength while the DFB laser shows a much higher threshold. We further show that flexible DBR lasers can be conveniently fabricated through the UV-imprinting technique by using the patterned silica substrate as the mold. Dot matrix holography represents a versatile approach to control the number, the size, the location and the orientation of DBR mirrors, thus providing great flexibility in designing DBR lasers.

  20. Distributed GPU Computing in GIScience

    Science.gov (United States)

    Jiang, Y.; Yang, C.; Huang, Q.; Li, J.; Sun, M.

    2013-12-01

    Geoscientists strived to discover potential principles and patterns hidden inside ever-growing Big Data for scientific discoveries. To better achieve this objective, more capable computing resources are required to process, analyze and visualize Big Data (Ferreira et al., 2003; Li et al., 2013). Current CPU-based computing techniques cannot promptly meet the computing challenges caused by increasing amount of datasets from different domains, such as social media, earth observation, environmental sensing (Li et al., 2013). Meanwhile CPU-based computing resources structured as cluster or supercomputer is costly. In the past several years with GPU-based technology matured in both the capability and performance, GPU-based computing has emerged as a new computing paradigm. Compare to traditional computing microprocessor, the modern GPU, as a compelling alternative microprocessor, has outstanding high parallel processing capability with cost-effectiveness and efficiency(Owens et al., 2008), although it is initially designed for graphical rendering in visualization pipe. This presentation reports a distributed GPU computing framework for integrating GPU-based computing within distributed environment. Within this framework, 1) for each single computer, computing resources of both GPU-based and CPU-based can be fully utilized to improve the performance of visualizing and processing Big Data; 2) within a network environment, a variety of computers can be used to build up a virtual super computer to support CPU-based and GPU-based computing in distributed computing environment; 3) GPUs, as a specific graphic targeted device, are used to greatly improve the rendering efficiency in distributed geo-visualization, especially for 3D/4D visualization. Key words: Geovisualization, GIScience, Spatiotemporal Studies Reference : 1. Ferreira de Oliveira, M. C., & Levkowitz, H. (2003). From visual data exploration to visual data mining: A survey. Visualization and Computer Graphics, IEEE

  1. Energy efficient distributed computing systems

    CERN Document Server

    Lee, Young-Choon

    2012-01-01

    The energy consumption issue in distributed computing systems raises various monetary, environmental and system performance concerns. Electricity consumption in the US doubled from 2000 to 2005.  From a financial and environmental standpoint, reducing the consumption of electricity is important, yet these reforms must not lead to performance degradation of the computing systems.  These contradicting constraints create a suite of complex problems that need to be resolved in order to lead to 'greener' distributed computing systems.  This book brings together a group of outsta

  2. Contributing to the design of run-time systems dedicated to high performance computing

    International Nuclear Information System (INIS)

    Perache, M.

    2006-10-01

    In the field of intensive scientific computing, the quest for performance has to face the increasing complexity of parallel architectures. Nowadays, these machines exhibit a deep memory hierarchy which complicates the design of efficient parallel applications. This thesis proposes a programming environment allowing to design efficient parallel programs on top of clusters of multi-processors. It features a programming model centered around collective communications and synchronizations, and provides load balancing facilities. The programming interface, named MPC, provides high level paradigms which are optimized according to the underlying architecture. The environment is fully functional and used within the CEA/DAM (TERANOVA) computing center. The evaluations presented in this document confirm the relevance of our approach. (author)

  3. LIAR: A COMPUTER PROGRAM FOR THE SIMULATION AND MODELING OF HIGH PERFORMANCE LINACS

    International Nuclear Information System (INIS)

    Adolphsen, Chris

    2003-01-01

    The computer program LIAR (''LInear Accelerator Research code'') is a numerical simulation and tracking program for linear colliders. The LIAR project was started at SLAC in August 1995 in order to provide a computing and simulation tool that specifically addresses the needs of high energy linear colliders. LIAR is designed to be used for a variety of different linear accelerators. It has been applied for and checked against the existing Stanford Linear Collider (SLC) as well as the linacs of the proposed Next Linear Collider (NLC) and the proposed Linac Coherent Light Source (LCLS). The program includes wakefield effects, a 4D coupled beam description, specific optimization algorithms and other advanced features. We describe the most important concepts and highlights of the program. After having presented the LIAR program at the LINAC96 and the PAC97 conferences, we do now introduce it to the European particle accelerator community

  4. Quo vadis: Hydrologic inverse analyses using high-performance computing and a D-Wave quantum annealer

    Science.gov (United States)

    O'Malley, D.; Vesselinov, V. V.

    2017-12-01

    Classical microprocessors have had a dramatic impact on hydrology for decades, due largely to the exponential growth in computing power predicted by Moore's law. However, this growth is not expected to continue indefinitely and has already begun to slow. Quantum computing is an emerging alternative to classical microprocessors. Here, we demonstrated cutting edge inverse model analyses utilizing some of the best available resources in both worlds: high-performance classical computing and a D-Wave quantum annealer. The classical high-performance computing resources are utilized to build an advanced numerical model that assimilates data from O(10^5) observations, including water levels, drawdowns, and contaminant concentrations. The developed model accurately reproduces the hydrologic conditions at a Los Alamos National Laboratory contamination site, and can be leveraged to inform decision-making about site remediation. We demonstrate the use of a D-Wave 2X quantum annealer to solve hydrologic inverse problems. This work can be seen as an early step in quantum-computational hydrology. We compare and contrast our results with an early inverse approach in classical-computational hydrology that is comparable to the approach we use with quantum annealing. Our results show that quantum annealing can be useful for identifying regions of high and low permeability within an aquifer. While the problems we consider are small-scale compared to the problems that can be solved with modern classical computers, they are large compared to the problems that could be solved with early classical CPUs. Further, the binary nature of the high/low permeability problem makes it well-suited to quantum annealing, but challenging for classical computers.

  5. AHPCRC (Army High Performance Computing Research Center) Bulletin. Volume 1, Issue 2

    Science.gov (United States)

    2011-01-01

    area and the researchers working on these projects. Also inside: news from the AHPCRC consortium partners at Morgan State University and the NASA ...Computing Research Center is provided by the supercomputing and research facilities at Stanford University and at the NASA Ames Research Center at...atomic and molecular level, he said. He noted that “every general would like to have” a Star Trek -like holodeck, where holographic avatars could

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

    Science.gov (United States)

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

    2018-05-01

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

  7. Air Force Science & Technology Issues & Opportunities Regarding High Performance Embedded Computing

    Science.gov (United States)

    2009-09-23

    price-performance advantage include: large scale simulations of neuromorphic computing models GOTCHA radar video SAR for wide area persistent...the handcuffs were not for me and that the military had so far got … Neuromorphic example: Robust recognition of occluded text Gotcha SAR PCID Image...Architecture 16 cores / chip 10 x 10 stacks / board50 chips / stack EDRAM AFPGA EDRAM AFPGA EDRAM AFPGA EDRAM AFPGA EDRAM AFPGA EDRAM AFPGA EDRAM AFPGA EDRAM

  8. High performance graphics processor based computed tomography reconstruction algorithms for nuclear and other large scale applications.

    Energy Technology Data Exchange (ETDEWEB)

    Jimenez, Edward S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Orr, Laurel J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Thompson, Kyle R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2013-09-01

    The goal of this work is to develop a fast computed tomography (CT) reconstruction algorithm based on graphics processing units (GPU) that achieves significant improvement over traditional central processing unit (CPU) based implementations. The main challenge in developing a CT algorithm that is capable of handling very large datasets is parallelizing the algorithm in such a way that data transfer does not hinder performance of the reconstruction algorithm. General Purpose Graphics Processing (GPGPU) is a new technology that the Science and Technology (S&T) community is starting to adopt in many fields where CPU-based computing is the norm. GPGPU programming requires a new approach to algorithm development that utilizes massively multi-threaded environments. Multi-threaded algorithms in general are difficult to optimize since performance bottlenecks occur that are non-existent in single-threaded algorithms such as memory latencies. If an efficient GPU-based CT reconstruction algorithm can be developed; computational times could be improved by a factor of 20. Additionally, cost benefits will be realized as commodity graphics hardware could potentially replace expensive supercomputers and high-end workstations. This project will take advantage of the CUDA programming environment and attempt to parallelize the task in such a way that multiple slices of the reconstruction volume are computed simultaneously. This work will also take advantage of the GPU memory by utilizing asynchronous memory transfers, GPU texture memory, and (when possible) pinned host memory so that the memory transfer bottleneck inherent to GPGPU is amortized. Additionally, this work will take advantage of GPU-specific hardware (i.e. fast texture memory, pixel-pipelines, hardware interpolators, and varying memory hierarchy) that will allow for additional performance improvements.

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

    Science.gov (United States)

    2018-01-01

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

  10. FPGA hardware acceleration for high performance neutron transport computation based on agent methodology - 318

    International Nuclear Information System (INIS)

    Shanjie, Xiao; Tatjana, Jevremovic

    2010-01-01

    The accurate, detailed and 3D neutron transport analysis for Gen-IV reactors is still time-consuming regardless of advanced computational hardware available in developed countries. This paper introduces a new concept in addressing the computational time while persevering the detailed and accurate modeling; a specifically designed FPGA co-processor accelerates robust AGENT methodology for complex reactor geometries. For the first time this approach is applied to accelerate the neutronics analysis. The AGENT methodology solves neutron transport equation using the method of characteristics. The AGENT methodology performance was carefully analyzed before the hardware design based on the FPGA co-processor was adopted. The most time-consuming kernel part is then transplanted into the FPGA co-processor. The FPGA co-processor is designed with data flow-driven non von-Neumann architecture and has much higher efficiency than the conventional computer architecture. Details of the FPGA co-processor design are introduced and the design is benchmarked using two different examples. The advanced chip architecture helps the FPGA co-processor obtaining more than 20 times speed up with its working frequency much lower than the CPU frequency. (authors)

  11. A high performance long-reach passive optical network with a novel excess bandwidth distribution scheme

    Science.gov (United States)

    Chao, I.-Fen; Zhang, Tsung-Min

    2015-06-01

    Long-reach passive optical networks (LR-PONs) have been considered to be promising solutions for future access networks. In this paper, we propose a distributed medium access control (MAC) scheme over an advantageous LR-PON network architecture that reroutes the control information from and back to all ONUs through an (N + 1) × (N + 1) star coupler (SC) deployed near the ONUs, thereby overwhelming the extremely long propagation delay problem in LR-PONs. In the network, the control slot is designed to contain all bandwidth requirements of all ONUs and is in-band time-division-multiplexed with a number of data slots within a cycle. In the proposed MAC scheme, a novel profit-weight-based dynamic bandwidth allocation (P-DBA) scheme is presented. The algorithm is designed to efficiently and fairly distribute the amount of excess bandwidth based on a profit value derived from the excess bandwidth usage of each ONU, which resolves the problems of previously reported DBA schemes that are either unfair or inefficient. The simulation results show that the proposed decentralized algorithms exhibit a nearly three-order-of-magnitude improvement in delay performance compared to the centralized algorithms over LR-PONs. Moreover, the newly proposed P-DBA scheme guarantees low delay performance and fairness even when under attack by the malevolent ONU irrespective of traffic loads and burstiness.

  12. Application of high performance asynchronous socket communication in power distribution automation

    Science.gov (United States)

    Wang, Ziyu

    2017-05-01

    With the development of information technology and Internet technology, and the growing demand for electricity, the stability and the reliable operation of power system have been the goal of power grid workers. With the advent of the era of big data, the power data will gradually become an important breakthrough to guarantee the safe and reliable operation of the power grid. So, in the electric power industry, how to efficiently and robustly receive the data transmitted by the data acquisition device, make the power distribution automation system be able to execute scientific decision quickly, which is the pursuit direction in power grid. In this paper, some existing problems in the power system communication are analysed, and with the help of the network technology, a set of solutions called Asynchronous Socket Technology to the problem in network communication which meets the high concurrency and the high throughput is proposed. Besides, the paper also looks forward to the development direction of power distribution automation in the era of big data and artificial intelligence.

  13. High performance computing of density matrix renormalization group method for 2-dimensional model. Parallelization strategy toward peta computing

    International Nuclear Information System (INIS)

    Yamada, Susumu; Igarashi, Ryo; Machida, Masahiko; Imamura, Toshiyuki; Okumura, Masahiko; Onishi, Hiroaki

    2010-01-01

    We parallelize the density matrix renormalization group (DMRG) method, which is a ground-state solver for one-dimensional quantum lattice systems. The parallelization allows us to extend the applicable range of the DMRG to n-leg ladders i.e., quasi two-dimension cases. Such an extension is regarded to bring about several breakthroughs in e.g., quantum-physics, chemistry, and nano-engineering. However, the straightforward parallelization requires all-to-all communications between all processes which are unsuitable for multi-core systems, which is a mainstream of current parallel computers. Therefore, we optimize the all-to-all communications by the following two steps. The first one is the elimination of the communications between all processes by only rearranging data distribution with the communication data amount kept. The second one is the avoidance of the communication conflict by rescheduling the calculation and the communication. We evaluate the performance of the DMRG method on multi-core supercomputers and confirm that our two-steps tuning is quite effective. (author)

  14. Investigating the Mobility of Light Autonoumous Tracked Vehicles Using a High Performance Computing Simulation Capability

    Science.gov (United States)

    2012-08-01

    UNCLASSIFIED: Distribution Statement A. Approved for public release. DISCLAIMER: Reference herein to any specific commercial company , product...FunctionBay, S. Korea – NVIDIA – Caterpillar – MSC.Software – Advanced Micro Devices (AMD) 14-16 AUG 2012  Aaron Bartholomew  Makarand Datar...16GB DDR2 Graphics: 4x NVIDIA Tesla C1060 Power supply 1: 1000W Power supply 2: 750W Assembled Quad GPU Machine 14-16 AUG 2012 30

  15. FY16 NRL DoD High Performance Computing Modernization Program Annual Reports

    Science.gov (United States)

    2017-09-15

    distributed radar systems in a dynamic EM environment; cognitive radar; automatic target recognition; intelligent decision aids, counter UAV systems, and...autonomous control of robots and UxVs; cyber security, monitoring, and defense; control of the electromagnetic spectrum; cognitive radios; sonar echo...forces from initial conditions generated with second order Lagrangian perturbation theory with the MUSIC software. We performed a series of small

  16. FY16 NRL DoD High Performance Computing Modernization Program

    Science.gov (United States)

    2017-09-15

    distributed radar systems in a dynamic EM environment; cognitive radar; automatic target recognition; intelligent decision aids, counter UAV systems, and...autonomous control of robots and UxVs; cyber security, monitoring, and defense; control of the electromagnetic spectrum; cognitive radios; sonar echo...forces from initial conditions generated with second order Lagrangian perturbation theory with the MUSIC software. We performed a series of small

  17. An Interactive, Web-based High Performance Modeling Environment for Computational Epidemiology.

    Science.gov (United States)

    Deodhar, Suruchi; Bisset, Keith R; Chen, Jiangzhuo; Ma, Yifei; Marathe, Madhav V

    2014-07-01

    We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly web-based interface that allows analysts to access the models and the analytics back-end remotely from a desktop or a mobile device. The environment is based on a loosely-coupled service-oriented-architecture that allows analysts to explore various counter factual scenarios. As the modeling tools for public health epidemiology are getting more sophisticated, it is becoming increasingly hard for non-computational scientists to effectively use the systems that incorporate such models. Thus an important design consideration for an integrated modeling environment is to improve ease of use such that experimental simulations can be driven by the users. This is achieved by designing intuitive and user-friendly interfaces that allow users to design and analyze a computational experiment and steer the experiment based on the state of the system. A key feature of a system that supports this design goal is the ability to start, stop, pause and roll-back the disease propagation and intervention application process interactively. An analyst can access the state of the system at any point in time and formulate dynamic interventions based on additional information obtained through state assessment. In addition, the environment provides automated services for experiment set-up and management, thus reducing the overall time for conducting end-to-end experimental studies. We illustrate the applicability of the system by describing computational experiments based on realistic pandemic planning scenarios. The experiments are designed to demonstrate the system's capability and enhanced user productivity.

  18. HPGMG 1.0: A Benchmark for Ranking High Performance Computing Systems

    Energy Technology Data Exchange (ETDEWEB)

    Adams, Mark; Brown, Jed; Shalf, John; Straalen, Brian Van; Strohmaier, Erich; Williams, Sam

    2014-05-05

    This document provides an overview of the benchmark ? HPGMG ? for ranking large scale general purpose computers for use on the Top500 list [8]. We provide a rationale for the need for a replacement for the current metric HPL, some background of the Top500 list and the challenges of developing such a metric; we discuss our design philosophy and methodology, and an overview of the specification of the benchmark. The primary documentation with maintained details on the specification can be found at hpgmg.org and the Wiki and benchmark code itself can be found in the repository https://bitbucket.org/hpgmg/hpgmg.

  19. Applying Machine Learning and High Performance Computing to Water Quality Assessment and Prediction

    OpenAIRE

    Ruijian Zhang; Deren Li

    2017-01-01

    Water quality assessment and prediction is a more and more important issue. Traditional ways either take lots of time or they can only do assessments. In this research, by applying machine learning algorithm to a long period time of water attributes’ data; we can generate a decision tree so that it can predict the future day’s water quality in an easy and efficient way. The idea is to combine the traditional ways and the computer algorithms together. Using machine learning algorithms, the ass...

  20. Distributed control software of high-performance control-loop algorithm

    CERN Document Server

    Blanc, D

    1999-01-01

    The majority of industrial cooling and ventilation plants require the control of complex processes. All these processes are highly important for the operation of the machines. The stability and reliability of these processes are leading factors identifying the quality of the service provided. The control system architecture and software structure, as well, are required to have high dynamical performance and robust behaviour. The intelligent systems based on PID or RST controllers are used for their high level of stability and accuracy. The design and tuning of these complex controllers require the dynamic model of the plant to be known (generally obtained by identification) and the desired performance of the various control loops to be specified for achieving good performances. The concept of having a distributed control algorithm software provides full automation facilities with well-adapted functionality and good performances, giving methodology, means and tools to master the dynamic process optimization an...

