XVIS: Visualization for the Extreme-Scale Scientific-Computation Ecosystem Final Scientific/Technical Report

Energy Technology Data Exchange (ETDEWEB)

Geveci, Berk [Kitware, Inc., Clifton Park, NY (United States); Maynard, Robert [Kitware, Inc., Clifton Park, NY (United States)

2017-10-27

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project brought together collaborators from predominant DOE projects for visualization on accelerators and combining their respective features into a new visualization toolkit called VTK-m.

On the Performance of the Python Programming Language for Serial and Parallel Scientific Computations

Directory of Open Access Journals (Sweden)

Xing Cai

2005-01-01

Full Text Available This article addresses the performance of scientific applications that use the Python programming language. First, we investigate several techniques for improving the computational efficiency of serial Python codes. Then, we discuss the basic programming techniques in Python for parallelizing serial scientific applications. It is shown that an efficient implementation of the array-related operations is essential for achieving good parallel performance, as for the serial case. Once the array-related operations are efficiently implemented, probably using a mixed-language implementation, good serial and parallel performance become achievable. This is confirmed by a set of numerical experiments. Python is also shown to be well suited for writing high-level parallel programs.

The Potential of the Cell Processor for Scientific Computing

Energy Technology Data Exchange (ETDEWEB)

Williams, Samuel; Shalf, John; Oliker, Leonid; Husbands, Parry; Kamil, Shoaib; Yelick, Katherine

2005-10-14

The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. As a result, the high performance computing community is examining alternative architectures that address the limitations of modern cache-based designs. In this work, we examine the potential of the using the forth coming STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. We are the first to present quantitative Cell performance data on scientific kernels and show direct comparisons against leading superscalar (AMD Opteron), VLIW (IntelItanium2), and vector (Cray X1) architectures. Since neither Cell hardware nor cycle-accurate simulators are currently publicly available, we develop both analytical models and simulators to predict kernel performance. Our work also explores the complexity of mapping several important scientific algorithms onto the Cells unique architecture. Additionally, we propose modest microarchitectural modifications that could significantly increase the efficiency of double-precision calculations. Overall results demonstrate the tremendous potential of the Cell architecture for scientific computations in terms of both raw performance and power efficiency.

The application of cloud computing to scientific workflows: a study of cost and performance.

Science.gov (United States)

Berriman, G Bruce; Deelman, Ewa; Juve, Gideon; Rynge, Mats; Vöckler, Jens-S

2013-01-28

The current model of transferring data from data centres to desktops for analysis will soon be rendered impractical by the accelerating growth in the volume of science datasets. Processing will instead often take place on high-performance servers co-located with data. Evaluations of how new technologies such as cloud computing would support such a new distributed computing model are urgently needed. Cloud computing is a new way of purchasing computing and storage resources on demand through virtualization technologies. We report here the results of investigations of the applicability of commercial cloud computing to scientific computing, with an emphasis on astronomy, including investigations of what types of applications can be run cheaply and efficiently on the cloud, and an example of an application well suited to the cloud: processing a large dataset to create a new science product.

Scientific Computing Kernels on the Cell Processor

Energy Technology Data Exchange (ETDEWEB)

Williams, Samuel W.; Shalf, John; Oliker, Leonid; Kamil, Shoaib; Husbands, Parry; Yelick, Katherine

2007-04-04

The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. As a result, the high performance computing community is examining alternative architectures that address the limitations of modern cache-based designs. In this work, we examine the potential of using the recently-released STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. First, we introduce a performance model for Cell and apply it to several key scientific computing kernels: dense matrix multiply, sparse matrix vector multiply, stencil computations, and 1D/2D FFTs. The difficulty of programming Cell, which requires assembly level intrinsics for the best performance, makes this model useful as an initial step in algorithm design and evaluation. Next, we validate the accuracy of our model by comparing results against published hardware results, as well as our own implementations on a 3.2GHz Cell blade. Additionally, we compare Cell performance to benchmarks run on leading superscalar (AMD Opteron), VLIW (Intel Itanium2), and vector (Cray X1E) architectures. Our work also explores several different mappings of the kernels and demonstrates a simple and effective programming model for Cell's unique architecture. Finally, we propose modest microarchitectural modifications that could significantly increase the efficiency of double-precision calculations. Overall results demonstrate the tremendous potential of the Cell architecture for scientific computations in terms of both raw performance and power efficiency.