  1. High performance reconciliation for continuous-variable quantum key distribution with LDPC code

    Science.gov (United States)

    Lin, Dakai; Huang, Duan; Huang, Peng; Peng, Jinye; Zeng, Guihua

    2015-03-01

    Reconciliation is a significant procedure in a continuous-variable quantum key distribution (CV-QKD) system. It is employed to extract secure secret key from the resulted string through quantum channel between two users. However, the efficiency and the speed of previous reconciliation algorithms are low. These problems limit the secure communication distance and the secure key rate of CV-QKD systems. In this paper, we proposed a high-speed reconciliation algorithm through employing a well-structured decoding scheme based on low density parity-check (LDPC) code. The complexity of the proposed algorithm is reduced obviously. By using a graphics processing unit (GPU) device, our method may reach a reconciliation speed of 25 Mb/s for a CV-QKD system, which is currently the highest level and paves the way to high-speed CV-QKD.

  2. A high-performance network for a distributed-control system

    International Nuclear Information System (INIS)

    Cuttone, G.; Aghion, F.; Giove, D.

    1989-01-01

    Local area networks play a central rule in modern distributed-control systems for accelerators. For a superconducting cyclotron under construction at the University of Milan, an optical Ethernet network has been implemented for the interconnection of multicomputer-based stations. Controller boards, with VLSI protocol chips, have been used. The higher levels of the ISO OSI model have been implemented to suit real-time control requirements. The experimental setup for measuring the data throughput between stations will be described. The effect of memory-to-memory data transfer with respect to the packet size has been studied for packets ranging from 200 bytes to 10 Kbytes. Results, showing the data throughput to range from 0.2 to 1.1 Mbit/s, will be discussed. (orig.)

  3. ArrayBridge: Interweaving declarative array processing with high-performance computing

    Energy Technology Data Exchange (ETDEWEB)

    Xing, Haoyuan [The Ohio State Univ., Columbus, OH (United States); Floratos, Sofoklis [The Ohio State Univ., Columbus, OH (United States); Blanas, Spyros [The Ohio State Univ., Columbus, OH (United States); Byna, Suren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Prabhat, Prabhat [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wu, Kesheng [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Brown, Paul [Paradigm4, Inc., Waltham, MA (United States)

    2017-05-04

    Scientists are increasingly turning to datacenter-scale computers to produce and analyze massive arrays. Despite decades of database research that extols the virtues of declarative query processing, scientists still write, debug and parallelize imperative HPC kernels even for the most mundane queries. This impedance mismatch has been partly attributed to the cumbersome data loading process; in response, the database community has proposed in situ mechanisms to access data in scientific file formats. Scientists, however, desire more than a passive access method that reads arrays from files. This paper describes ArrayBridge, a bi-directional array view mechanism for scientific file formats, that aims to make declarative array manipulations interoperable with imperative file-centric analyses. Our prototype implementation of ArrayBridge uses HDF5 as the underlying array storage library and seamlessly integrates into the SciDB open-source array database system. In addition to fast querying over external array objects, ArrayBridge produces arrays in the HDF5 file format just as easily as it can read from it. ArrayBridge also supports time travel queries from imperative kernels through the unmodified HDF5 API, and automatically deduplicates between array versions for space efficiency. Our extensive performance evaluation in NERSC, a large-scale scientific computing facility, shows that ArrayBridge exhibits statistically indistinguishable performance and I/O scalability to the native SciDB storage engine.

  4. New Developments in Modeling MHD Systems on High Performance Computing Architectures

    Science.gov (United States)

    Germaschewski, K.; Raeder, J.; Larson, D. J.; Bhattacharjee, A.

    2009-04-01

    Modeling the wide range of time and length scales present even in fluid models of plasmas like MHD and X-MHD (Extended MHD including two fluid effects like Hall term, electron inertia, electron pressure gradient) is challenging even on state-of-the-art supercomputers. In the last years, HPC capacity has continued to grow exponentially, but at the expense of making the computer systems more and more difficult to program in order to get maximum performance. In this paper, we will present a new approach to managing the complexity caused by the need to write efficient codes: Separating the numerical description of the problem, in our case a discretized right hand side (r.h.s.), from the actual implementation of efficiently evaluating it. An automatic code generator is used to describe the r.h.s. in a quasi-symbolic form while leaving the translation into efficient and parallelized code to a computer program itself. We implemented this approach for OpenGGCM (Open General Geospace Circulation Model), a model of the Earth's magnetosphere, which was accelerated by a factor of three on regular x86 architecture and a factor of 25 on the Cell BE architecture (commonly known for its deployment in Sony's PlayStation 3).

  5. Exploiting Data Intensive Applications on High Performance Computers to Unlock Australia's Landsat Archive

    Science.gov (United States)

    Purss, Matthew; Lewis, Adam; Edberg, Roger; Ip, Alex; Sixsmith, Joshua; Frankish, Glenn; Chan, Tai; Evans, Ben; Hurst, Lachlan

    2013-04-01

    Australia's Earth Observation Program has downlinked and archived satellite data acquired under the NASA Landsat mission for the Australian Government since the establishment of the Australian Landsat Station in 1979. Geoscience Australia maintains this archive and produces image products to aid the delivery of government policy objectives. Due to the labor intensive nature of processing of this data there have been few national-scale datasets created to date. To compile any Earth Observation product the historical approach has been to select the required subset of data and process "scene by scene" on an as-needed basis. As data volumes have increased over time, and the demand for the processed data has also grown, it has become increasingly difficult to rapidly produce these products and achieve satisfactory policy outcomes using these historic processing methods. The result is that we have been "drowning in a sea of uncalibrated data" and scientists, policy makers and the public have not been able to realize the full potential of the Australian Landsat Archive and its value is therefore significantly diminished. To overcome this critical issue, the Australian Space Research Program has funded the "Unlocking the Landsat Archive" (ULA) Project from April 2011 to June 2013 to improve the access and utilization of Australia's archive of Landsat data. The ULA Project is a public-private consortium led by Lockheed Martin Australia (LMA) and involving Geoscience Australia (GA), the Victorian Partnership for Advanced Computing (VPAC), the National Computational Infrastructure (NCI) at the Australian National University (ANU) and the Cooperative Research Centre for Spatial Information (CRC-SI). The outputs from the ULA project will become a fundamental component of Australia's eResearch infrastructure, with the Australian Landsat Archive hosted on the NCI and made openly available under a creative commons license. NCI provides access to researchers through significant HPC

  6. SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations

    Science.gov (United States)

    Choi, Shinhyun; Tan, Scott H.; Li, Zefan; Kim, Yunjo; Choi, Chanyeol; Chen, Pai-Yu; Yeon, Hanwool; Yu, Shimeng; Kim, Jeehwan

    2018-01-01

    Although several types of architecture combining memory cells and transistors have been used to demonstrate artificial synaptic arrays, they usually present limited scalability and high power consumption. Transistor-free analog switching devices may overcome these limitations, yet the typical switching process they rely on—formation of filaments in an amorphous medium—is not easily controlled and hence hampers the spatial and temporal reproducibility of the performance. Here, we demonstrate analog resistive switching devices that possess desired characteristics for neuromorphic computing networks with minimal performance variations using a single-crystalline SiGe layer epitaxially grown on Si as a switching medium. Such epitaxial random access memories utilize threading dislocations in SiGe to confine metal filaments in a defined, one-dimensional channel. This confinement results in drastically enhanced switching uniformity and long retention/high endurance with a high analog on/off ratio. Simulations using the MNIST handwritten recognition data set prove that epitaxial random access memories can operate with an online learning accuracy of 95.1%.

  7. 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.

  8. 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.

  9. Distributed computing for macromolecular crystallography.

    Science.gov (United States)

    Krissinel, Evgeny; Uski, Ville; Lebedev, Andrey; Winn, Martyn; Ballard, Charles

    2018-02-01

    Modern crystallographic computing is characterized by the growing role of automated structure-solution pipelines, which represent complex expert systems utilizing a number of program components, decision makers and databases. They also require considerable computational resources and regular database maintenance, which is increasingly more difficult to provide at the level of individual desktop-based CCP4 setups. On the other hand, there is a significant growth in data processed in the field, which brings up the issue of centralized facilities for keeping both the data collected and structure-solution projects. The paradigm of distributed computing and data management offers a convenient approach to tackling these problems, which has become more attractive in recent years owing to the popularity of mobile devices such as tablets and ultra-portable laptops. In this article, an overview is given of developments by CCP4 aimed at bringing distributed crystallographic computations to a wide crystallographic community.

  10. High Performance Computation of a Jet in Crossflow by Lattice Boltzmann Based Parallel Direct Numerical Simulation

    Directory of Open Access Journals (Sweden)

    Jiang Lei

    2015-01-01

    Full Text Available Direct numerical simulation (DNS of a round jet in crossflow based on lattice Boltzmann method (LBM is carried out on multi-GPU cluster. Data parallel SIMT (single instruction multiple thread characteristic of GPU matches the parallelism of LBM well, which leads to the high efficiency of GPU on the LBM solver. With present GPU settings (6 Nvidia Tesla K20M, the present DNS simulation can be completed in several hours. A grid system of 1.5 × 108 is adopted and largest jet Reynolds number reaches 3000. The jet-to-free-stream velocity ratio is set as 3.3. The jet is orthogonal to the mainstream flow direction. The validated code shows good agreement with experiments. Vortical structures of CRVP, shear-layer vortices and horseshoe vortices, are presented and analyzed based on velocity fields and vorticity distributions. Turbulent statistical quantities of Reynolds stress are also displayed. Coherent structures are revealed in a very fine resolution based on the second invariant of the velocity gradients.

  11. Run-Time Dynamically-Adaptable FPGA-Based Architecture for High-Performance Autonomous Distributed Systems

    OpenAIRE

    Valverde Alcalá, Juan

    2016-01-01

    Esta tesis doctoral se enmarca dentro del campo de los sistemas embebidos reconfigurables, redes de sensores inalámbricas para aplicaciones de altas prestaciones, y computación distribuida. El documento se centra en el estudio de alternativas de procesamiento para sistemas embebidos autónomos distribuidos de altas prestaciones (por sus siglas en inglés, High-Performance Autonomous Distributed Systems (HPADS)), así como su evolución hacia el procesamiento de alta resolución. El estudio se ha ...

  12. Distributed-memory matrix computations

    DEFF Research Database (Denmark)

    Balle, Susanne Mølleskov

    1995-01-01

    The main goal of this project is to investigate, develop, and implement algorithms for numerical linear algebra on parallel computers in order to acquire expertise in methods for parallel computations. An important motivation for analyzaing and investigating the potential for parallelism in these......The main goal of this project is to investigate, develop, and implement algorithms for numerical linear algebra on parallel computers in order to acquire expertise in methods for parallel computations. An important motivation for analyzaing and investigating the potential for parallelism...... in these algorithms is that many scientific applications rely heavily on the performance of the involved dense linear algebra building blocks. Even though we consider the distributed-memory as well as the shared-memory programming paradigm, the major part of the thesis is dedicated to distributed-memory architectures....... We emphasize distributed-memory massively parallel computers - such as the Connection Machines model CM-200 and model CM-5/CM-5E - available to us at UNI-C and at Thinking Machines Corporation. The CM-200 was at the time this project started one of the few existing massively parallel computers...

  13. Coordinated Fault-Tolerance for High-Performance Computing Final Project Report

    Energy Technology Data Exchange (ETDEWEB)

    Panda, Dhabaleswar Kumar [The Ohio State University; Beckman, Pete

    2011-07-28

    existing publish-subscribe tools. We enhanced the intrinsic fault tolerance capabilities representative implementations of a variety of key HPC software subsystems and integrated them with the FTB. Targeting software subsystems included: MPI communication libraries, checkpoint/restart libraries, resource managers and job schedulers, and system monitoring tools. Leveraging the aforementioned infrastructure, as well as developing and utilizing additional tools, we have examined issues associated with expanded, end-to-end fault response from both system and application viewpoints. From the standpoint of system operations, we have investigated log and root cause analysis, anomaly detection and fault prediction, and generalized notification mechanisms. Our applications work has included libraries for fault-tolerance linear algebra, application frameworks for coupled multiphysics applications, and external frameworks to support the monitoring and response for general applications. Our final goal was to engage the high-end computing community to increase awareness of tools and issues around coordinated end-to-end fault management.

  14. Development of three-dimensional neoclassical transport simulation code with high performance Fortran on a vector-parallel computer

    International Nuclear Information System (INIS)

    Satake, Shinsuke; Okamoto, Masao; Nakajima, Noriyoshi; Takamaru, Hisanori

    2005-11-01

    A neoclassical transport simulation code (FORTEC-3D) applicable to three-dimensional configurations has been developed using High Performance Fortran (HPF). Adoption of computing techniques for parallelization and a hybrid simulation model to the δf Monte-Carlo method transport simulation, including non-local transport effects in three-dimensional configurations, makes it possible to simulate the dynamism of global, non-local transport phenomena with a self-consistent radial electric field within a reasonable computation time. In this paper, development of the transport code using HPF is reported. Optimization techniques in order to achieve both high vectorization and parallelization efficiency, adoption of a parallel random number generator, and also benchmark results, are shown. (author)

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

    Science.gov (United States)

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

    2014-12-01

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

  16. High performance in software development

    CERN Multimedia

    CERN. Geneva; Haapio, Petri; Liukkonen, Juha-Matti

    2015-01-01

    What are the ingredients of high-performing software? Software development, especially for large high-performance systems, is one the most complex tasks mankind has ever tried. Technological change leads to huge opportunities but challenges our old ways of working. Processing large data sets, possibly in real time or with other tight computational constraints, requires an efficient solution architecture. Efficiency requirements span from the distributed storage and large-scale organization of computation and data onto the lowest level of processor and data bus behavior. Integrating performance behavior over these levels is especially important when the computation is resource-bounded, as it is in numerics: physical simulation, machine learning, estimation of statistical models, etc. For example, memory locality and utilization of vector processing are essential for harnessing the computing power of modern processor architectures due to the deep memory hierarchies of modern general-purpose computers. As a r...

  17. 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

  18. Refficientlib: an efficient load-rebalanced adaptive mesh refinement algorithm for high-performance computational physics meshes

    OpenAIRE

    Baiges Aznar, Joan; Bayona Roa, Camilo Andrés

    2017-01-01

    No separate or additional fees are collected for access to or distribution of the work. In this paper we present a novel algorithm for adaptive mesh refinement in computational physics meshes in a distributed memory parallel setting. The proposed method is developed for nodally based parallel domain partitions where the nodes of the mesh belong to a single processor, whereas the elements can belong to multiple processors. Some of the main features of the algorithm presented in this paper a...

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

    KAUST Repository

    Danani, Bob K.

    2012-01-01

    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

  20. Photons, photosynthesis, and high-performance computing: challenges, progress, and promise of modeling metabolism in green algae

    International Nuclear Information System (INIS)

    Chang, C H; Graf, P; Alber, D M; Kim, K; Murray, G; Posewitz, M; Seibert, M

    2008-01-01

    The complexity associated with biological metabolism considered at a kinetic level presents a challenge to quantitative modeling. In particular, the relatively sparse knowledge of parameters for enzymes with known kinetic responses is problematic. The possible space of these parameters is of high-dimension, and sampling of such a space typifies a combinatorial explosion of possible dynamic states. However, with sufficient quantitative transcriptomics, proteomics, and metabolomics data at hand, these challenges could be met by high-performance software with sampling, fitting, and optimization capabilities. With this in mind, we present the High-Performance Systems Biology Toolkit HiPer SBTK, an evolving software package to simulate, fit, and optimize metabolite concentrations and fluxes within the space of rate and binding parameters associated with detailed enzyme kinetic models. We present our chosen modeling paradigm for the formulation of metabolic pathway models, the means to address the challenge of representing such models in a precise and persistent fashion using the standardized Systems Biology Markup Language, and our second-generation model of H2-associated Chlamydomonas metabolism. Processing of such models for hierarchically parallelized simulation and optimization, job specification by the user through a GUI interface, software capabilities and initial scaling data, and the mapping of the computation to biological questions is also discussed. Moreover, we present near-term future software and model development goals

  1. Harnessing the Department of Energy’s High-Performance Computing Expertise to Strengthen the U.S. Chemical Enterprise

    Energy Technology Data Exchange (ETDEWEB)

    Dixon, David A.; Dupuis, Michel; Garrett, Bruce C.; Neaton, Jeffrey B.; Plata, Charity; Tarr, Matthew A.; Tomb, Jean-Francois; Golab, Joseph T.

    2012-01-17

    High-performance computing (HPC) is one area where the DOE has developed extensive expertise and capability. However, this expertise currently is not properly shared with or used by the private sector to speed product development, enable industry to move rapidly into new areas, and improve product quality. Such use would lead to substantial competitive advantages in global markets and yield important economic returns for the United States. To stimulate the dissemination of DOE's HPC expertise, the Council for Chemical Research (CCR) and the DOE jointly held a workshop on this topic. Four important energy topic areas were chosen as the focus of the meeting: Biomass/Bioenergy, Catalytic Materials, Energy Storage, and Photovoltaics. Academic, industrial, and government experts in these topic areas participated in the workshop to identify industry needs, evaluate the current state of expertise, offer proposed actions and strategies, and forecast the expected benefits of implementing those strategies.

  2. Physical modeling and high-performance GPU computing for characterization, interception, and disruption of hazardous near-Earth objects

    Science.gov (United States)

    Kaplinger, Brian Douglas

    For the past few decades, both the scientific community and the general public have been becoming more aware that the Earth lives in a shooting gallery of small objects. We classify all of these asteroids and comets, known or unknown, that cross Earth's orbit as near-Earth objects (NEOs). A look at our geologic history tells us that NEOs have collided with Earth in the past, and we expect that they will continue to do so. With thousands of known NEOs crossing the orbit of Earth, there has been significant scientific interest in developing the capability to deflect an NEO from an impacting trajectory. This thesis applies the ideas of Smoothed Particle Hydrodynamics (SPH) theory to the NEO disruption problem. A simulation package was designed that allows efficacy simulation to be integrated into the mission planning and design process. This is done by applying ideas in high-performance computing (HPC) on the computer graphics processing unit (GPU). Rather than prove a concept through large standalone simulations on a supercomputer, a highly parallel structure allows for flexible, target dependent questions to be resolved. Built around nonclassified data and analysis, this computer package will allow academic institutions to better tackle the issue of NEO mitigation effectiveness.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-02-06

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

  4. Proceedings of the High Performance Embedded Computing Workshop (HPEC 2006) (10th). Held in Lexington, Massachusetts on September 19-21, 2006 (CD-ROM)

    National Research Council Canada - National Science Library

    Kepner, Jeremy

    2007-01-01

    ...: 1 CD-ROM; 4 3/4 in.; 78.3 MB. ABSTRACT: The High-Performance Embedded Computing (HPEC) technical committee announced the tenth annual HPEC Workshop held in September 2006 at MIT Lincoln Laboratory in Lexington, MA...

  5. High-performance simulation-based algorithms for an alpine ski racer’s trajectory optimization in heterogeneous computer systems

    Directory of Open Access Journals (Sweden)

    Dębski Roman

    2014-09-01

    Full Text Available Effective, simulation-based trajectory optimization algorithms adapted to heterogeneous computers are studied with reference to the problem taken from alpine ski racing (the presented solution is probably the most general one published so far. The key idea behind these algorithms is to use a grid-based discretization scheme to transform the continuous optimization problem into a search problem over a specially constructed finite graph, and then to apply dynamic programming to find an approximation of the global solution. In the analyzed example it is the minimum-time ski line, represented as a piecewise-linear function (a method of elimination of unfeasible solutions is proposed. Serial and parallel versions of the basic optimization algorithm are presented in detail (pseudo-code, time and memory complexity. Possible extensions of the basic algorithm are also described. The implementation of these algorithms is based on OpenCL. The included experimental results show that contemporary heterogeneous computers can be treated as μ-HPC platforms-they offer high performance (the best speedup was equal to 128 while remaining energy and cost efficient (which is crucial in embedded systems, e.g., trajectory planners of autonomous robots. The presented algorithms can be applied to many trajectory optimization problems, including those having a black-box represented performance measure

  6. Exploring Subpixel Learning Algorithms for Estimating Global Land Cover Fractions from Satellite Data Using High Performance Computing

    Directory of Open Access Journals (Sweden)

    Uttam Kumar

    2017-10-01

    Full Text Available Land cover (LC refers to the physical and biological cover present over the Earth’s surface in terms of the natural environment such as vegetation, water, bare soil, etc. Most LC features occur at finer spatial scales compared to the resolution of primary remote sensing satellites. Therefore, observed data are a mixture of spectral signatures of two or more LC features resulting in mixed pixels. One solution to the mixed pixel problem is the use of subpixel learning algorithms to disintegrate the pixel spectrum into its constituent spectra. Despite the popularity and existing research conducted on the topic, the most appropriate approach is still under debate. As an attempt to address this question, we compared the performance of several subpixel learning algorithms based on least squares, sparse regression, signal–subspace and geometrical methods. Analysis of the results obtained through computer-simulated and Landsat data indicated that fully constrained least squares (FCLS outperformed the other techniques. Further, FCLS was used to unmix global Web-Enabled Landsat Data to obtain abundances of substrate (S, vegetation (V and dark object (D classes. Due to the sheer nature of data and computational needs, we leveraged the NASA Earth Exchange (NEX high-performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into four classes, namely forest, farmland, water and urban areas (in conjunction with nighttime lights data over California, USA using a random forest classifier. Validation of these LC maps with the National Land Cover Database 2011 products and North American Forest Dynamics static forest map shows a 6% improvement in unmixing-based classification relative to per-pixel classification. As such, abundance maps continue to offer a useful alternative to high-spatial-resolution classified maps for forest inventory analysis, multi

  7. Overlapping clusters for distributed computation.

    Energy Technology Data Exchange (ETDEWEB)

    Mirrokni, Vahab (Google Research, New York, NY); Andersen, Reid (Microsoft Corporation, Redmond, WA); Gleich, David F.

    2010-11-01

    Scalable, distributed algorithms must address communication problems. We investigate overlapping clusters, or vertex partitions that intersect, for graph computations. This setup stores more of the graph than required but then affords the ease of implementation of vertex partitioned algorithms. Our hope is that this technique allows us to reduce communication in a computation on a distributed graph. The motivation above draws on recent work in communication avoiding algorithms. Mohiyuddin et al. (SC09) design a matrix-powers kernel that gives rise to an overlapping partition. Fritzsche et al. (CSC2009) develop an overlapping clustering for a Schwarz method. Both techniques extend an initial partitioning with overlap. Our procedure generates overlap directly. Indeed, Schwarz methods are commonly used to capitalize on overlap. Elsewhere, overlapping communities (Ahn et al, Nature 2009; Mishra et al. WAW2007) are now a popular model of structure in social networks. These have long been studied in statistics (Cole and Wishart, CompJ 1970). We present two types of results: (i) an estimated swapping probability {rho}{infinity}; and (ii) the communication volume of a parallel PageRank solution (link-following {alpha} = 0.85) using an additive Schwarz method. The volume ratio is the amount of extra storage for the overlap (2 means we store the graph twice). Below, as the ratio increases, the swapping probability and PageRank communication volume decreases.

  8. Complex three dimensional modelling of porous media using high performance computing and multi-scale incompressible approach

    Science.gov (United States)

    Martin, R.; Orgogozo, L.; Noiriel, C. N.; Guibert, R.; Golfier, F.; Debenest, G.; Quintard, M.

    2013-05-01

    In the context of biofilm growth in porous media, we developed high performance computing tools to study the impact of biofilms on the fluid transport through pores of a solid matrix. Indeed, biofilms are consortia of micro-organisms that are developing in polymeric extracellular substances that are generally located at a fluid-solid interfaces like pore interfaces in a water-saturated porous medium. Several applications of biofilms in porous media are encountered for instance in bio-remediation methods by allowing the dissolution of organic pollutants. Many theoretical studies have been done on the resulting effective properties of these modified media ([1],[2], [3]) but the bio-colonized porous media under consideration are mainly described following simplified theoretical media (stratified media, cubic networks of spheres ...). Therefore, recent experimental advances have provided tomography images of bio-colonized porous media which allow us to observe realistic biofilm micro-structures inside the porous media [4]. To solve closure system of equations related to upscaling procedures in realistic porous media, we solve the velocity field of fluids through pores on complex geometries that are described with a huge number of cells (up to billions). Calculations are made on a realistic 3D sample geometry obtained by X micro-tomography. Cell volumes are coming from a percolation experiment performed to estimate the impact of precipitation processes on the properties of a fluid transport phenomena in porous media [5]. Average permeabilities of the sample are obtained from velocities by using MPI-based high performance computing on up to 1000 processors. Steady state Stokes equations are solved using finite volume approach. Relaxation pre-conditioning is introduced to accelerate the code further. Good weak or strong scaling are reached with results obtained in hours instead of weeks. Factors of accelerations of 20 up to 40 can be reached. Tens of geometries can now be

  9. Computational Approach for Securing Radiology-Diagnostic Data in Connected Health Network using High-Performance GPU-Accelerated AES.

    Science.gov (United States)

    Adeshina, A M; Hashim, R

    2017-03-01

    Diagnostic radiology is a core and integral part of modern medicine, paving ways for the primary care physicians in the disease diagnoses, treatments and therapy managements. Obviously, all recent standard healthcare procedures have immensely benefitted from the contemporary information technology revolutions, apparently revolutionizing those approaches to acquiring, storing and sharing of diagnostic data for efficient and timely diagnosis of diseases. Connected health network was introduced as an alternative to the ageing traditional concept in healthcare system, improving hospital-physician connectivity and clinical collaborations. Undoubtedly, the modern medicinal approach has drastically improved healthcare but at the expense of high computational cost and possible breach of diagnosis privacy. Consequently, a number of cryptographical techniques are recently being applied to clinical applications, but the challenges of not being able to successfully encrypt both the image and the textual data persist. Furthermore, processing time of encryption-decryption of medical datasets, within a considerable lower computational cost without jeopardizing the required security strength of the encryption algorithm, still remains as an outstanding issue. This study proposes a secured radiology-diagnostic data framework for connected health network using high-performance GPU-accelerated Advanced Encryption Standard. The study was evaluated with radiology image datasets consisting of brain MR and CT datasets obtained from the department of Surgery, University of North Carolina, USA, and the Swedish National Infrastructure for Computing. Sample patients' notes from the University of North Carolina, School of medicine at Chapel Hill were also used to evaluate the framework for its strength in encrypting-decrypting textual data in the form of medical report. Significantly, the framework is not only able to accurately encrypt and decrypt medical image datasets, but it also

  10. Towards distributed multiscale computing for the VPH

    NARCIS (Netherlands)

    Hoekstra, A.G.; Coveney, P.

    2010-01-01

    Multiscale modeling is fundamental to the Virtual Physiological Human (VPH) initiative. Most detailed three-dimensional multiscale models lead to prohibitive computational demands. As a possible solution we present MAPPER, a computational science infrastructure for Distributed Multiscale Computing

  11. Adoption of High Performance Computational (HPC) Modeling Software for Widespread Use in the Manufacture of Welded Structures

    Energy Technology Data Exchange (ETDEWEB)

    Brust, Frederick W. [Engineering Mechanics Corporation of Columbus, Columbus, OH (United States); Punch, Edward F. [Engineering Mechanics Corporation of Columbus, Columbus, OH (United States); Twombly, Elizabeth Kurth [Engineering Mechanics Corporation of Columbus, Columbus, OH (United States); Kalyanam, Suresh [Engineering Mechanics Corporation of Columbus, Columbus, OH (United States); Kennedy, James [Engineering Mechanics Corporation of Columbus, Columbus, OH (United States); Hattery, Garty R. [Engineering Mechanics Corporation of Columbus, Columbus, OH (United States); Dodds, Robert H. [Professional Consulting Services, Inc., Lisle, IL (United States); Mach, Justin C [Caterpillar, Peoria, IL (United States); Chalker, Alan [Ohio Supercomputer Center (OSC), Columbus, OH (United States); Nicklas, Jeremy [Ohio Supercomputer Center (OSC), Columbus, OH (United States); Gohar, Basil M [Ohio Supercomputer Center (OSC), Columbus, OH (United States); Hudak, David [Ohio Supercomputer Center (OSC), Columbus, OH (United States)

    2016-12-30

    This report summarizes the final product developed for the US DOE Small Business Innovation Research (SBIR) Phase II grant made to Engineering Mechanics Corporation of Columbus (Emc2) between April 16, 2014 and August 31, 2016 titled ‘Adoption of High Performance Computational (HPC) Modeling Software for Widespread Use in the Manufacture of Welded Structures’. Many US companies have moved fabrication and production facilities off shore because of cheaper labor costs. A key aspect in bringing these jobs back to the US is the use of technology to render US-made fabrications more cost-efficient overall with higher quality. One significant advantage that has emerged in the US over the last two decades is the use of virtual design for fabrication of small and large structures in weld fabrication industries. Industries that use virtual design and analysis tools have reduced material part size, developed environmentally-friendly fabrication processes, improved product quality and performance, and reduced manufacturing costs. Indeed, Caterpillar Inc. (CAT), one of the partners in this effort, continues to have a large fabrication presence in the US because of the use of weld fabrication modeling to optimize fabrications by controlling weld residual stresses and distortions and improving fatigue, corrosion, and fracture performance. This report describes Emc2’s DOE SBIR Phase II final results to extend an existing, state-of-the-art software code, Virtual Fabrication Technology (VFT®), currently used to design and model large welded structures prior to fabrication - to a broader range of products with widespread applications for small and medium-sized enterprises (SMEs). VFT® helps control distortion, can minimize and/or control residual stresses, control welding microstructure, and pre-determine welding parameters such as weld-sequencing, pre-bending, thermal-tensioning, etc. VFT® uses material properties, consumable properties, etc. as inputs

  12. High performance systems

    Energy Technology Data Exchange (ETDEWEB)

    Vigil, M.B. [comp.

    1995-03-01

    This document provides a written compilation of the presentations and viewgraphs from the 1994 Conference on High Speed Computing given at the High Speed Computing Conference, {open_quotes}High Performance Systems,{close_quotes} held at Gleneden Beach, Oregon, on April 18 through 21, 1994.

  13. A New High-Performance Liquid Chromatographic Method for the Determination and Distribution of Linalool in Michelia alba

    Directory of Open Access Journals (Sweden)

    Hua-Bin Li

    2010-07-01

    Full Text Available A new high-performance liquid chromatographic method with photodiode array detection was established for the determination of linalool in the plant Michelia alba. Linalool was extracted from the plant sample with the aid of ultrasound, and was analyzed on a Waters RP C18 column (4.6 × 150 mm, 5 μm using an acetonitrile and water (55:45, v/v mobile phase at a flow rate of 1.0 mL/min. The column temperature was set at 25 ºC, and the detection wavelength was 210 nm. The linear range of the method was 5–200 μg/mL with a correlation coefficient of 0.9975. The recovery was 92–112%, and the relative standard deviation was 1.85% (n = 9. The present method has been used to study the distribution of linalool in the plant Michelia alba. The plant samples include flowers, leaves and tender twigs. Furthermore, leaves included samples in their tender, grown-up and fallen phases, and flowers included samples in their juvenile, middle and whitening phases. The concentrations of linalool in different parts of the plant were 0.21–0.65%, 1.63–4.89% and 0.43% for leaves, flowers and tender twigs, respectively. The results showed that all the plant materials contained relative high concentration of linalool, and juvenile phase flowers contained the highest concentration of linalool. Notably, the fallen leaves also contained high concentrations of linalool, which could be a potential resource of this compound. The results obtained are very helpful for the potential full utilization of this plant.

  14. Distributed and cloud computing from parallel processing to the Internet of Things

    CERN Document Server

    Hwang, Kai; Fox, Geoffrey C

    2012-01-01

    Distributed and Cloud Computing, named a 2012 Outstanding Academic Title by the American Library Association's Choice publication, explains how to create high-performance, scalable, reliable systems, exposing the design principles, architecture, and innovative applications of parallel, distributed, and cloud computing systems. Starting with an overview of modern distributed models, the book provides comprehensive coverage of distributed and cloud computing, including: Facilitating management, debugging, migration, and disaster recovery through virtualization Clustered systems for resear

  15. A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

    Science.gov (United States)

    Basu, Saikat; Ganguly, Sangram; Michaelis, Andrew; Votava, Petr; Roy, Anshuman; Mukhopadhyay, Supratik; Nemani, Ramakrishna

    2015-01-01

    Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

  16. A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery using a Probabilistic Learning Framework

    Science.gov (United States)

    Basu, S.; Ganguly, S.; Michaelis, A.; Votava, P.; Roy, A.; Mukhopadhyay, S.; Nemani, R. R.

    2015-12-01

    Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

  17. SU-E-T-531: Performance Evaluation of Multithreaded Geant4 for Proton Therapy Dose Calculations in a High Performance Computing Facility

    International Nuclear Information System (INIS)

    Shin, J; Coss, D; McMurry, J; Farr, J; Faddegon, B

    2014-01-01

    Purpose: To evaluate the efficiency of multithreaded Geant4 (Geant4-MT, version 10.0) for proton Monte Carlo dose calculations using a high performance computing facility. Methods: Geant4-MT was used to calculate 3D dose distributions in 1×1×1 mm3 voxels in a water phantom and patient's head with a 150 MeV proton beam covering approximately 5×5 cm2 in the water phantom. Three timestamps were measured on the fly to separately analyze the required time for initialization (which cannot be parallelized), processing time of individual threads, and completion time. Scalability of averaged processing time per thread was calculated as a function of thread number (1, 100, 150, and 200) for both 1M and 50 M histories. The total memory usage was recorded. Results: Simulations with 50 M histories were fastest with 100 threads, taking approximately 1.3 hours and 6 hours for the water phantom and the CT data, respectively with better than 1.0 % statistical uncertainty. The calculations show 1/N scalability in the event loops for both cases. The gains from parallel calculations started to decrease with 150 threads. The memory usage increases linearly with number of threads. No critical failures were observed during the simulations. Conclusion: Multithreading in Geant4-MT decreased simulation time in proton dose distribution calculations by a factor of 64 and 54 at a near optimal 100 threads for water phantom and patient's data respectively. Further simulations will be done to determine the efficiency at the optimal thread number. Considering the trend of computer architecture development, utilizing Geant4-MT for radiotherapy simulations is an excellent cost-effective alternative for a distributed batch queuing system. However, because the scalability depends highly on simulation details, i.e., the ratio of the processing time of one event versus waiting time to access for the shared event queue, a performance evaluation as described is recommended

  18. Simulation model of load balancing in distributed computing systems

    Science.gov (United States)

    Botygin, I. A.; Popov, V. N.; Frolov, S. G.

    2017-02-01

    The availability of high-performance computing, high speed data transfer over the network and widespread of software for the design and pre-production in mechanical engineering have led to the fact that at the present time the large industrial enterprises and small engineering companies implement complex computer systems for efficient solutions of production and management tasks. Such computer systems are generally built on the basis of distributed heterogeneous computer systems. The analytical problems solved by such systems are the key models of research, but the system-wide problems of efficient distribution (balancing) of the computational load and accommodation input, intermediate and output databases are no less important. The main tasks of this balancing system are load and condition monitoring of compute nodes, and the selection of a node for transition of the user’s request in accordance with a predetermined algorithm. The load balancing is one of the most used methods of increasing productivity of distributed computing systems through the optimal allocation of tasks between the computer system nodes. Therefore, the development of methods and algorithms for computing optimal scheduling in a distributed system, dynamically changing its infrastructure, is an important task.

  19. Computer Graphics Simulations of Sampling Distributions.

    Science.gov (United States)

    Gordon, Florence S.; Gordon, Sheldon P.