Highly parallel machines and future of scientific computing

International Nuclear Information System (INIS)

Singh, G.S.

1992-01-01

Computing requirement of large scale scientific computing has always been ahead of what state of the art hardware could supply in the form of supercomputers of the day. And for any single processor system the limit to increase in the computing power was realized a few years back itself. Now with the advent of parallel computing systems the availability of machines with the required computing power seems a reality. In this paper the author tries to visualize the future large scale scientific computing in the penultimate decade of the present century. The author summarized trends in parallel computers and emphasize the need for a better programming environment and software tools for optimal performance. The author concludes this paper with critique on parallel architectures, software tools and algorithms. (author). 10 refs., 2 tabs

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.

Pascal-SC a computer language for scientific computation

CERN Document Server

Bohlender, Gerd; von Gudenberg, Jürgen Wolff; Rheinboldt, Werner; Siewiorek, Daniel

1987-01-01

Perspectives in Computing, Vol. 17: Pascal-SC: A Computer Language for Scientific Computation focuses on the application of Pascal-SC, a programming language developed as an extension of standard Pascal, in scientific computation. The publication first elaborates on the introduction to Pascal-SC, a review of standard Pascal, and real floating-point arithmetic. Discussions focus on optimal scalar product, standard functions, real expressions, program structure, simple extensions, real floating-point arithmetic, vector and matrix arithmetic, and dynamic arrays. The text then examines functions a

Research initiatives for plug-and-play scientific computing

International Nuclear Information System (INIS)

McInnes, Lois Curfman; Dahlgren, Tamara; Nieplocha, Jarek; Bernholdt, David; Allan, Ben; Armstrong, Rob; Chavarria, Daniel; Elwasif, Wael; Gorton, Ian; Kenny, Joe; Krishan, Manoj; Malony, Allen; Norris, Boyana; Ray, Jaideep; Shende, Sameer

2007-01-01

This paper introduces three component technology initiatives within the SciDAC Center for Technology for Advanced Scientific Component Software (TASCS) that address ever-increasing productivity challenges in creating, managing, and applying simulation software to scientific discovery. By leveraging the Common Component Architecture (CCA), a new component standard for high-performance scientific computing, these initiatives tackle difficulties at different but related levels in the development of component-based scientific software: (1) deploying applications on massively parallel and heterogeneous architectures, (2) investigating new approaches to the runtime enforcement of behavioral semantics, and (3) developing tools to facilitate dynamic composition, substitution, and reconfiguration of component implementations and parameters, so that application scientists can explore tradeoffs among factors such as accuracy, reliability, and performance

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.

Initial explorations of ARM processors for scientific computing

International Nuclear Information System (INIS)

Abdurachmanov, David; Elmer, Peter; Eulisse, Giulio; Muzaffar, Shahzad

2014-01-01

Power efficiency is becoming an ever more important metric for both high performance and high throughput computing. Over the course of next decade it is expected that flops/watt will be a major driver for the evolution of computer architecture. Servers with large numbers of ARM processors, already ubiquitous in mobile computing, are a promising alternative to traditional x86-64 computing. We present the results of our initial investigations into the use of ARM processors for scientific computing applications. In particular we report the results from our work with a current generation ARMv7 development board to explore ARM-specific issues regarding the software development environment, operating system, performance benchmarks and issues for porting High Energy Physics software

National Energy Research Scientific Computing Center (NERSC): Advancing the frontiers of computational science and technology

Energy Technology Data Exchange (ETDEWEB)

Hules, J. [ed.