    1989-01-01

    Describes the use of computer graphics simulations to enhance student understanding of sampling distributions that arise in introductory statistics. Highlights include the distribution of sample proportions, the distribution of the difference of sample means, the distribution of the difference of sample proportions, and the distribution of sample…

  20. The Benefits and Complexities of Operating Geographic Information Systems (GIS) in a High Performance Computing (HPC) Environment

    Science.gov (United States)

    Shute, J.; Carriere, L.; Duffy, D.; Hoy, E.; Peters, J.; Shen, Y.; Kirschbaum, D.

    2017-12-01

    The NASA Center for Climate Simulation (NCCS) at the Goddard Space Flight Center is building and maintaining an Enterprise GIS capability for its stakeholders, to include NASA scientists, industry partners, and the public. This platform is powered by three GIS subsystems operating in a highly-available, virtualized environment: 1) the Spatial Analytics Platform is the primary NCCS GIS and provides users discoverability of the vast DigitalGlobe/NGA raster assets within the NCCS environment; 2) the Disaster Mapping Platform provides mapping and analytics services to NASA's Disaster Response Group; and 3) the internal (Advanced Data Analytics Platform/ADAPT) enterprise GIS provides users with the full suite of Esri and open source GIS software applications and services. All systems benefit from NCCS's cutting edge infrastructure, to include an InfiniBand network for high speed data transfers; a mixed/heterogeneous environment featuring seamless sharing of information between Linux and Windows subsystems; and in-depth system monitoring and warning systems. Due to its co-location with the NCCS Discover High Performance Computing (HPC) environment and the Advanced Data Analytics Platform (ADAPT), the GIS platform has direct access to several large NCCS datasets including DigitalGlobe/NGA, Landsat, MERRA, and MERRA2. Additionally, the NCCS ArcGIS Desktop Windows virtual machines utilize existing NetCDF and OPeNDAP assets for visualization, modelling, and analysis - thus eliminating the need for data duplication. With the advent of this platform, Earth scientists have full access to vast data repositories and the industry-leading tools required for successful management and analysis of these multi-petabyte, global datasets. The full system architecture and integration with scientific datasets will be presented. Additionally, key applications and scientific analyses will be explained, to include the NASA Global Landslide Catalog (GLC) Reporter crowdsourcing application, the

  1. Distributed GIS Computing for High Performance Simulation and Visualization, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Today, the ability of sensors to generate geographical data is virtually limitless. Although NASA now provides (together with other agencies such as the USGS) a...

  2. Support system for ATLAS distributed computing operations

    CERN Document Server

    Kishimoto, Tomoe; The ATLAS collaboration

    2018-01-01

    The ATLAS distributed computing system has allowed the experiment to successfully meet the challenges of LHC Run 2. In order for distributed computing to operate smoothly and efficiently, several support teams are organized in the ATLAS experiment. The ADCoS (ATLAS Distributed Computing Operation Shifts) is a dedicated group of shifters who follow and report failing jobs, failing data transfers between sites, degradation of ATLAS central computing services, and more. The DAST (Distributed Analysis Support Team) provides user support to resolve issues related to running distributed analysis on the grid. The CRC (Computing Run Coordinator) maintains a global view of the day-to-day operations. In this presentation, the status and operational experience of the support system for ATLAS distributed computing in LHC Run 2 will be reported. This report also includes operations experience from the grid site point of view, and an analysis of the errors that create the biggest waste of wallclock time. The report of oper...

  3. Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Chase Qishi [New Jersey Inst. of Technology, Newark, NJ (United States); Univ. of Memphis, TN (United States); Zhu, Michelle Mengxia [Southern Illinois Univ., Carbondale, IL (United States)

    2016-06-06

    The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models feature diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific

  4. A distributed computer system for digitising machines

    International Nuclear Information System (INIS)

    Bairstow, R.; Barlow, J.; Waters, M.; Watson, J.

    1977-07-01

    This paper describes a Distributed Computing System, based on micro computers, for the monitoring and control of digitising tables used by the Rutherford Laboratory Bubble Chamber Research Group in the measurement of bubble chamber photographs. (author)

  5. Distributed Processing in Cloud Computing

    OpenAIRE

    Mavridis, Ilias; Karatza, Eleni

    2016-01-01

    Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016) Timisoara, Romania. February 8-11, 2016. Cloud computing offers a wide range of resources and services through the Internet that can been used for various purposes. The rapid growth of cloud computing has exempted many companies and institutions from the burden of maintaining expensive hardware and software infrastructure. With characteristics like high scalability, availability ...

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

    OpenAIRE

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

    2010-01-01

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

  7. Distributed computing and nuclear reactor analysis

    International Nuclear Information System (INIS)

    Brown, F.B.; Derstine, K.L.; Blomquist, R.N.

    1994-01-01

    Large-scale scientific and engineering calculations for nuclear reactor analysis can now be carried out effectively in a distributed computing environment, at costs far lower than for traditional mainframes. The distributed computing environment must include support for traditional system services, such as a queuing system for batch work, reliable filesystem backups, and parallel processing capabilities for large jobs. All ANL computer codes for reactor analysis have been adapted successfully to a distributed system based on workstations and X-terminals. Distributed parallel processing has been demonstrated to be effective for long-running Monte Carlo calculations

  8. An Introduction to High Performance Fortran

    Directory of Open Access Journals (Sweden)

    John Merlin

    1995-01-01

    Full Text Available High Performance Fortran (HPF is an informal standard for extensions to Fortran 90 to assist its implementation on parallel architectures, particularly for data-parallel computation. Among other things, it includes directives for specifying data distribution across multiple memories, and concurrent execution features. This article provides a tutorial introduction to the main features of HPF.

  9. Bayesian optimization for computationally extensive probability distributions.

    Science.gov (United States)

    Tamura, Ryo; Hukushima, Koji

    2018-01-01

    An efficient method for finding a better maximizer of computationally extensive probability distributions is proposed on the basis of a Bayesian optimization technique. A key idea of the proposed method is to use extreme values of acquisition functions by Gaussian processes for the next training phase, which should be located near a local maximum or a global maximum of the probability distribution. Our Bayesian optimization technique is applied to the posterior distribution in the effective physical model estimation, which is a computationally extensive probability distribution. Even when the number of sampling points on the posterior distributions is fixed to be small, the Bayesian optimization provides a better maximizer of the posterior distributions in comparison to those by the random search method, the steepest descent method, or the Monte Carlo method. Furthermore, the Bayesian optimization improves the results efficiently by combining the steepest descent method and thus it is a powerful tool to search for a better maximizer of computationally extensive probability distributions.

  10. Fel simulations using distributed computing

    NARCIS (Netherlands)

    Einstein, J.; Biedron, S.G.; Freund, H.P.; Milton, S.V.; Van Der Slot, P. J M; Bernabeu, G.

    2016-01-01

    While simulation tools are available and have been used regularly for simulating light sources, including Free-Electron Lasers, the increasing availability and lower cost of accelerated computing opens up new opportunities. This paper highlights a method of how accelerating and parallelizing code

  11. High performance computing applied to simulation of the flow in pipes; Computacao de alto desempenho aplicada a simulacao de escoamento em dutos

    Energy Technology Data Exchange (ETDEWEB)

    Cozin, Cristiane; Lueders, Ricardo; Morales, Rigoberto E.M. [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil). Dept. de Engenharia Mecanica

    2008-07-01

    In recent years, computer cluster has emerged as a real alternative to solution of problems which require high performance computing. Consequently, the development of new applications has been driven. Among them, flow simulation represents a real computational burden specially for large systems. This work presents a study of using parallel computing for numerical fluid flow simulation in pipelines. A mathematical flow model is numerically solved. In general, this procedure leads to a tridiagonal system of equations suitable to be solved by a parallel algorithm. In this work, this is accomplished by a parallel odd-oven reduction method found in the literature which is implemented on Fortran programming language. A computational platform composed by twelve processors was used. Many measures of CPU times for different tridiagonal system sizes and number of processors were obtained, highlighting the communication time between processors as an important issue to be considered when evaluating the performance of parallel applications. (author)

  12. Hazard-to-Risk: High-Performance Computing Simulations of Large Earthquake Ground Motions and Building Damage in the Near-Fault Region

    Science.gov (United States)

    Miah, M.; Rodgers, A. J.; McCallen, D.; Petersson, N. A.; Pitarka, A.

    2017-12-01

    We are running high-performance computing (HPC) simulations of ground motions for large (magnitude, M=6.5-7.0) earthquakes in the near-fault region (steel moment frame buildings throughout the near-fault domain. For ground motions, we are using SW4, a fourth order summation-by-parts finite difference time-domain code running on 10,000-100,000's of cores. Earthquake ruptures are generated using the Graves and Pitarka (2017) method. We validated ground motion intensity measurements against Ground Motion Prediction Equations. We considered two events (M=6.5 and 7.0) for vertical strike-slip ruptures with three-dimensional (3D) basin structures, including stochastic heterogeneity. We have also considered M7.0 scenarios for a Hayward Fault rupture scenario which effects the San Francisco Bay Area and northern California using both 1D and 3D earth structure. Dynamic, inelastic response of canonical buildings is computed with the NEVADA, a nonlinear, finite-deformation finite element code. Canonical buildings include 3-, 9-, 20- and 40-story steel moment frame buildings. Damage potential is tracked by the peak inter-story drift (PID) ratio, which measures the maximum displacement between adjacent floors of the building and is strongly correlated with damage. PID ratios greater 1.0 generally indicate non-linear response and permanent deformation of the structure. We also track roof displacement to identify permanent deformation. PID (damage) for a given earthquake scenario (M, slip distribution, hypocenter) is spatially mapped throughout the SW4 domain with 1-2 km resolution. Results show that in the near fault region building damage is correlated with peak ground velocity (PGV), while farther away (> 20 km) it is better correlated with peak ground acceleration (PGA). We also show how simulated ground motions have peaks in the response spectra that shift to longer periods for larger magnitude events and for locations of forward directivity, as has been reported by

  13. High-Performance Networking

    CERN Multimedia

    CERN. Geneva

    2003-01-01

    The series will start with an historical introduction about what people saw as high performance message communication in their time and how that developed to the now to day known "standard computer network communication". It will be followed by a far more technical part that uses the High Performance Computer Network standards of the 90's, with 1 Gbit/sec systems as introduction for an in depth explanation of the three new 10 Gbit/s network and interconnect technology standards that exist already or emerge. If necessary for a good understanding some sidesteps will be included to explain important protocols as well as some necessary details of concerned Wide Area Network (WAN) standards details including some basics of wavelength multiplexing (DWDM). Some remarks will be made concerning the rapid expanding applications of networked storage.

  14. Inulin in Medicinal Plants (IV) : Reversed-Phase High-Performance Liquid Chromatography of Inulin after Acetylation : Molecular-Weight Distribution of Inulin in Medicinal Plants

    OpenAIRE

    三野, 芳紀; 筒井, 聡美; 太田, 長世; YOSHIKI, MINO; SATOMI, TSUTSUI; NAGAYO, OTA; 大阪薬科大学; 大阪薬科大学; 大阪薬科大学; Osaka College of Pharmacy; Osaka College of Pharmacy; Osaka College of Pharmacy

    1985-01-01

    Reversed-phase high-performance liquid chromatography coupled with pre-acetylation enabled acculate molecular-weight assay of inulin in medicinal plants to be conducted. The results clearly showed that the molecular-weight distribution of inulin varied depending on the stage of growth: Small molecular weight inulin polymers were detected in large quantity in the earlier growth stage whereas large molecular weight inulin polymers at the flowering and post flowering period.

  15. High performance architecture design for large scale fibre-optic sensor arrays using distributed EDFAs and hybrid TDM/DWDM

    Science.gov (United States)

    Liao, Yi; Austin, Ed; Nash, Philip J.; Kingsley, Stuart A.; Richardson, David J.

    2013-09-01

    A distributed amplified dense wavelength division multiplexing (DWDM) array architecture is presented for interferometric fibre-optic sensor array systems. This architecture employs a distributed erbium-doped fibre amplifier (EDFA) scheme to decrease the array insertion loss, and employs time division multiplexing (TDM) at each wavelength to increase the number of sensors that can be supported. The first experimental demonstration of this system is reported including results which show the potential for multiplexing and interrogating up to 4096 sensors using a single telemetry fibre pair with good system performance. The number can be increased to 8192 by using dual pump sources.

  16. Study on High Performance of MPI-Based Parallel FDTD from WorkStation to Super Computer Platform

    Directory of Open Access Journals (Sweden)

    Z. L. He

    2012-01-01

    Full Text Available Parallel FDTD method is applied to analyze the electromagnetic problems of the electrically large targets on super computer. It is well known that the more the number of processors the less computing time consumed. Nevertheless, with the same number of processors, computing efficiency is affected by the scheme of the MPI virtual topology. Then, the influence of different virtual topology schemes on parallel performance of parallel FDTD is studied in detail. The general rules are presented on how to obtain the highest efficiency of parallel FDTD algorithm by optimizing MPI virtual topology. To show the validity of the presented method, several numerical results are given in the later part. Various comparisons are made and some useful conclusions are summarized.

  17. Distributed fiber optic sensor-enhanced detection and prediction of shrinkage-induced delamination of ultra-high-performance concrete overlay

    Science.gov (United States)

    Bao, Yi; Valipour, Mahdi; Meng, Weina; Khayat, Kamal H.; Chen, Genda

    2017-08-01

    This study develops a delamination detection system for smart ultra-high-performance concrete (UHPC) overlays using a fully distributed fiber optic sensor. Three 450 mm (length) × 200 mm (width) × 25 mm (thickness) UHPC overlays were cast over an existing 200 mm thick concrete substrate. The initiation and propagation of delamination due to early-age shrinkage of the UHPC overlay were detected as sudden increases and their extension in spatial distribution of shrinkage-induced strains measured from the sensor based on pulse pre-pump Brillouin optical time domain analysis. The distributed sensor is demonstrated effective in detecting delamination openings from microns to hundreds of microns. A three-dimensional finite element model with experimental material properties is proposed to understand the complete delamination process measured from the distributed sensor. The model is validated using the distributed sensor data. The finite element model with cohesive elements for the overlay-substrate interface can predict the complete delamination process.

  18. Impossibility results for distributed computing

    CERN Document Server

    Attiya, Hagit

    2014-01-01

    To understand the power of distributed systems, it is necessary to understand their inherent limitations: what problems cannot be solved in particular systems, or without sufficient resources (such as time or space). This book presents key techniques for proving such impossibility results and applies them to a variety of different problems in a variety of different system models. Insights gained from these results are highlighted, aspects of a problem that make it difficult are isolated, features of an architecture that make it inadequate for solving certain problems efficiently are identified

  19. LHCb: LHCb Distributed Computing Operations

    CERN Multimedia

    Stagni, F

    2011-01-01

    The proliferation of tools for monitoring both activities and infrastructure, together with the pressing need for prompt reaction in case of problems impacting data taking, data reconstruction, data reprocessing and user analysis brought to the need of better organizing the huge amount of information available. The monitoring system for the LHCb Grid Computing relies on many heterogeneous and independent sources of information offering different views for a better understanding of problems while an operations team and defined procedures have been put in place to handle them. This work summarizes the state-of-the-art of LHCb Grid operations emphasizing the reasons that brought to various choices and what are the tools currently in use to run our daily activities. We highlight the most common problems experienced across years of activities on the WLCG infrastructure, the services with their criticality, the procedures in place, the relevant metrics and the tools available and the ones still missing.

  20. Distributed computing by oblivious mobile robots

    CERN Document Server

    Flocchini, Paola; Santoro, Nicola

    2012-01-01

    The study of what can be computed by a team of autonomous mobile robots, originally started in robotics and AI, has become increasingly popular in theoretical computer science (especially in distributed computing), where it is now an integral part of the investigations on computability by mobile entities. The robots are identical computational entities located and able to move in a spatial universe; they operate without explicit communication and are usually unable to remember the past; they are extremely simple, with limited resources, and individually quite weak. However, collectively the ro

  1. Distributed computer systems theory and practice

    CERN Document Server

    Zedan, H S M

    2014-01-01

    Distributed Computer Systems: Theory and Practice is a collection of papers dealing with the design and implementation of operating systems, including distributed systems, such as the amoeba system, argus, Andrew, and grapevine. One paper discusses the concepts and notations for concurrent programming, particularly language notation used in computer programming, synchronization methods, and also compares three classes of languages. Another paper explains load balancing or load redistribution to improve system performance, namely, static balancing and adaptive load balancing. For program effici

  2. CMS distributed computing workflow experience

    Science.gov (United States)

    Adelman-McCarthy, Jennifer; Gutsche, Oliver; Haas, Jeffrey D.; Prosper, Harrison B.; Dutta, Valentina; Gomez-Ceballos, Guillelmo; Hahn, Kristian; Klute, Markus; Mohapatra, Ajit; Spinoso, Vincenzo; Kcira, Dorian; Caudron, Julien; Liao, Junhui; Pin, Arnaud; Schul, Nicolas; De Lentdecker, Gilles; McCartin, Joseph; Vanelderen, Lukas; Janssen, Xavier; Tsyganov, Andrey; Barge, Derek; Lahiff, Andrew

    2011-12-01

    The vast majority of the CMS Computing capacity, which is organized in a tiered hierarchy, is located away from CERN. The 7 Tier-1 sites archive the LHC proton-proton collision data that is initially processed at CERN. These sites provide access to all recorded and simulated data for the Tier-2 sites, via wide-area network (WAN) transfers. All central data processing workflows are executed at the Tier-1 level, which contain re-reconstruction and skimming workflows of collision data as well as reprocessing of simulated data to adapt to changing detector conditions. This paper describes the operation of the CMS processing infrastructure at the Tier-1 level. The Tier-1 workflows are described in detail. The operational optimization of resource usage is described. In particular, the variation of different workflows during the data taking period of 2010, their efficiencies and latencies as well as their impact on the delivery of physics results is discussed and lessons are drawn from this experience. The simulation of proton-proton collisions for the CMS experiment is primarily carried out at the second tier of the CMS computing infrastructure. Half of the Tier-2 sites of CMS are reserved for central Monte Carlo (MC) production while the other half is available for user analysis. This paper summarizes the large throughput of the MC production operation during the data taking period of 2010 and discusses the latencies and efficiencies of the various types of MC production workflows. We present the operational procedures to optimize the usage of available resources and we the operational model of CMS for including opportunistic resources, such as the larger Tier-3 sites, into the central production operation.

  3. CMS distributed computing workflow experience

    International Nuclear Information System (INIS)

    Adelman-McCarthy, Jennifer; Gutsche, Oliver; Haas, Jeffrey D; Prosper, Harrison B; Dutta, Valentina; Gomez-Ceballos, Guillelmo; Hahn, Kristian; Klute, Markus; Mohapatra, Ajit; Spinoso, Vincenzo; Kcira, Dorian; Caudron, Julien; Liao Junhui; Pin, Arnaud; Schul, Nicolas; Lentdecker, Gilles De; McCartin, Joseph; Vanelderen, Lukas; Janssen, Xavier; Tsyganov, Andrey

    2011-01-01

    The vast majority of the CMS Computing capacity, which is organized in a tiered hierarchy, is located away from CERN. The 7 Tier-1 sites archive the LHC proton-proton collision data that is initially processed at CERN. These sites provide access to all recorded and simulated data for the Tier-2 sites, via wide-area network (WAN) transfers. All central data processing workflows are executed at the Tier-1 level, which contain re-reconstruction and skimming workflows of collision data as well as reprocessing of simulated data to adapt to changing detector conditions. This paper describes the operation of the CMS processing infrastructure at the Tier-1 level. The Tier-1 workflows are described in detail. The operational optimization of resource usage is described. In particular, the variation of different workflows during the data taking period of 2010, their efficiencies and latencies as well as their impact on the delivery of physics results is discussed and lessons are drawn from this experience. The simulation of proton-proton collisions for the CMS experiment is primarily carried out at the second tier of the CMS computing infrastructure. Half of the Tier-2 sites of CMS are reserved for central Monte Carlo (MC) production while the other half is available for user analysis. This paper summarizes the large throughput of the MC production operation during the data taking period of 2010 and discusses the latencies and efficiencies of the various types of MC production workflows. We present the operational procedures to optimize the usage of available resources and we the operational model of CMS for including opportunistic resources, such as the larger Tier-3 sites, into the central production operation.

  4. The smallest cells pose the biggest problems: high-performance computing and the analysis of metagenome sequence data

    International Nuclear Information System (INIS)

    Edwards, R A

    2008-01-01

    New high-throughput DNA sequencing technologies have revolutionized how scientists study the organisms around us. In particular, microbiology - the study of the smallest, unseen organisms that pervade our lives - has embraced these new techniques to characterize and analyze the cellular constituents and use this information to develop novel tools, techniques, and therapeutics. So-called next-generation DNA sequencing platforms have resulted in huge increases in the amount of raw data that can be rapidly generated. Argonne National Laboratory developed the premier platform for the analysis of this new data (mg-rast) that is used by microbiologists worldwide. This paper uses the accounting from the computational analysis of more than 10,000,000,000 bp of DNA sequence data, describes an analysis of the advanced computational requirements, and suggests the level of analysis that will be essential as microbiologists move to understand how these tiny organisms affect our every day lives. The results from this analysis indicate that data analysis is a linear problem, but that most analyses are held up in queues. With sufficient resources, computations could be completed in a few hours for a typical dataset. These data also suggest execution times that delimit timely completion of computational analyses, and provide bounds for problematic processes

  5. Designing a Scalable Fault Tolerance Model for High Performance Computational Chemistry: A Case Study with Coupled Cluster Perturbative Triples.

    Science.gov (United States)

    van Dam, Hubertus J J; Vishnu, Abhinav; de Jong, Wibe A

    2011-01-11

    In the past couple of decades, the massive computational power provided by the most modern supercomputers has resulted in simulation of higher-order computational chemistry methods, previously considered intractable. As the system sizes continue to increase, the computational chemistry domain continues to escalate this trend using parallel computing with programming models such as Message Passing Interface (MPI) and Partitioned Global Address Space (PGAS) programming models such as Global Arrays. The ever increasing scale of these supercomputers comes at a cost of reduced Mean Time Between Failures (MTBF), currently on the order of days and projected to be on the order of hours for upcoming extreme scale systems. While traditional disk-based check pointing methods are ubiquitous for storing intermediate solutions, they suffer from high overhead of writing and recovering from checkpoints. In practice, checkpointing itself often brings the system down. Clearly, methods beyond checkpointing are imperative to handling the aggravating issue of reducing MTBF. In this paper, we address this challenge by designing and implementing an efficient fault tolerant version of the Coupled Cluster (CC) method with NWChem, using in-memory data redundancy. We present the challenges associated with our design, including an efficient data storage model, maintenance of at least one consistent data copy, and the recovery process. Our performance evaluation without faults shows that the current design exhibits a small overhead. In the presence of a simulated fault, the proposed design incurs negligible overhead in comparison to the state of the art implementation without faults.

  6. ATLAS Distributed Computing in LHC Run2

    CERN Document Server

    Campana, Simone; The ATLAS collaboration

    2015-01-01

    The ATLAS Distributed Computing infrastructure has evolved after the first period of LHC data taking in order to cope with the challenges of the upcoming LHC Run2. An increased data rate and computing demands of the Monte-Carlo simulation, as well as new approaches to ATLAS analysis, dictated a more dynamic workload management system (ProdSys2) and data management system (Rucio), overcoming the boundaries imposed by the design of the old computing model. In particular, the commissioning of new central computing system components was the core part of the migration toward the flexible computing model. The flexible computing utilization exploring the opportunistic resources such as HPC, cloud, and volunteer computing is embedded in the new computing model, the data access mechanisms have been enhanced with the remote access, and the network topology and performance is deeply integrated into the core of the system. Moreover a new data management strategy, based on defined lifetime for each dataset, has been defin...

  7. Mobile Agents in Networking and Distributed Computing

    CERN Document Server

    Cao, Jiannong

    2012-01-01

    The book focuses on mobile agents, which are computer programs that can autonomously migrate between network sites. This text introduces the concepts and principles of mobile agents, provides an overview of mobile agent technology, and focuses on applications in networking and distributed computing.

  8. A Software Rejuvenation Framework for Distributed Computing

    Science.gov (United States)

    Chau, Savio

    2009-01-01

    A performability-oriented conceptual framework for software rejuvenation has been constructed as a means of increasing levels of reliability and performance in distributed stateful computing. As used here, performability-oriented signifies that the construction of the framework is guided by the concept of analyzing the ability of a given computing system to deliver services with gracefully degradable performance. The framework is especially intended to support applications that involve stateful replicas of server computers.

  9. CMS Distributed Computing Workflow Experience

    CERN Document Server

    Haas, Jeffrey David

    2010-01-01

    The vast majority of the CMS Computing capacity, which is organized in a tiered hierarchy, is located away from CERN. The 7 Tier-1 sites archive the LHC proton-proton collision data that is initially processed at CERN. These sites provide access to all recorded and simulated data for the Tier-2 sites, via wide-area network (WAN) transfers. All central data processing workflows are executed at the Tier-1 level, which contain re-reconstruction and skimming workflows of collision data as well as reprocessing of simulated data to adapt to changing detector conditions. This paper describes the operation of the CMS processing infrastructure at the Tier-1 level. The Tier-1 workflows are described in detail. The operational optimization of resource usage is described. In particular, the variation of different workflows during the data taking period of 2010, their efficiencies and latencies as well as their impact on the delivery of physics results is discussed and lessons are drawn from this experience. The simul...

  10. Re-Form: FPGA-Powered True Codesign Flow for High-Performance Computing In The Post-Moore Era

    Energy Technology Data Exchange (ETDEWEB)

    Cappello, Franck; Yoshii, Kazutomo; Finkel, Hal; Cong, Jason

    2016-11-14

    Multicore scaling will end soon because of practical power limits. Dark silicon is becoming a major issue even more than the end of Moore’s law. In the post-Moore era, the energy efficiency of computing will be a major concern. FPGAs could be a key to maximizing the energy efficiency. In this paper we address severe challenges in the adoption of FPGA in HPC and describe “Re-form,” an FPGA-powered codesign flow.

  11. Hybrid GPU-CPU adaptive precision ray-triangle intersection tests for robust high-performance GPU dosimetry computations

    International Nuclear Information System (INIS)

    Perrotte, Lancelot; Bodin, Bruno; Chodorge, Laurent

    2011-01-01

    Before an intervention on a nuclear site, it is essential to study different scenarios to identify the less dangerous one for the operator. Therefore, it is mandatory to dispose of an efficient dosimetry simulation code with accurate results. One classical method in radiation protection is the straight-line attenuation method with build-up factors. In the case of 3D industrial scenes composed of meshes, the computation cost resides in the fast computation of all of the intersections between the rays and the triangles of the scene. Efficient GPU algorithms have already been proposed, that enable dosimetry calculation for a huge scene (800000 rays, 800000 triangles) in a fraction of second. But these algorithms are not robust: because of the rounding caused by floating-point arithmetic, the numerical results of the ray-triangle intersection tests can differ from the expected mathematical results. In worst case scenario, this can lead to a computed dose rate dramatically inferior to the real dose rate to which the operator is exposed. In this paper, we present a hybrid GPU-CPU algorithm to manage adaptive precision floating-point arithmetic. This algorithm allows robust ray-triangle intersection tests, with very small loss of performance (less than 5 % overhead), and without any need for scene-dependent tuning. (author)

  12. High performance computing enabling exhaustive analysis of higher order single nucleotide polymorphism interaction in Genome Wide Association Studies.

    Science.gov (United States)

    Goudey, Benjamin; Abedini, Mani; Hopper, John L; Inouye, Michael; Makalic, Enes; Schmidt, Daniel F; Wagner, John; Zhou, Zeyu; Zobel, Justin; Reumann, Matthias

    2015-01-01

    Genome-wide association studies (GWAS) are a common approach for systematic discovery of single nucleotide polymorphisms (SNPs) which are associated with a given disease. Univariate analysis approaches commonly employed may miss important SNP associations that only appear through multivariate analysis in complex diseases. However, multivariate SNP analysis is currently limited by its inherent computational complexity. In this work, we present a computational framework that harnesses supercomputers. Based on our results, we estimate a three-way interaction analysis on 1.1 million SNP GWAS data requiring over 5.8 years on the full "Avoca" IBM Blue Gene/Q installation at the Victorian Life Sciences Computation Initiative. This is hundreds of times faster than estimates for other CPU based methods and four times faster than runtimes estimated for GPU methods, indicating how the improvement in the level of hardware applied to interaction analysis may alter the types of analysis that can be performed. Furthermore, the same analysis would take under 3 months on the currently largest IBM Blue Gene/Q supercomputer "Sequoia" at the Lawrence Livermore National Laboratory assuming linear scaling is maintained as our results suggest. Given that the implementation used in this study can be further optimised, this runtime means it is becoming feasible to carry out exhaustive analysis of higher order interaction studies on large modern GWAS.

  13. Distributed simulation of large computer systems

    International Nuclear Information System (INIS)

    Marzolla, M.

    2001-01-01

    Sequential simulation of large complex physical systems is often regarded as a computationally expensive task. In order to speed-up complex discrete-event simulations, the paradigm of Parallel and Distributed Discrete Event Simulation (PDES) has been introduced since the late 70s. The authors analyze the applicability of PDES to the modeling and analysis of large computer system; such systems are increasingly common in the area of High Energy and Nuclear Physics, because many modern experiments make use of large 'compute farms'. Some feasibility tests have been performed on a prototype distributed simulator

  14. Exploring the meteorological potential for planning a high performance European electricity super-grid: optimal power capacity distribution among countries

    Science.gov (United States)

    Santos-Alamillos, Francisco J.; Brayshaw, David J.; Methven, John; Thomaidis, Nikolaos S.; Ruiz-Arias, José A.; Pozo-Vázquez, David

    2017-11-01

    The concept of a European super-grid for electricity presents clear advantages for a reliable and affordable renewable power production (photovoltaics and wind). Based on the mean-variance portfolio optimization analysis, we explore optimal scenarios for the allocation of new renewable capacity at national level in order to provide to energy decision-makers guidance about which regions should be mostly targeted to either maximize total production or reduce its day-to-day variability. The results show that the existing distribution of renewable generation capacity across Europe is far from optimal: i.e. a ‘better’ spatial distribution of resources could have been achieved with either a ~31% increase in mean power supply (for the same level of day-to-day variability) or a ~37.5% reduction in day-to-day variability (for the same level of mean productivity). Careful planning of additional increments in renewable capacity at the European level could, however, act to significantly ameliorate this deficiency. The choice of where to deploy resources depends, however, on the objective being pursued—if the goal is to maximize average output, then new capacity is best allocated in the countries with highest resources, whereas investment in additional capacity in a north/south dipole pattern across Europe would act to most reduce daily variations and thus decrease the day-to-day volatility of renewable power supply.

  15. High Performance Computing Application: Solar Dynamo Model Project II, Corona and Heliosphere Component Initialization, Integration and Validation

    Science.gov (United States)

    2015-06-24

    distribution at this level replaced a constant temperature assumption, and density was calculated locally through a balance of radiation loss, thermal...G. References Altschuler, M. D., and G. Newkirk, Jr. (1969), Magnetic fields and the structure of the solar corona. I: Methods of calculating ...Weather, 11, 17-33, doi:10.1029/2012SW000853. Nakamizo, A., T. Tanaka, Y. Kubo , S. Kamei, H. Shimazu, and H. Shinagawa (2009), Development of the

  16. ATLAS Distributed Computing: Experience and Evolution

    CERN Document Server

    Nairz, A; The ATLAS collaboration

    2013-01-01

    The ATLAS experiment has just concluded its first running period which commenced in 2010. After two years of remarkable performance from the LHC and ATLAS, the experiment has accumulated more than 25 fb-1 of data. The total volume of beam and simulated data products exceeds 100 PB distributed across more than 150 computing centers around the world, managed by the experiment's distributed data management system. These sites have provided up to 150,000 computing cores to ATLAS's global production and analysis processing system, enabling a rich physics program including the discovery of the Higgs-like boson in 2012. The wealth of accumulated experience in global data-intensive computing at this massive scale, and the considerably more challenging requirements of LHC computing from 2014 when the LHC resumes operation, are driving a comprehensive design and development cycle to prepare a revised computing model together with data processing and management systems able to meet the demands of higher trigger rates, e...

  17. ATLAS distributed computing: experience and evolution

    CERN Document Server

    Nairz, A; The ATLAS collaboration

    2014-01-01

    The ATLAS experiment has just concluded its first running period which commenced in 2010. After two years of remarkable performance from the LHC and ATLAS, the experiment has accumulated more than 25/fb of data. The total volume of beam and simulated data products exceeds 100~PB distributed across more than 150 computing centres around the world, managed by the experiment's distributed data management system. These sites have provided up to 150,000 computing cores to ATLAS's global production and analysis processing system, enabling a rich physics programme including the discovery of the Higgs-like boson in 2012. The wealth of accumulated experience in global data-intensive computing at this massive scale, and the considerably more challenging requirements of LHC computing from 2015 when the LHC resumes operation, are driving a comprehensive design and development cycle to prepare a revised computing model together with data processing and management systems able to meet the demands of higher trigger rates, e...

  18. Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation and Completion of Episodic Information.

    Energy Technology Data Exchange (ETDEWEB)

    Aimone, James Bradley; Bernard, Michael Lewis; Vineyard, Craig Michael; Verzi, Stephen Joseph.

    2014-10-01

    Adult neurogenesis in the hippocampus region of the brain is a neurobiological process that is believed to contribute to the brain's advanced abilities in complex pattern recognition and cognition. Here, we describe how realistic scale simulations of the neurogenesis process can offer both a unique perspective on the biological relevance of this process and confer computational insights that are suggestive of novel machine learning techniques. First, supercomputer based scaling studies of the neurogenesis process demonstrate how a small fraction of adult-born neurons have a uniquely larger impact in biologically realistic scaled networks. Second, we describe a novel technical approach by which the information content of ensembles of neurons can be estimated. Finally, we illustrate several examples of broader algorithmic impact of neurogenesis, including both extending existing machine learning approaches and novel approaches for intelligent sensing.

  19. Pattern recognition, neural networks, genetic algorithms and high performance computing in nuclear reactor diagnostics. Results and perspectives

    International Nuclear Information System (INIS)

    Dzwinel, W.; Pepyolyshev, N.

    1996-01-01

    The main goal of this paper is the presentation of our experience in development of the diagnostic system for the IBR-2 (Russia - Dubna) nuclear reactor. The authors show the principal results of the system modifications to make it work more reliable and much faster. The former needs the adaptation of new techniques of data processing, the latter, implementation of the newest computational facilities. The results of application of the clustering techniques and a method of visualization of the multi-dimensional information directly on the operator display are presented. The experiences with neural nets, used for prediction of the reactor operation, are discussed. The genetic algorithms were also tested, to reduce the quantity of data nd extracting the most informative components of the analyzed spectra. (authors)

  20. Viscoelastic Waves Simulation in a Blocky Medium with Fluid-Saturated Interlayers Using High-Performance Computing

    Science.gov (United States)

    Sadovskii, Vladimir; Sadovskaya, Oxana

    2017-04-01

    A thermodynamically consistent approach to the description of linear and nonlinear wave processes in a blocky medium, which consists of a large number of elastic blocks interacting with each other via pliant interlayers, is proposed. The mechanical properties of interlayers are defined by means of the rheological schemes of different levels of complexity. Elastic interaction between the blocks is considered in the framework of the linear elasticity theory [1]. The effects of viscoelastic shear in the interblock interlayers are taken into consideration using the Pointing-Thomson rheological scheme. The model of an elastic porous material is used in the interlayers, where the pores collapse if an abrupt compressive stress is applied. On the basis of the Biot equations for a fluid-saturated porous medium, a new mathematical model of a blocky medium is worked out, in which the interlayers provide a convective fluid motion due to the external perturbations. The collapse of pores is modeled within the generalized rheological approach, wherein the mechanical properties of a material are simulated using four rheological elements. Three of them are the traditional elastic, viscous and plastic elements, the fourth element is the so-called rigid contact [2], which is used to describe the behavior of materials with different resistance to tension and compression. Thermodynamic consistency of the equations in interlayers with the equations in blocks guarantees fulfillment of the energy conservation law for a blocky medium in a whole, i.e. kinetic and potential energy of the system is the sum of kinetic and potential energies of the blocks and interlayers. As a result of discretization of the equations of the model, robust computational algorithm is constructed, that is stable because of the thermodynamic consistency of the finite difference equations at a discrete level. The splitting method by the spatial variables and the Godunov gap decay scheme are used in the blocks, the

  1. Leveraging the Power of High Performance Computing for Next Generation Sequencing Data Analysis: Tricks and Twists from a High Throughput Exome Workflow

    Science.gov (United States)

    Wonczak, Stephan; Thiele, Holger; Nieroda, Lech; Jabbari, Kamel; Borowski, Stefan; Sinha, Vishal; Gunia, Wilfried; Lang, Ulrich; Achter, Viktor; Nürnberg, Peter

    2015-01-01

    Next generation sequencing (NGS) has been a great success and is now a standard method of research in the life sciences. With this technology, dozens of whole genomes or hundreds of exomes can be sequenced in rather short time, producing huge amounts of data. Complex bioinformatics analyses are required to turn these data into scientific findings. In order to run these analyses fast, automated workflows implemented on high performance computers are state of the art. While providing sufficient compute power and storage to meet the NGS data challenge, high performance computing (HPC) systems require special care when utilized for high throughput processing. This is especially true if the HPC system is shared by different users. Here, stability, robustness and maintainability are as important for automated workflows as speed and throughput. To achieve all of these aims, dedicated solutions have to be developed. In this paper, we present the tricks and twists that we utilized in the implementation of our exome data processing workflow. It may serve as a guideline for other high throughput data analysis projects using a similar infrastructure. The code implementing our solutions is provided in the supporting information files. PMID:25942438

  2. Distributed quantum computing with single photon sources

    International Nuclear Information System (INIS)

    Beige, A.; Kwek, L.C.