1996-11-01

National Energy Research Scientific Computing Center (NERSC) provides researchers with high-performance computing tools to tackle science`s biggest and most challenging problems. Founded in 1974 by DOE/ER, the Controlled Thermonuclear Research Computer Center was the first unclassified supercomputer center and was the model for those that followed. Over the years the center`s name was changed to the National Magnetic Fusion Energy Computer Center and then to NERSC; it was relocated to LBNL. NERSC, one of the largest unclassified scientific computing resources in the world, is the principal provider of general-purpose computing services to DOE/ER programs: Magnetic Fusion Energy, High Energy and Nuclear Physics, Basic Energy Sciences, Health and Environmental Research, and the Office of Computational and Technology Research. NERSC users are a diverse community located throughout US and in several foreign countries. This brochure describes: the NERSC advantage, its computational resources and services, future technologies, scientific resources, and computational science of scale (interdisciplinary research over a decade or longer; examples: combustion in engines, waste management chemistry, global climate change modeling).

High-End Scientific Computing

Science.gov (United States)

EPA uses high-end scientific computing, geospatial services and remote sensing/imagery analysis to support EPA's mission. The Center for Environmental Computing (CEC) assists the Agency's program offices and regions to meet staff needs in these areas.

Software Engineering for Scientific Computer Simulations

Science.gov (United States)

Post, Douglass E.; Henderson, Dale B.; Kendall, Richard P.; Whitney, Earl M.

2004-11-01

Computer simulation is becoming a very powerful tool for analyzing and predicting the performance of fusion experiments. Simulation efforts are evolving from including only a few effects to many effects, from small teams with a few people to large teams, and from workstations and small processor count parallel computers to massively parallel platforms. Successfully making this transition requires attention to software engineering issues. We report on the conclusions drawn from a number of case studies of large scale scientific computing projects within DOE, academia and the DoD. The major lessons learned include attention to sound project management including setting reasonable and achievable requirements, building a good code team, enforcing customer focus, carrying out verification and validation and selecting the optimum computational mathematics approaches.

Practical scientific computing

CERN Document Server

Muhammad, A

2011-01-01

Scientific computing is about developing mathematical models, numerical methods and computer implementations to study and solve real problems in science, engineering, business and even social sciences. Mathematical modelling requires deep understanding of classical numerical methods. This essential guide provides the reader with sufficient foundations in these areas to venture into more advanced texts. The first section of the book presents numEclipse, an open source tool for numerical computing based on the notion of MATLAB®. numEclipse is implemented as a plug-in for Eclipse, a leading integ

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...

The Y2K program for scientific-analysis computer programs at AECL

International Nuclear Information System (INIS)

Popovic, J.; Gaver, C.; Chapman, D.

1999-01-01

The evaluation of scientific-analysis computer programs for year-2000 compliance is part of AECL' s year-2000 (Y2K) initiative, which addresses both the infrastructure systems at AECL and AECL's products and services. This paper describes the Y2K-compliance program for scientific-analysis computer codes. This program involves the integrated evaluation of the computer hardware, middleware, and third-party software in addition to the scientific codes developed in-house. The project involves several steps: the assessment of the scientific computer programs for Y2K compliance, performing any required corrective actions, porting the programs to Y2K-compliant platforms, and verification of the programs after porting. Some programs or program versions, deemed no longer required in the year 2000 and beyond, will be retired and archived. (author)

The Y2K program for scientific-analysis computer programs at AECL

International Nuclear Information System (INIS)

Popovic, J.; Gaver, C.; Chapman, D.

1999-01-01

The evaluation of scientific analysis computer programs for year-2000 compliance is part of AECL's year-2000 (Y2K) initiative, which addresses both the infrastructure systems at AECL and AECL's products and services. This paper describes the Y2K-compliance program for scientific-analysis computer codes. This program involves the integrated evaluation of the computer hardware, middleware, and third-party software in addition to the scientific codes developed in-house. The project involves several steps: the assessment of the scientific computer programs for Y2K compliance, performing any required corrective actions, porting the programs to Y2K-compliant platforms, and verification of the programs after porting. Some programs or program versions, deemed no longer required in the year 2000 and beyond, will be retired and archived. (author)