    2005-01-01

    Full text: Distributed quantum computing requires the ability to perform nonlocal gate operations between the distant nodes (stationary qubits) of a large network. To achieve this, it has been proposed to interconvert stationary qubits with flying qubits. In contrast to this, we show that distributed quantum computing only requires the ability to encode stationary qubits into flying qubits but not the conversion of flying qubits into stationary qubits. We describe a scheme for the realization of an eventually deterministic controlled phase gate by performing measurements on pairs of flying qubits. Our scheme could be implemented with a linear optics quantum computing setup including sources for the generation of single photons on demand, linear optics elements and photon detectors. In the presence of photon loss and finite detector efficiencies, the scheme could be used to build large cluster states for one way quantum computing with a high fidelity. (author)

  3. Satellite Remote Sensing of Cropland Characteristics in 30m Resolution: The First North American Continental-Scale Classification on High Performance Computing Platforms

    Science.gov (United States)

    Massey, Richard

    Cropland characteristics and accurate maps of their spatial distribution are required to develop strategies for global food security by continental-scale assessments and agricultural land use policies. North America is the major producer and exporter of coarse grains, wheat, and other crops. While cropland characteristics such as crop types are available at country-scales in North America, however, at continental-scale cropland products are lacking at fine sufficient resolution such as 30m. Additionally, applications of automated, open, and rapid methods to map cropland characteristics over large areas without the need of ground samples are needed on efficient high performance computing platforms for timely and long-term cropland monitoring. In this study, I developed novel, automated, and open methods to map cropland extent, crop intensity, and crop types in the North American continent using large remote sensing datasets on high-performance computing platforms. First, a novel method was developed in this study to fuse pixel-based classification of continental-scale Landsat data using Random Forest algorithm available on Google Earth Engine cloud computing platform with an object-based classification approach, recursive hierarchical segmentation (RHSeg) to map cropland extent at continental scale. Using the fusion method, a continental-scale cropland extent map for North America at 30m spatial resolution for the nominal year 2010 was produced. In this map, the total cropland area for North America was estimated at 275.2 million hectares (Mha). This map was assessed for accuracy using randomly distributed samples derived from United States Department of Agriculture (USDA) cropland data layer (CDL), Agriculture and Agri-Food Canada (AAFC) annual crop inventory (ACI), Servicio de Informacion Agroalimentaria y Pesquera (SIAP), Mexico's agricultural boundaries, and photo-interpretation of high-resolution imagery. The overall accuracies of the map are 93.4% with a

  4. Distributed computing environment for Mine Warfare Command

    OpenAIRE

    Pritchard, Lane L.

    1993-01-01

    Approved for public release; distribution is unlimited. The Mine Warfare Command in Charleston, South Carolina has been converting its information systems architecture from a centralized mainframe based system to a decentralized network of personal computers over the past several years. This thesis analyzes the progress Of the evolution as of May of 1992. The building blocks of a distributed architecture are discussed in relation to the choices the Mine Warfare Command has made to date. Ar...

  5. ATLAS distributed computing: experience and evolution

    International Nuclear Information System (INIS)

    Nairz, A

    2014-01-01

    The ATLAS experiment has just concluded its first running period which commenced in 2010. After two years of remarkable performance from the LHC and ATLAS, the experiment has accumulated more than 25 fb −1 of data. The total volume of beam and simulated data products exceeds 100 PB distributed across more than 150 computing centres around the world, managed by the experiment's distributed data management system. These sites have provided up to 150,000 computing cores to ATLAS's global production and analysis processing system, enabling a rich physics programme including the discovery of the Higgs-like boson in 2012. The wealth of accumulated experience in global data-intensive computing at this massive scale, and the considerably more challenging requirements of LHC computing from 2015 when the LHC resumes operation, are driving a comprehensive design and development cycle to prepare a revised computing model together with data processing and management systems able to meet the demands of higher trigger rates, energies and event complexities. An essential requirement will be the efficient utilisation of current and future processor technologies as well as a broad range of computing platforms, including supercomputing and cloud resources. We will report on experience gained thus far and our progress in preparing ATLAS computing for the future

  6. Intelligent Distributed Computing VI : Proceedings of the 6th International Symposium on Intelligent Distributed Computing

    CERN Document Server

    Badica, Costin; Malgeri, Michele; Unland, Rainer

    2013-01-01

    This book represents the combined peer-reviewed proceedings of the Sixth International Symposium on Intelligent Distributed Computing -- IDC~2012, of the International Workshop on Agents for Cloud -- A4C~2012 and of the Fourth International Workshop on Multi-Agent Systems Technology and Semantics -- MASTS~2012. All the events were held in Calabria, Italy during September 24-26, 2012. The 37 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: adaptive and autonomous distributed systems, agent programming, ambient assisted living systems, business process modeling and verification, cloud computing, coalition formation, decision support systems, distributed optimization and constraint satisfaction, gesture recognition, intelligent energy management in WSNs, intelligent logistics, machine learning, mobile agents, parallel and distributed computational intelligence, parallel evolutionary computing, trus...

  7. System Software and Tools for High Performance Computing Environments: A report on the findings of the Pasadena Workshop, April 14--16, 1992

    Energy Technology Data Exchange (ETDEWEB)

    Sterling, T. [Universities Space Research Association, Washington, DC (United States); Messina, P. [Jet Propulsion Lab., Pasadena, CA (United States); Chen, M. [Yale Univ., New Haven, CT (United States)] [and others

    1993-04-01

    The Pasadena Workshop on System Software and Tools for High Performance Computing Environments was held at the Jet Propulsion Laboratory from April 14 through April 16, 1992. The workshop was sponsored by a number of Federal agencies committed to the advancement of high performance computing (HPC) both as a means to advance their respective missions and as a national resource to enhance American productivity and competitiveness. Over a hundred experts in related fields from industry, academia, and government were invited to participate in this effort to assess the current status of software technology in support of HPC systems. The overall objectives of the workshop were to understand the requirements and current limitations of HPC software technology and to contribute to a basis for establishing new directions in research and development for software technology in HPC environments. This report includes reports written by the participants of the workshop`s seven working groups. Materials presented at the workshop are reproduced in appendices. Additional chapters summarize the findings and analyze their implications for future directions in HPC software technology development.

  8. High performance data transfer

    Science.gov (United States)

    Cottrell, R.; Fang, C.; Hanushevsky, A.; Kreuger, W.; Yang, W.

    2017-10-01

    The exponentially increasing need for high speed data transfer is driven by big data, and cloud computing together with the needs of data intensive science, High Performance Computing (HPC), defense, the oil and gas industry etc. We report on the Zettar ZX software. This has been developed since 2013 to meet these growing needs by providing high performance data transfer and encryption in a scalable, balanced, easy to deploy and use way while minimizing power and space utilization. In collaboration with several commercial vendors, Proofs of Concept (PoC) consisting of clusters have been put together using off-the- shelf components to test the ZX scalability and ability to balance services using multiple cores, and links. The PoCs are based on SSD flash storage that is managed by a parallel file system. Each cluster occupies 4 rack units. Using the PoCs, between clusters we have achieved almost 200Gbps memory to memory over two 100Gbps links, and 70Gbps parallel file to parallel file with encryption over a 5000 mile 100Gbps link.

  9. ATLAS Distributed Computing in LHC Run2

    International Nuclear Information System (INIS)

    Campana, Simone

    2015-01-01

    The ATLAS Distributed Computing infrastructure has evolved after the first period of LHC data taking in order to cope with the challenges of the upcoming LHC Run-2. An increase in both the data rate and the computing demands of the Monte-Carlo simulation, as well as new approaches to ATLAS analysis, dictated a more dynamic workload management system (Prodsys-2) and data management system (Rucio), overcoming the boundaries imposed by the design of the old computing model. In particular, the commissioning of new central computing system components was the core part of the migration toward a flexible computing model. A flexible computing utilization exploring the use of opportunistic resources such as HPC, cloud, and volunteer computing is embedded in the new computing model; the data access mechanisms have been enhanced with the remote access, and the network topology and performance is deeply integrated into the core of the system. Moreover, a new data management strategy, based on a defined lifetime for each dataset, has been defined to better manage the lifecycle of the data. In this note, an overview of an operational experience of the new system and its evolution is presented. (paper)

  10. Research computing in a distributed cloud environment

    International Nuclear Information System (INIS)

    Fransham, K; Agarwal, A; Armstrong, P; Bishop, A; Charbonneau, A; Desmarais, R; Hill, N; Gable, I; Gaudet, S; Goliath, S; Impey, R; Leavett-Brown, C; Ouellete, J; Paterson, M; Pritchet, C; Penfold-Brown, D; Podaima, W; Schade, D; Sobie, R J

    2010-01-01

    The recent increase in availability of Infrastructure-as-a-Service (IaaS) computing clouds provides a new way for researchers to run complex scientific applications. However, using cloud resources for a large number of research jobs requires significant effort and expertise. Furthermore, running jobs on many different clouds presents even more difficulty. In order to make it easy for researchers to deploy scientific applications across many cloud resources, we have developed a virtual machine resource manager (Cloud Scheduler) for distributed compute clouds. In response to a user's job submission to a batch system, the Cloud Scheduler manages the distribution and deployment of user-customized virtual machines across multiple clouds. We describe the motivation for and implementation of a distributed cloud using the Cloud Scheduler that is spread across both commercial and dedicated private sites, and present some early results of scientific data analysis using the system.

  11. 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.

  12. Operation of the ATLAS distributed computing

    CERN Document Server

    Barreiro Megino, Fernando Harald; The ATLAS collaboration

    2018-01-01

    We describe the central operation of the ATLAS distributed computing system. The majority of compute intensive activities within ATLAS are carried out on some 350,000 CPU cores on the Grid, augmented by opportunistic usage of significant HPC and volunteer resources. The increasing scale, and challenging new payloads, demand fine-tuning of operational procedures together with timely developments of the production system. We describe several such developments, motivated directly from operational experience. Optimization of inefficient task requests, from both official production and users, is made possible by automatic detection of payload properties. User education, job shaping or preventative throttling help to increase the overall throughput of the available resources.

  13. Economic Model For a Return on Investment Analysis of United States Government High Performance Computing (HPC) Research and Development (R & D) Investment

    Energy Technology Data Exchange (ETDEWEB)

    Joseph, Earl C. [IDC Research Inc., Framingham, MA (United States); Conway, Steve [IDC Research Inc., Framingham, MA (United States); Dekate, Chirag [IDC Research Inc., Framingham, MA (United States)

    2013-09-30

    This study investigated how high-performance computing (HPC) investments can improve economic success and increase scientific innovation. This research focused on the common good and provided uses for DOE, other government agencies, industry, and academia. The study created two unique economic models and an innovation index: 1 A macroeconomic model that depicts the way HPC investments result in economic advancements in the form of ROI in revenue (GDP), profits (and cost savings), and jobs. 2 A macroeconomic model that depicts the way HPC investments result in basic and applied innovations, looking at variations by sector, industry, country, and organization size. A new innovation index that provides a means of measuring and comparing innovation levels. Key findings of the pilot study include: IDC collected the required data across a broad set of organizations, with enough detail to create these models and the innovation index. The research also developed an expansive list of HPC success stories.

  14. Overview of the ATLAS distributed computing system

    CERN Document Server

    Elmsheuser, Johannes; The ATLAS collaboration

    2018-01-01

    The CERN ATLAS experiment successfully uses a worldwide computing infrastructure to support the physics program during LHC Run 2. The grid workflow system PanDA routinely manages 250 to 500 thousand concurrently running production and analysis jobs to process simulation and detector data. In total more than 300 PB of data is distributed over more than 150 sites in the WLCG and handled by the ATLAS data management system Rucio. To prepare for the ever growing LHC luminosity in future runs new developments are underway to even more efficiently use opportunistic resources such as HPCs and utilize new technologies. This presentation will review and explain the outline and the performance of the ATLAS distributed computing system and give an outlook to new workflow and data management ideas for the beginning of the LHC Run 3.

  15. Decentralized Resource Management in Distributed Computer Systems.

    Science.gov (United States)

    1982-02-01

    directly exchanging user state information. Eventcounts and sequencers correspond to semaphores in the sense that synchronization primitives are used to...and techniques are required to achieve synchronization in distributed computers without reliance on any centralized entity such as a semaphore ...known solutions to the access synchronization problem was Dijkstra’s semaphore [12]. The importance of the semaphore is that it correctly addresses the

  16. High Performance Proactive Digital Forensics

    International Nuclear Information System (INIS)

    Alharbi, Soltan; Traore, Issa; Moa, Belaid; Weber-Jahnke, Jens

    2012-01-01

    With the increase in the number of digital crimes and in their sophistication, High Performance Computing (HPC) is becoming a must in Digital Forensics (DF). According to the FBI annual report, the size of data processed during the 2010 fiscal year reached 3,086 TB (compared to 2,334 TB in 2009) and the number of agencies that requested Regional Computer Forensics Laboratory assistance increasing from 689 in 2009 to 722 in 2010. Since most investigation tools are both I/O and CPU bound, the next-generation DF tools are required to be distributed and offer HPC capabilities. The need for HPC is even more evident in investigating crimes on clouds or when proactive DF analysis and on-site investigation, requiring semi-real time processing, are performed. Although overcoming the performance challenge is a major goal in DF, as far as we know, there is almost no research on HPC-DF except for few papers. As such, in this work, we extend our work on the need of a proactive system and present a high performance automated proactive digital forensic system. The most expensive phase of the system, namely proactive analysis and detection, uses a parallel extension of the iterative z algorithm. It also implements new parallel information-based outlier detection algorithms to proactively and forensically handle suspicious activities. To analyse a large number of targets and events and continuously do so (to capture the dynamics of the system), we rely on a multi-resolution approach to explore the digital forensic space. Data set from the Honeynet Forensic Challenge in 2001 is used to evaluate the system from DF and HPC perspectives.

  17. ATLAS Distributed Computing: Its Central Services core

    CERN Document Server

    Lee, Christopher Jon; The ATLAS collaboration

    2018-01-01

    The ATLAS Distributed Computing (ADC) Project is responsible for the off-line processing of data produced by the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. It facilitates data and workload management for ATLAS computing on the Worldwide LHC Computing Grid (WLCG). ADC Central Services operations (CSops)is a vital part of ADC, responsible for the deployment and configuration of services needed by ATLAS computing and operation of those services on CERN IT infrastructure, providing knowledge of CERN IT services to ATLAS service managers and developers, and supporting them in case of issues. Currently this entails the management of thirty seven different OpenStack projects, with more than five thousand cores allocated for these virtual machines, as well as overseeing the distribution of twenty nine petabytes of storage space in EOS for ATLAS. As the LHC begins to get ready for the next long shut-down, which will bring in many new upgrades to allow for more data to be captured by the on-line syste...

  18. 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 ...

  19. Tom Tabor, the owner of Tabor Communications, presents Wolfgang von Rüden with the Editors Choice Award of HPCwire, which was awarded to CERN for its commitment to educating the public about high-performance computing.

    CERN Multimedia

    Maximilien Brice

    2006-01-01

    Tom Tabor, the owner of Tabor Communications, presents Wolfgang von Rüden with the Editors Choice Award of HPCwire, which was awarded to CERN for its commitment to educating the public about high-performance computing.

  20. Current Capabilities at SNL for the Integration of Small Modular Reactors onto Smart Microgrids Using Sandia's Smart Microgrid Technology High Performance Computing and Advanced Manufacturing.

    Energy Technology Data Exchange (ETDEWEB)

    Rodriguez, Salvador B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-05-01

    Smart grids are a crucial component for enabling the nation’s future energy needs, as part of a modernization effort led by the Department of Energy. Smart grids and smart microgrids are being considered in niche applications, and as part of a comprehensive energy strategy to help manage the nation’s growing energy demands, for critical infrastructures, military installations, small rural communities, and large populations with limited water supplies. As part of a far-reaching strategic initiative, Sandia National Laboratories (SNL) presents herein a unique, three-pronged approach to integrate small modular reactors (SMRs) into microgrids, with the goal of providing economically-competitive, reliable, and secure energy to meet the nation’s needs. SNL’s triad methodology involves an innovative blend of smart microgrid technology, high performance computing (HPC), and advanced manufacturing (AM). In this report, Sandia’s current capabilities in those areas are summarized, as well as paths forward that will enable DOE to achieve its energy goals. In the area of smart grid/microgrid technology, Sandia’s current computational capabilities can model the entire grid, including temporal aspects and cyber security issues. Our tools include system development, integration, testing and evaluation, monitoring, and sustainment.

  1. High-performance size-exclusion chromatography studies on the formation and distribution of polar compounds in camellia seed oil during heating*

    Science.gov (United States)

    Feng, Hong-xia; Sam, Rokayya; Jiang, Lian-zhou; Li, Yang; Cao, Wen-ming

    2016-01-01

    Camellia seed oil (CSO) is rich in oleic acid and has a high number of active components, which give the oil high nutritional value and a variety of biological activity. The aim of the present study was to determine the changes in the content and distribution of total polar compounds (TPC) in CSO during heating. TPC were isolated by means of preparative flash chromatography and further analyzed by high-performance size-exclusion chromatography (HPSEC). The TPC content of CSO increased from 4.74% to 25.29%, showing a significantly lower formation rate as compared to that of extra virgin olive oil (EVOO) and soybean oil (SBO) during heating. Furthermore, heating also resulted in significant differences (P<0.05) in the distribution of TPC among these oils. Though the content of oxidized triacylglycerol dimers, oxidized triacylglycerol oligomers, and oxidized triacylglycerol monomers significantly increased in all these oils, their increased percentages were much less in CSO than those in EVOO, indicating that CSO has a greater ability to resist oxidation. This work may be useful for the food oil industry and consumers in helping to choose the correct oil and to decide on the useful lifetime of the oil. PMID:27819135

  2. Distributed Computing for the Pierre Auger Observatory

    International Nuclear Information System (INIS)

    Chudoba, J.

    2015-01-01

    Pierre Auger Observatory operates the largest system of detectors for ultra-high energy cosmic ray measurements. Comparison of theoretical models of interactions with recorded data requires thousands of computing cores for Monte Carlo simulations. Since 2007 distributed resources connected via EGI grid are successfully used. The first and the second versions of production system based on bash scripts and MySQL database were able to submit jobs to all reliable sites supporting Virtual Organization auger. For many years VO auger belongs to top ten of EGI users based on the total used computing time. Migration of the production system to DIRAC interware started in 2014. Pilot jobs improve efficiency of computing jobs and eliminate problems with small and less reliable sites used for the bulk production. The new system has also possibility to use available resources in clouds. Dirac File Catalog replaced LFC for new files, which are organized in datasets defined via metadata. CVMFS is used for software distribution since 2014. In the presentation we give a comparison of the old and the new production system and report the experience on migrating to the new system. (paper)

  3. Distributed Computing for the Pierre Auger Observatory

    Science.gov (United States)

    Chudoba, J.

    2015-12-01

    Pierre Auger Observatory operates the largest system of detectors for ultra-high energy cosmic ray measurements. Comparison of theoretical models of interactions with recorded data requires thousands of computing cores for Monte Carlo simulations. Since 2007 distributed resources connected via EGI grid are successfully used. The first and the second versions of production system based on bash scripts and MySQL database were able to submit jobs to all reliable sites supporting Virtual Organization auger. For many years VO auger belongs to top ten of EGI users based on the total used computing time. Migration of the production system to DIRAC interware started in 2014. Pilot jobs improve efficiency of computing jobs and eliminate problems with small and less reliable sites used for the bulk production. The new system has also possibility to use available resources in clouds. Dirac File Catalog replaced LFC for new files, which are organized in datasets defined via metadata. CVMFS is used for software distribution since 2014. In the presentation we give a comparison of the old and the new production system and report the experience on migrating to the new system.

  4. Distributed computer control system for reactor optimization

    International Nuclear Information System (INIS)

    Williams, A.H.

    1983-01-01

    At the Oldbury power station a prototype distributed computer control system has been installed. This system is designed to support research and development into improved reactor temperature control methods. This work will lead to the development and demonstration of new optimal control systems for improvement of plant efficiency and increase of generated output. The system can collect plant data from special test instrumentation connected to dedicated scanners and from the station's existing data processing system. The system can also, via distributed microprocessor-based interface units, make adjustments to the desired reactor channel gas exit temperatures. The existing control equipment will then adjust the height of control rods to maintain operation at these temperatures. The design of the distributed system is based on extensive experience with distributed systems for direct digital control, operator display and plant monitoring. The paper describes various aspects of this system, with particular emphasis on: (1) the hierarchal system structure; (2) the modular construction of the system to facilitate installation, commissioning and testing, and to reduce maintenance to module replacement; (3) the integration of the system into the station's existing data processing system; (4) distributed microprocessor-based interfaces to the reactor controls, with extensive security facilities implemented by hardware and software; (5) data transfer using point-to-point and bussed data links; (6) man-machine communication based on VDUs with computer input push-buttons and touch-sensitive screens; and (7) the use of a software system supporting a high-level engineer-orientated programming language, at all levels in the system, together with comprehensive data link management

  5. Pseudo-interactive monitoring in distributed computing

    International Nuclear Information System (INIS)

    Sfiligoi, I.; Bradley, D.; Livny, M.

    2009-01-01

    Distributed computing, and in particular Grid computing, enables physicists to use thousands of CPU days worth of computing every day, by submitting thousands of compute jobs. Unfortunately, a small fraction of such jobs regularly fail; the reasons vary from disk and network problems to bugs in the user code. A subset of these failures result in jobs being stuck for long periods of time. In order to debug such failures, interactive monitoring is highly desirable; users need to browse through the job log files and check the status of the running processes. Batch systems typically don't provide such services; at best, users get job logs at job termination, and even this may not be possible if the job is stuck in an infinite loop. In this paper we present a novel approach of using regular batch system capabilities of Condor to enable users to access the logs and processes of any running job. This does not provide true interactive access, so commands like vi are not viable, but it does allow operations like ls, cat, top, ps, lsof, netstat and dumping the stack of any process owned by the user; we call this pseudo-interactive monitoring. It is worth noting that the same method can be used to monitor Grid jobs in a glidein-based environment. We further believe that the same mechanism could be applied to many other batch systems.

  6. Pseudo-interactive monitoring in distributed computing

    International Nuclear Information System (INIS)

    Sfiligoi, I; Bradley, D; Livny, M

    2010-01-01

    Distributed computing, and in particular Grid computing, enables physicists to use thousands of CPU days worth of computing every day, by submitting thousands of compute jobs. Unfortunately, a small fraction of such jobs regularly fail; the reasons vary from disk and network problems to bugs in the user code. A subset of these failures result in jobs being stuck for long periods of time. In order to debug such failures, interactive monitoring is highly desirable; users need to browse through the job log files and check the status of the running processes. Batch systems typically don't provide such services; at best, users get job logs at job termination, and even this may not be possible if the job is stuck in an infinite loop. In this paper we present a novel approach of using regular batch system capabilities of Condor to enable users to access the logs and processes of any running job. This does not provide true interactive access, so commands like vi are not viable, but it does allow operations like ls, cat, top, ps, lsof, netstat and dumping the stack of any process owned by the user; we call this pseudo-interactive monitoring. It is worth noting that the same method can be used to monitor Grid jobs in a glidein-based environment. We further believe that the same mechanism could be applied to many other batch systems.

  7. Pseudo-interactive monitoring in distributed computing

    Energy Technology Data Exchange (ETDEWEB)

    Sfiligoi, I.; /Fermilab; Bradley, D.; Livny, M.; /Wisconsin U., Madison

    2009-05-01

    Distributed computing, and in particular Grid computing, enables physicists to use thousands of CPU days worth of computing every day, by submitting thousands of compute jobs. Unfortunately, a small fraction of such jobs regularly fail; the reasons vary from disk and network problems to bugs in the user code. A subset of these failures result in jobs being stuck for long periods of time. In order to debug such failures, interactive monitoring is highly desirable; users need to browse through the job log files and check the status of the running processes. Batch systems typically don't provide such services; at best, users get job logs at job termination, and even this may not be possible if the job is stuck in an infinite loop. In this paper we present a novel approach of using regular batch system capabilities of Condor to enable users to access the logs and processes of any running job. This does not provide true interactive access, so commands like vi are not viable, but it does allow operations like ls, cat, top, ps, lsof, netstat and dumping the stack of any process owned by the user; we call this pseudo-interactive monitoring. It is worth noting that the same method can be used to monitor Grid jobs in a glidein-based environment. We further believe that the same mechanism could be applied to many other batch systems.

  8. Role of information systems in controlling costs: the electronic medical record (EMR) and the high-performance computing and communications (HPCC) efforts

    Science.gov (United States)

    Kun, Luis G.

    1994-12-01

    On October 18, 1991, the IEEE-USA produced an entity statement which endorsed the vital importance of the High Performance Computer and Communications Act of 1991 (HPCC) and called for the rapid implementation of all its elements. Efforts are now underway to develop a Computer Based Patient Record (CBPR), the National Information Infrastructure (NII) as part of the HPCC, and the so-called `Patient Card'. Multiple legislative initiatives which address these and related information technology issues are pending in Congress. Clearly, a national information system will greatly affect the way health care delivery is provided to the United States public. Timely and reliable information represents a critical element in any initiative to reform the health care system as well as to protect and improve the health of every person. Appropriately used, information technologies offer a vital means of improving the quality of patient care, increasing access to universal care and lowering overall costs within a national health care program. Health care reform legislation should reflect increased budgetary support and a legal mandate for the creation of a national health care information system by: (1) constructing a National Information Infrastructure; (2) building a Computer Based Patient Record System; (3) bringing the collective resources of our National Laboratories to bear in developing and implementing the NII and CBPR, as well as a security system with which to safeguard the privacy rights of patients and the physician-patient privilege; and (4) utilizing Government (e.g. DOD, DOE) capabilities (technology and human resources) to maximize resource utilization, create new jobs and accelerate technology transfer to address health care issues.

  9. Higher order correlations in computed particle distributions

    International Nuclear Information System (INIS)

    Hanerfeld, H.; Herrmannsfeldt, W.; Miller, R.H.

    1989-03-01

    The rms emittances calculated for beam distributions using computer simulations are frequently dominated by higher order aberrations. Thus there are substantial open areas in the phase space plots. It has long been observed that the rms emittance is not an invariant to beam manipulations. The usual emittance calculation removes the correlation between transverse displacement and transverse momentum. In this paper, we explore the possibility of defining higher order correlations that can be removed from the distribution to result in a lower limit to the realizable emittance. The intent is that by inserting the correct combinations of linear lenses at the proper position, the beam may recombine in a way that cancels the effects of some higher order forces. An example might be the non-linear transverse space charge forces which cause a beam to spread. If the beam is then refocused so that the same non-linear forces reverse the inward velocities, the resulting phase space distribution may reasonably approximate the original distribution. The approach to finding the location and strength of the proper lens to optimize the transported beam is based on work by Bruce Carlsten of Los Alamos National Laboratory. 11 refs., 4 figs

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

    CERN Document Server

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

    2017-01-01

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

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

    CERN Document Server

    Adam Bourdarios, Claire; The ATLAS collaboration

    2016-01-01

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

  12. A multipurpose computing center with distributed resources

    Science.gov (United States)

    Chudoba, J.; Adam, M.; Adamová, D.; Kouba, T.; Mikula, A.; Říkal, V.; Švec, J.; Uhlířová, J.; Vokáč, P.; Svatoš, M.

    2017-10-01

    The Computing Center of the Institute of Physics (CC IoP) of the Czech Academy of Sciences serves a broad spectrum of users with various computing needs. It runs WLCG Tier-2 center for the ALICE and the ATLAS experiments; the same group of services is used by astroparticle physics projects the Pierre Auger Observatory (PAO) and the Cherenkov Telescope Array (CTA). OSG stack is installed for the NOvA experiment. Other groups of users use directly local batch system. Storage capacity is distributed to several locations. DPM servers used by the ATLAS and the PAO are all in the same server room, but several xrootd servers for the ALICE experiment are operated in the Nuclear Physics Institute in Řež, about 10 km away. The storage capacity for the ATLAS and the PAO is extended by resources of the CESNET - the Czech National Grid Initiative representative. Those resources are in Plzen and Jihlava, more than 100 km away from the CC IoP. Both distant sites use a hierarchical storage solution based on disks and tapes. They installed one common dCache instance, which is published in the CC IoP BDII. ATLAS users can use these resources using the standard ATLAS tools in the same way as the local storage without noticing this geographical distribution. Computing clusters LUNA and EXMAG dedicated to users mostly from the Solid State Physics departments offer resources for parallel computing. They are part of the Czech NGI infrastructure MetaCentrum with distributed batch system based on torque with a custom scheduler. Clusters are installed remotely by the MetaCentrum team and a local contact helps only when needed. Users from IoP have exclusive access only to a part of these two clusters and take advantage of higher priorities on the rest (1500 cores in total), which can also be used by any user of the MetaCentrum. IoP researchers can also use distant resources located in several towns of the Czech Republic with a capacity of more than 12000 cores in total.

  13. Design considerations of high-performance InGaAs/InP single-photon avalanche diodes for quantum key distribution.

    Science.gov (United States)

    Ma, Jian; Bai, Bing; Wang, Liu-Jun; Tong, Cun-Zhu; Jin, Ge; Zhang, Jun; Pan, Jian-Wei

    2016-09-20

    InGaAs/InP single-photon avalanche diodes (SPADs) are widely used in practical applications requiring near-infrared photon counting such as quantum key distribution (QKD). Photon detection efficiency and dark count rate are the intrinsic parameters of InGaAs/InP SPADs, due to the fact that their performances cannot be improved using different quenching electronics given the same operation conditions. After modeling these parameters and developing a simulation platform for InGaAs/InP SPADs, we investigate the semiconductor structure design and optimization. The parameters of photon detection efficiency and dark count rate highly depend on the variables of absorption layer thickness, multiplication layer thickness, excess bias voltage, and temperature. By evaluating the decoy-state QKD performance, the variables for SPAD design and operation can be globally optimized. Such optimization from the perspective of specific applications can provide an effective approach to design high-performance InGaAs/InP SPADs.

  14. Real time computer system with distributed microprocessors

    International Nuclear Information System (INIS)

    Heger, D.; Steusloff, H.; Syrbe, M.

    1979-01-01

    The usual centralized structure of computer systems, especially of process computer systems, cannot sufficiently use the progress of very large-scale integrated semiconductor technology with respect to increasing the reliability and performance and to decreasing the expenses especially of the external periphery. This and the increasing demands on process control systems has led the authors to generally examine the structure of such systems and to adapt it to the new surroundings. Computer systems with distributed, optical fibre-coupled microprocessors allow a very favourable problem-solving with decentralized controlled buslines and functional redundancy with automatic fault diagnosis and reconfiguration. A fit programming system supports these hardware properties: PEARL for multicomputer systems, dynamic loader, processor and network operating system. The necessary design principles for this are proved mainly theoretically and by value analysis. An optimal overall system of this new generation of process control systems was established, supported by results of 2 PDV projects (modular operating systems, input/output colour screen system as control panel), for the purpose of testing by apllying the system for the control of 28 pit furnaces of a steel work. (orig.) [de

  15. WImpiBLAST: web interface for mpiBLAST to help biologists perform large-scale annotation using high performance computing.

    Directory of Open Access Journals (Sweden)

    Parichit Sharma

    Full Text Available The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture

  16. WImpiBLAST: web interface for mpiBLAST to help biologists perform large-scale annotation using high performance computing.

    Science.gov (United States)

    Sharma, Parichit; Mantri, Shrikant S

    2014-01-01

    The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design

  17. High performance homes

    DEFF Research Database (Denmark)

    Beim, Anne; Vibæk, Kasper Sánchez

    2014-01-01

    Can prefabrication contribute to the development of high performance homes? To answer this question, this chapter defines high performance in more broadly inclusive terms, acknowledging the technical, architectural, social and economic conditions under which energy consumption and production occur....... Consideration of all these factors is a precondition for a truly integrated practice and as this chapter demonstrates, innovative project delivery methods founded on the manufacturing of prefabricated buildings contribute to the production of high performance homes that are cost effective to construct, energy...

  18. High-Performance Operating Systems

    DEFF Research Database (Denmark)

    Sharp, Robin

    1999-01-01

    Notes prepared for the DTU course 49421 "High Performance Operating Systems". The notes deal with quantitative and qualitative techniques for use in the design and evaluation of operating systems in computer systems for which performance is an important parameter, such as real-time applications......, communication systems and multimedia systems....

  19. 10th International Symposium on Intelligent Distributed Computing

    CERN Document Server

    Seghrouchni, Amal; Beynier, Aurélie; Camacho, David; Herpson, Cédric; Hindriks, Koen; Novais, Paulo

    2017-01-01

    This book presents the combined peer-reviewed proceedings of the tenth International Symposium on Intelligent Distributed Computing (IDC’2016), which was held in Paris, France from October 10th to 12th, 2016. The 23 contributions address a range of topics related to theory and application of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.

  20. An Applet-based Anonymous Distributed Computing System.

    Science.gov (United States)

    Finkel, David; Wills, Craig E.; Ciaraldi, Michael J.; Amorin, Kevin; Covati, Adam; Lee, Michael

    2001-01-01

    Defines anonymous distributed computing systems and focuses on the specifics of a Java, applet-based approach for large-scale, anonymous, distributed computing on the Internet. Explains the possibility of a large number of computers participating in a single computation and describes a test of the functionality of the system. (Author/LRW)

  1. Sepsis reconsidered: Identifying novel metrics for behavioral landscape characterization with a high-performance computing implementation of an agent-based model.