Scientific Discovery through Advanced Computing in Plasma Science

Science.gov (United States)

Tang, William

2005-03-01

Advanced computing is generally recognized to be an increasingly vital tool for accelerating progress in scientific research during the 21st Century. For example, the Department of Energy's ``Scientific Discovery through Advanced Computing'' (SciDAC) Program was motivated in large measure by the fact that formidable scientific challenges in its research portfolio could best be addressed by utilizing the combination of the rapid advances in super-computing technology together with the emergence of effective new algorithms and computational methodologies. The imperative is to translate such progress into corresponding increases in the performance of the scientific codes used to model complex physical systems such as those encountered in high temperature plasma research. If properly validated against experimental measurements and analytic benchmarks, these codes can provide reliable predictive capability for the behavior of a broad range of complex natural and engineered systems. This talk reviews recent progress and future directions for advanced simulations with some illustrative examples taken from the plasma science applications area. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by the combination of access to powerful new computational resources together with innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning a huge range in time and space scales. In particular, the plasma science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations

Computers and Computation. Readings from Scientific American.

Science.gov (United States)

Fenichel, Robert R.; Weizenbaum, Joseph

A collection of articles from "Scientific American" magazine has been put together at this time because the current period in computer science is one of consolidation rather than innovation. A few years ago, computer science was moving so swiftly that even the professional journals were more archival than informative; but today it is…

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY17.

Energy Technology Data Exchange (ETDEWEB)

Moreland, Kenneth D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pugmire, David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Rogers, David [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Childs, Hank [Univ. of Oregon, Eugene, OR (United States); Ma, Kwan-Liu [Univ. of California, Davis, CA (United States); Geveci, Berk [Kitware, Inc., Clifton Park, NY (United States)

2017-10-01

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

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.

US QCD computational performance studies with PERI

International Nuclear Information System (INIS)

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

2007-01-01

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

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

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.

Scientific computing

CERN Document Server

Trangenstein, John A

2017-01-01

This is the third of three volumes providing a comprehensive presentation of the fundamentals of scientific computing. This volume discusses topics that depend more on calculus than linear algebra, in order to prepare the reader for solving differential equations. This book and its companions show how to determine the quality of computational results, and how to measure the relative efficiency of competing methods. Readers learn how to determine the maximum attainable accuracy of algorithms, and how to select the best method for computing problems. This book also discusses programming in several languages, including C++, Fortran and MATLAB. There are 90 examples, 200 exercises, 36 algorithms, 40 interactive JavaScript programs, 91 references to software programs and 1 case study. Topics are introduced with goals, literature references and links to public software. There are descriptions of the current algorithms in GSLIB and MATLAB. This book could be used for a second course in numerical methods, for either ...

ScalaLab and GroovyLab: Comparing Scala and Groovy for Scientific Computing

Directory of Open Access Journals (Sweden)

Stergios Papadimitriou

2015-01-01

Full Text Available ScalaLab and GroovyLab are both MATLAB-like environments for the Java Virtual Machine. ScalaLab is based on the Scala programming language and GroovyLab is based on the Groovy programming language. They present similar user interfaces and functionality to the user. They also share the same set of Java scientific libraries and of native code libraries. From the programmer's point of view though, they have significant differences. This paper compares some aspects of the two environments and highlights some of the strengths and weaknesses of Scala versus Groovy for scientific computing. The discussion also examines some aspects of the dilemma of using dynamic typing versus static typing for scientific programming. The performance of the Java platform is continuously improved at a fast pace. Today Java can effectively support demanding high-performance computing and scales well on multicore platforms. Thus, both systems can challenge the performance of the traditional C/C++/Fortran scientific code with an easier to use and more productive programming environment.