    Science.gov (United States)

    Cockrell, Chase; An, Gary

    2017-10-07

    Sepsis affects nearly 1 million people in the United States per year, has a mortality rate of 28-50% and requires more than $20 billion a year in hospital costs. Over a quarter century of research has not yielded a single reliable diagnostic test or a directed therapeutic agent for sepsis. Central to this insufficiency is the fact that sepsis remains a clinical/physiological diagnosis representing a multitude of molecularly heterogeneous pathological trajectories. Advances in computational capabilities offered by High Performance Computing (HPC) platforms call for an evolution in the investigation of sepsis to attempt to define the boundaries of traditional research (bench, clinical and computational) through the use of computational proxy models. We present a novel investigatory and analytical approach, derived from how HPC resources and simulation are used in the physical sciences, to identify the epistemic boundary conditions of the study of clinical sepsis via the use of a proxy agent-based model of systemic inflammation. Current predictive models for sepsis use correlative methods that are limited by patient heterogeneity and data sparseness. We address this issue by using an HPC version of a system-level validated agent-based model of sepsis, the Innate Immune Response ABM (IIRBM), as a proxy system in order to identify boundary conditions for the possible behavioral space for sepsis. We then apply advanced analysis derived from the study of Random Dynamical Systems (RDS) to identify novel means for characterizing system behavior and providing insight into the tractability of traditional investigatory methods. The behavior space of the IIRABM was examined by simulating over 70 million sepsis patients for up to 90 days in a sweep across the following parameters: cardio-respiratory-metabolic resilience; microbial invasiveness; microbial toxigenesis; and degree of nosocomial exposure. In addition to using established methods for describing parameter space, we

  2. Xcache in the ATLAS Distributed Computing Environment

    CERN Document Server

    Hanushevsky, Andrew; The ATLAS collaboration

    2018-01-01

    Built upon the Xrootd Proxy Cache (Xcache), we developed additional features to adapt the ATLAS distributed computing and data environment, especially its data management system RUCIO, to help improve the cache hit rate, as well as features that make the Xcache easy to use, similar to the way the Squid cache is used by the HTTP protocol. We are optimizing Xcache for the HPC environments, and adapting the HL-LHC Data Lakes design as its component for data delivery. We packaged the software in CVMFS, in Docker and Singularity containers in order to standardize the deployment and reduce the cost to resolve issues at remote sites. We are also integrating it into RUCIO as a volatile storage systems, and into various ATLAS workflow such as user analysis,

  3. Distributed computer controls for accelerator systems

    International Nuclear Information System (INIS)

    Moore, T.L.

    1988-09-01

    A distributed control system has been designed and installed at the Lawrence Livermore National Laboratory Multi-user Tandem Facility using an extremely modular approach in hardware and software. The two tiered, geographically organized design allowed total system implementation with four months with a computer and instrumentation cost of approximately $100K. Since the system structure is modular, application to a variety of facilities is possible. Such a system allows rethinking and operational style of the facilities, making possible highly reproducible and unattended operation. The impact of industry standards, i.e., UNIX, CAMAC, and IEEE-802.3, and the use of a graphics-oriented controls software suite allowed the efficient implementation of the system. The definition, design, implementation, operation and total system performance will be discussed. 3 refs

  4. Distributed computer controls for accelerator systems

    Science.gov (United States)

    Moore, T. L.

    1989-04-01

    A distributed control system has been designed and installed at the Lawrence Livermore National Laboratory Multiuser Tandem Facility using an extremely modular approach in hardware and software. The two tiered, geographically organized design allowed total system implantation within four months with a computer and instrumentation cost of approximately $100k. Since the system structure is modular, application to a variety of facilities is possible. Such a system allows rethinking of operational style of the facilities, making possible highly reproducible and unattended operation. The impact of industry standards, i.e., UNIX, CAMAC, and IEEE-802.3, and the use of a graphics-oriented controls software suite allowed the effective implementation of the system. The definition, design, implementation, operation and total system performance will be discussed.

  5. Distributed computer controls for accelerator systems

    International Nuclear Information System (INIS)

    Moore, T.L.

    1989-01-01

    A distributed control system has been designed and installed at the Lawrence Livermore National Laboratory Multiuser Tandem Facility using an extremely modular approach in hardware and software. The two tiered, geographically organized design allowed total system implantation within four months with a computer and instrumentation cost of approximately $100k. Since the system structure is modular, application to a variety of facilities is possible. Such a system allows rethinking of operational style of the facilities, making possible highly reproducible and unattended operation. The impact of industry standards, i.e., UNIX, CAMAC, and IEEE-802.3, and the use of a graphics-oriented controls software suite allowed the effective implementation of the system. The definition, design, implementation, operation and total system performance will be discussed. (orig.)

  6. Proceedings of workshop on distributed computing and network

    International Nuclear Information System (INIS)

    Abe, F.; Yuasa, F.

    1993-02-01

    'Distributed Computing and Network' is one of hot topics in the field of computing. Recent progress in the computer technology is providing new paradigm for computing even in High Energy Physics. Particularly the workstation based computer system is opening new active field of computer application to sciences. The major topics discussed in this symposium are distributed computing and wide area research network for domestic and international link. The two days symposium provided so enough topics to foresee the next direction of our computing environment. 70 people have got together to discuss on these interesting thema as well as information exchange on the computer technologies. (J.P.N.)

  7. DISTRIBUTED COMPUTING SUPPORT CONTRACT USER SURVEY

    CERN Multimedia

    2001-01-01

    IT Division operates a Distributed Computing Support Service, which offers support to owners and users of all variety of desktops throughout CERN as well as more dedicated services for certain groups, divisions and experiments. It also provides the staff who operate the central and satellite Computing Helpdesks, it supports printers throughout the site and it provides the installation activities of the IT Division PC Service. We have published a questionnaire which seeks to gather your feedback on how the services are seen, how they are progressing and how they can be improved. Please take a few minutes to fill in this questionnaire. Replies will be treated in confidence if desired although you may also request an opportunity to be contacted by CERN's service management directly. Please tell us if you met problems but also if you had a successful conclusion to your request for assistance. You will find the questionnaire at the web site http://wwwinfo/support/survey/desktop-contract There will also be a link ...

  8. DISTRIBUTED COMPUTING SUPPORT SERVICE USER SURVEY

    CERN Multimedia

    2001-01-01

    IT Division operates a Distributed Computing Support Service, which offers support to owners and users of all variety of desktops throughout CERN as well as more dedicated services for certain groups, divisions and experiments. It also provides the staff who operate the central and satellite Computing Helpdesks, it supports printers throughout the site and it provides the installation activities of the IT Division PC Service. We have published a questionnaire, which seeks to gather your feedback on how the services are seen, how they are progressing and how they can be improved. Please take a few minutes to fill in this questionnaire. Replies will be treated in confidence if desired although you may also request an opportunity to be contacted by CERN's service management directly. Please tell us if you met problems but also if you had a successful conclusion to your request for assistance. You will find the questionnaire at the web site http://wwwinfo/support/survey/desktop-contract There will also be a link...

  9. Distributed computing for FTU data handling

    Energy Technology Data Exchange (ETDEWEB)

    Bertocchi, A. E-mail: bertocchi@frascati.enea.it; Bracco, G.; Buceti, G.; Centioli, C.; Giovannozzi, E.; Iannone, F.; Panella, M.; Vitale, V

    2002-06-01

    The growth of data warehouse in tokamak experiment is leading fusion laboratories to provide new IT solutions in data handling. In the last three years, the Frascati Tokamak Upgrade (FTU) experimental database was migrated from IBM-mainframe to Unix distributed computing environment. The migration efforts have taken into account the following items: (1) a new data storage solution based on storage area network over fibre channel; (2) andrew file system (AFS) for wide area network file sharing; (3) 'one measure/one file' philosophy replacing 'one shot/one file' to provide a faster read/write data access; (4) more powerful services, such as AFS, CORBA and MDSplus to allow users to access FTU database from different clients, regardless their O.S.; (5) large availability of data analysis tools, from the locally developed utility SHOW to the multi-platform Matlab, interactive data language and jScope (all these tools are now able to access also the Joint European Torus data, in the framework of the remote data access activity); (6) a batch-computing cluster of Alpha/CompaqTru64 CPU based on CODINE/GRD to optimize utilization of software and hardware resources.

  10. Distributed computing grid experiences in CMS

    CERN Document Server

    Andreeva, Julia; Barrass, T; Bonacorsi, D; Bunn, Julian; Capiluppi, P; Corvo, M; Darmenov, N; De Filippis, N; Donno, F; Donvito, G; Eulisse, G; Fanfani, A; Fanzago, F; Filine, A; Grandi, C; Hernández, J M; Innocente, V; Jan, A; Lacaprara, S; Legrand, I; Metson, S; Newbold, D; Newman, H; Pierro, A; Silvestris, L; Steenberg, C; Stockinger, H; Taylor, Lucas; Thomas, M; Tuura, L; Van Lingen, F; Wildish, Tony

    2005-01-01

    The CMS experiment is currently developing a computing system capable of serving, processing and archiving the large number of events that will be generated when the CMS detector starts taking data. During 2004 CMS undertook a large scale data challenge to demonstrate the ability of the CMS computing system to cope with a sustained data- taking rate equivalent to 25% of startup rate. Its goals were: to run CMS event reconstruction at CERN for a sustained period at 25 Hz input rate; to distribute the data to several regional centers; and enable data access at those centers for analysis. Grid middleware was utilized to help complete all aspects of the challenge. To continue to provide scalable access from anywhere in the world to the data, CMS is developing a layer of software that uses Grid tools to gain access to data and resources, and that aims to provide physicists with a user friendly interface for submitting their analysis jobs. This paper describes the data challenge experience with Grid infrastructure ...

  11. Automating usability of ATLAS distributed computing resources

    International Nuclear Information System (INIS)

    Tupputi, S A; Girolamo, A Di; Kouba, T; Schovancová, J

    2014-01-01

    The automation of ATLAS Distributed Computing (ADC) operations is essential to reduce manpower costs and allow performance-enhancing actions, which improve the reliability of the system. In this perspective a crucial case is the automatic handling of outages of ATLAS computing sites storage resources, which are continuously exploited at the edge of their capabilities. It is challenging to adopt unambiguous decision criteria for storage resources of non-homogeneous types, sizes and roles. The recently developed Storage Area Automatic Blacklisting (SAAB) tool has provided a suitable solution, by employing an inference algorithm which processes history of storage monitoring tests outcome. SAAB accomplishes both the tasks of providing global monitoring as well as automatic operations on single sites. The implementation of the SAAB tool has been the first step in a comprehensive review of the storage areas monitoring and central management at all levels. Such review has involved the reordering and optimization of SAM tests deployment and the inclusion of SAAB results in the ATLAS Site Status Board with both dedicated metrics and views. The resulting structure allows monitoring the storage resources status with fine time-granularity and automatic actions to be taken in foreseen cases, like automatic outage handling and notifications to sites. Hence, the human actions are restricted to reporting and following up problems, where and when needed. In this work we show SAAB working principles and features. We present also the decrease of human interactions achieved within the ATLAS Computing Operation team. The automation results in a prompt reaction to failures, which leads to the optimization of resource exploitation.

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

    Directory of Open Access Journals (Sweden)

    Wojtek James eGoscinski

    2014-03-01

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

  13. A Semi-Automated Machine Learning Algorithm for Tree Cover Delineation from 1-m Naip Imagery Using a High Performance Computing Architecture

    Science.gov (United States)

    Basu, S.; Ganguly, S.; Nemani, R. R.; Mukhopadhyay, S.; Milesi, C.; Votava, P.; Michaelis, A.; Zhang, G.; Cook, B. D.; Saatchi, S. S.; Boyda, E.

    2014-12-01

    Accurate tree cover delineation is a useful instrument in the derivation of Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) satellite imagery data. Numerous algorithms have been designed to perform tree cover delineation in high to coarse resolution satellite imagery, but most of them do not scale to terabytes of data, typical in these VHR datasets. In this paper, we present an automated probabilistic framework for the segmentation and classification of 1-m VHR data as obtained from the National Agriculture Imagery Program (NAIP) for deriving tree cover estimates for the whole of Continental United States, using a High Performance Computing Architecture. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field (CRF), which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by incorporating expert knowledge through the relabeling of misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the state of California, which covers a total of 11,095 NAIP tiles and spans a total geographical area of 163,696 sq. miles. Our framework produced correct detection rates of around 85% for fragmented forests and 70% for urban tree cover areas, with false positive rates lower than 3% for both regions. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR high-resolution canopy height model shows the effectiveness of our algorithm in generating accurate high-resolution tree cover maps.

  14. Using spatial principles to optimize distributed computing for enabling the physical science discoveries.

    Science.gov (United States)

    Yang, Chaowei; Wu, Huayi; Huang, Qunying; Li, Zhenlong; Li, Jing

    2011-04-05

    Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences. Spatial principles govern the interactions between scientific parameters across space and time by providing the spatial connections and constraints to drive the progression of the phenomena. Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences. Using geospatial science as an example, this paper illustrates through three research examples how spatial computing could (i) enable data intensive science with efficient data/services search, access, and utilization, (ii) facilitate physical science studies with enabling high-performance computing capabilities, and (iii) empower scientists with multidimensional visualization tools to understand observations and simulations. The research examples demonstrate that spatial computing is of critical importance to design computing methods to catalyze physical science studies with better data access, phenomena simulation, and analytical visualization. We envision that spatial computing will become a core technology that drives fundamental physical science advancements in the 21st century.

  15. High Performance Marine Vessels

    CERN Document Server

    Yun, Liang

    2012-01-01

    High Performance Marine Vessels (HPMVs) range from the Fast Ferries to the latest high speed Navy Craft, including competition power boats and hydroplanes, hydrofoils, hovercraft, catamarans and other multi-hull craft. High Performance Marine Vessels covers the main concepts of HPMVs and discusses historical background, design features, services that have been successful and not so successful, and some sample data of the range of HPMVs to date. Included is a comparison of all HPMVs craft and the differences between them and descriptions of performance (hydrodynamics and aerodynamics). Readers will find a comprehensive overview of the design, development and building of HPMVs. In summary, this book: Focuses on technology at the aero-marine interface Covers the full range of high performance marine vessel concepts Explains the historical development of various HPMVs Discusses ferries, racing and pleasure craft, as well as utility and military missions High Performance Marine Vessels is an ideal book for student...

  16. High Performance Macromolecular Material

    National Research Council Canada - National Science Library

    Forest, M

    2002-01-01

    .... In essence, most commercial high-performance polymers are processed through fiber spinning, following Nature and spider silk, which is still pound-for-pound the toughest liquid crystalline polymer...

  17. Amorphous Zinc Oxide Integrated Wavy Channel Thin Film Transistor Based High Performance Digital Circuits

    KAUST Repository

    Hanna, Amir; Hussain, Aftab M.; Omran, Hesham; Alshareef, Sarah; Salama, Khaled N.; Hussain, Muhammad Mustafa

    2015-01-01

    High performance thin film transistor (TFT) can be a great driving force for display, sensor/actuator, integrated electronics, and distributed computation for Internet of Everything applications. While semiconducting oxides like zinc oxide (Zn

  18. An Overview of Cloud Computing in Distributed Systems

    Science.gov (United States)

    Divakarla, Usha; Kumari, Geetha

    2010-11-01

    Cloud computing is the emerging trend in the field of distributed computing. Cloud computing evolved from grid computing and distributed computing. Cloud plays an important role in huge organizations in maintaining huge data with limited resources. Cloud also helps in resource sharing through some specific virtual machines provided by the cloud service provider. This paper gives an overview of the cloud organization and some of the basic security issues pertaining to the cloud.

  19. Distributed Memory Parallel Computing with SEAWAT

    Science.gov (United States)

    Verkaik, J.; Huizer, S.; van Engelen, J.; Oude Essink, G.; Ram, R.; Vuik, K.

    2017-12-01

    Fresh groundwater reserves in coastal aquifers are threatened by sea-level rise, extreme weather conditions, increasing urbanization and associated groundwater extraction rates. To counteract these threats, accurate high-resolution numerical models are required to optimize the management of these precious reserves. The major model drawbacks are long run times and large memory requirements, limiting the predictive power of these models. Distributed memory parallel computing is an efficient technique for reducing run times and memory requirements, where the problem is divided over multiple processor cores. A new Parallel Krylov Solver (PKS) for SEAWAT is presented. PKS has recently been applied to MODFLOW and includes Conjugate Gradient (CG) and Biconjugate Gradient Stabilized (BiCGSTAB) linear accelerators. Both accelerators are preconditioned by an overlapping additive Schwarz preconditioner in a way that: a) subdomains are partitioned using Recursive Coordinate Bisection (RCB) load balancing, b) each subdomain uses local memory only and communicates with other subdomains by Message Passing Interface (MPI) within the linear accelerator, c) it is fully integrated in SEAWAT. Within SEAWAT, the PKS-CG solver replaces the Preconditioned Conjugate Gradient (PCG) solver for solving the variable-density groundwater flow equation and the PKS-BiCGSTAB solver replaces the Generalized Conjugate Gradient (GCG) solver for solving the advection-diffusion equation. PKS supports the third-order Total Variation Diminishing (TVD) scheme for computing advection. Benchmarks were performed on the Dutch national supercomputer (https://userinfo.surfsara.nl/systems/cartesius) using up to 128 cores, for a synthetic 3D Henry model (100 million cells) and the real-life Sand Engine model ( 10 million cells). The Sand Engine model was used to investigate the potential effect of the long-term morphological evolution of a large sand replenishment and climate change on fresh groundwater resources

  20. Management issues for high performance storage systems

    Energy Technology Data Exchange (ETDEWEB)

    Louis, S. [Lawrence Livermore National Lab., CA (United States); Burris, R. [Oak Ridge National Lab., TN (United States)

    1995-03-01

    Managing distributed high-performance storage systems is complex and, although sharing common ground with traditional network and systems management, presents unique storage-related issues. Integration technologies and frameworks exist to help manage distributed network and system environments. Industry-driven consortia provide open forums where vendors and users cooperate to leverage solutions. But these new approaches to open management fall short addressing the needs of scalable, distributed storage. We discuss the motivation and requirements for storage system management (SSM) capabilities and describe how SSM manages distributed servers and storage resource objects in the High Performance Storage System (HPSS), a new storage facility for data-intensive applications and large-scale computing. Modem storage systems, such as HPSS, require many SSM capabilities, including server and resource configuration control, performance monitoring, quality of service, flexible policies, file migration, file repacking, accounting, and quotas. We present results of initial HPSS SSM development including design decisions and implementation trade-offs. We conclude with plans for follow-on work and provide storage-related recommendations for vendors and standards groups seeking enterprise-wide management solutions.