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,…

RXY/DRXY-a postprocessing graphical system for scientific computation

International Nuclear Information System (INIS)

Jin Qijie

1990-01-01

Scientific computing require computer graphical function for its visualization. The developing objects and functions of a postprocessing graphical system for scientific computation are described, and also briefly described its implementation

ASCR Cybersecurity for Scientific Computing Integrity - Research Pathways and Ideas Workshop

Energy Technology Data Exchange (ETDEWEB)

Peisert, Sean [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Davis, CA (United States); Potok, Thomas E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Jones, Todd [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-06-03

At the request of the U.S. Department of Energy's (DOE) Office of Science (SC) Advanced Scientific Computing Research (ASCR) program office, a workshop was held June 2-3, 2015, in Gaithersburg, MD, to identify potential long term (10 to +20 year) cybersecurity fundamental basic research and development challenges, strategies and roadmap facing future high performance computing (HPC), networks, data centers, and extreme-scale scientific user facilities. This workshop was a follow-on to the workshop held January 7-9, 2015, in Rockville, MD, that examined higher level ideas about scientific computing integrity specific to the mission of the DOE Office of Science. Issues included research computation and simulation that takes place on ASCR computing facilities and networks, as well as network-connected scientific instruments, such as those run by various DOE Office of Science programs. Workshop participants included researchers and operational staff from DOE national laboratories, as well as academic researchers and industry experts. Participants were selected based on the submission of abstracts relating to the topics discussed in the previous workshop report [1] and also from other ASCR reports, including "Abstract Machine Models and Proxy Architectures for Exascale Computing" [27], the DOE "Preliminary Conceptual Design for an Exascale Computing Initiative" [28], and the January 2015 machine learning workshop [29]. The workshop was also attended by several observers from DOE and other government agencies. The workshop was divided into three topic areas: (1) Trustworthy Supercomputing, (2) Extreme-Scale Data, Knowledge, and Analytics for Understanding and Improving Cybersecurity, and (3) Trust within High-end Networking and Data Centers. Participants were divided into three corresponding teams based on the category of their abstracts. The workshop began with a series of talks from the program manager and workshop chair, followed by the leaders for each of the

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY15 Q4.

Energy Technology Data Exchange (ETDEWEB)

Moreland, Kenneth D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sewell, Christopher [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Childs, Hank [Univ. of Oregon, Eugene, OR (United States); Ma, Kwan-Liu [Univ. of California, Davis, CA (United States); Geveci, Berk [Kitware, Inc., Clifton Park, NY (United States); Meredith, Jeremy [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2015-12-01

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Mid-year report FY17 Q2

Energy Technology Data Exchange (ETDEWEB)

Moreland, Kenneth D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pugmire, David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Rogers, David [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Childs, Hank [Univ. of Oregon, Eugene, OR (United States); Ma, Kwan-Liu [Univ. of California, Davis, CA (United States); Geveci, Berk [Kitware Inc., Clifton Park, NY (United States)

2017-05-01

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem. Mid-year report FY16 Q2

Energy Technology Data Exchange (ETDEWEB)

Moreland, Kenneth D.; Sewell, Christopher (LANL); Childs, Hank (U of Oregon); Ma, Kwan-Liu (UC Davis); Geveci, Berk (Kitware); Meredith, Jeremy (ORNL)

2016-05-01

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

Implementation of Scientific Computing Applications on the Cell Broadband Engine

Directory of Open Access Journals (Sweden)

Guochun Shi

2009-01-01

Full Text Available The Cell Broadband Engine architecture is a revolutionary processor architecture well suited for many scientific codes. This paper reports on an effort to implement several traditional high-performance scientific computing applications on the Cell Broadband Engine processor, including molecular dynamics, quantum chromodynamics and quantum chemistry codes. The paper discusses data and code restructuring strategies necessary to adapt the applications to the intrinsic properties of the Cell processor and demonstrates performance improvements achieved on the Cell architecture. It concludes with the lessons learned and provides practical recommendations on optimization techniques that are believed to be most appropriate.

Top scientific research center deploys Zambeel Aztera (TM) network storage system in high performance environment

CERN Multimedia

2002-01-01

" The National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory has implemented a Zambeel Aztera storage system and software to accelerate the productivity of scientists running high performance scientific simulations and computations" (1 page).

Performance of Air Pollution Models on Massively Parallel Computers

DEFF Research Database (Denmark)

Brown, John; Hansen, Per Christian; Wasniewski, Jerzy

1996-01-01

To compare the performance and use of three massively parallel SIMD computers, we implemented a large air pollution model on the computers. Using a realistic large-scale model, we gain detailed insight about the performance of the three computers when used to solve large-scale scientific problems...

Scientific computing and algorithms in industrial simulations projects and products of Fraunhofer SCAI

CERN Document Server

Schüller, Anton; Schweitzer, Marc

2017-01-01

The contributions gathered here provide an overview of current research projects and selected software products of the Fraunhofer Institute for Algorithms and Scientific Computing SCAI. They show the wide range of challenges that scientific computing currently faces, the solutions it offers, and its important role in developing applications for industry. Given the exciting field of applied collaborative research and development it discusses, the book will appeal to scientists, practitioners, and students alike. The Fraunhofer Institute for Algorithms and Scientific Computing SCAI combines excellent research and application-oriented development to provide added value for our partners. SCAI develops numerical techniques, parallel algorithms and specialized software tools to support and optimize industrial simulations. Moreover, it implements custom software solutions for production and logistics, and offers calculations on high-performance computers. Its services and products are based on state-of-the-art metho...

Language interoperability for high-performance parallel scientific components

International Nuclear Information System (INIS)

Elliot, N; Kohn, S; Smolinski, B

1999-01-01

With the increasing complexity and interdisciplinary nature of scientific applications, code reuse is becoming increasingly important in scientific computing. One method for facilitating code reuse is the use of components technologies, which have been used widely in industry. However, components have only recently worked their way into scientific computing. Language interoperability is an important underlying technology for these component architectures. In this paper, we present an approach to language interoperability for a high-performance parallel, component architecture being developed by the Common Component Architecture (CCA) group. Our approach is based on Interface Definition Language (IDL) techniques. We have developed a Scientific Interface Definition Language (SIDL), as well as bindings to C and Fortran. We have also developed a SIDL compiler and run-time library support for reference counting, reflection, object management, and exception handling (Babel). Results from using Babel to call a standard numerical solver library (written in C) from C and Fortran show that the cost of using Babel is minimal, where as the savings in development time and the benefits of object-oriented development support for C and Fortran far outweigh the costs

Molecular Science Computing Facility Scientific Challenges: Linking Across Scales

Energy Technology Data Exchange (ETDEWEB)

De Jong, Wibe A.; Windus, Theresa L.

2005-07-01

The purpose of this document is to define the evolving science drivers for performing environmental molecular research at the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL) and to provide guidance associated with the next-generation high-performance computing center that must be developed at EMSL's Molecular Science Computing Facility (MSCF) in order to address this critical research. The MSCF is the pre-eminent computing facility?supported by the U.S. Department of Energy's (DOE's) Office of Biological and Environmental Research (BER)?tailored to provide the fastest time-to-solution for current computational challenges in chemistry and biology, as well as providing the means for broad research in the molecular and environmental sciences. The MSCF provides integral resources and expertise to emerging EMSL Scientific Grand Challenges and Collaborative Access Teams that are designed to leverage the multiple integrated research capabilities of EMSL, thereby creating a synergy between computation and experiment to address environmental molecular science challenges critical to DOE and the nation.

DOE Advanced Scientific Computing Advisory Subcommittee (ASCAC) Report: Top Ten Exascale Research Challenges

Energy Technology Data Exchange (ETDEWEB)

Lucas, Robert [University of Southern California, Information Sciences Institute; Ang, James [Sandia National Laboratories; Bergman, Keren [Columbia University; Borkar, Shekhar [Intel; Carlson, William [Institute for Defense Analyses; Carrington, Laura [University of California, San Diego; Chiu, George [IBM; Colwell, Robert [DARPA; Dally, William [NVIDIA; Dongarra, Jack [University of Tennessee; Geist, Al [Oak Ridge National Laboratory; Haring, Rud [IBM; Hittinger, Jeffrey [Lawrence Livermore National Laboratory; Hoisie, Adolfy [Pacific Northwest National Laboratory; Klein, Dean Micron; Kogge, Peter [University of Notre Dame; Lethin, Richard [Reservoir Labs; Sarkar, Vivek [Rice University; Schreiber, Robert [Hewlett Packard; Shalf, John [Lawrence Berkeley National Laboratory; Sterling, Thomas [Indiana University; Stevens, Rick [Argonne National Laboratory; Bashor, Jon [Lawrence Berkeley National Laboratory; Brightwell, Ron [Sandia National Laboratories; Coteus, Paul [IBM; Debenedictus, Erik [Sandia National Laboratories; Hiller, Jon [Science and Technology Associates; Kim, K. H. [IBM; Langston, Harper [Reservoir Labs; Murphy, Richard Micron; Webster, Clayton [Oak Ridge National Laboratory; Wild, Stefan [Argonne National Laboratory; Grider, Gary [Los Alamos National Laboratory; Ross, Rob [Argonne National Laboratory; Leyffer, Sven [Argonne National Laboratory; Laros III, James [Sandia National Laboratories

2014-02-10

Exascale computing systems are essential for the scientific fields that will transform the 21st century global economy, including energy, biotechnology, nanotechnology, and materials science. Progress in these fields is predicated on the ability to perform advanced scientific and engineering simulations, and analyze the deluge of data. On July 29, 2013, ASCAC was charged by Patricia Dehmer, the Acting Director of the Office of Science, to assemble a subcommittee to provide advice on exascale computing. This subcommittee was directed to return a list of no more than ten technical approaches (hardware and software) that will enable the development of a system that achieves the Department's goals for exascale computing. Numerous reports over the past few years have documented the technical challenges and the non¬-viability of simply scaling existing computer designs to reach exascale. The technical challenges revolve around energy consumption, memory performance, resilience, extreme concurrency, and big data. Drawing from these reports and more recent experience, this ASCAC subcommittee has identified the top ten computing technology advancements that are critical to making a capable, economically viable, exascale system.

Quality assurance of analytical, scientific, and design computer programs for nuclear power plants

International Nuclear Information System (INIS)

1994-06-01

This Standard applies to the design and development, modification, documentation, execution, and configuration management of computer programs used to perform analytical, scientific, and design computations during the design and analysis of safety-related nuclear power plant equipment, systems, structures, and components as identified by the owner. 2 figs

Quality assurance of analytical, scientific, and design computer programs for nuclear power plants

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-06-01

This Standard applies to the design and development, modification, documentation, execution, and configuration management of computer programs used to perform analytical, scientific, and design computations during the design and analysis of safety-related nuclear power plant equipment, systems, structures, and components as identified by the owner. 2 figs.

Heterogeneous High Throughput Scientific Computing with APM X-Gene and Intel Xeon Phi

CERN Document Server

Abdurachmanov, David; Elmer, Peter; Eulisse, Giulio; Knight, Robert; Muzaffar, Shahzad

2014-01-01

Electrical power requirements will be a constraint on the future growth of Distributed High Throughput Computing (DHTC) as used by High Energy Physics. Performance-per-watt is a critical metric for the evaluation of computer architectures for cost- efficient computing. Additionally, future performance growth will come from heterogeneous, many-core, and high computing density platforms with specialized processors. In this paper, we examine the Intel Xeon Phi Many Integrated Cores (MIC) co-processor and Applied Micro X-Gene ARMv8 64-bit low-power server system-on-a-chip (SoC) solutions for scientific computing applications. We report our experience on software porting, performance and energy efficiency and evaluate the potential for use of such technologies in the context of distributed computing systems such as the Worldwide LHC Computing Grid (WLCG).

Heterogeneous High Throughput Scientific Computing with APM X-Gene and Intel Xeon Phi

Science.gov (United States)

Abdurachmanov, David; Bockelman, Brian; Elmer, Peter; Eulisse, Giulio; Knight, Robert; Muzaffar, Shahzad

2015-05-01

Electrical power requirements will be a constraint on the future growth of Distributed High Throughput Computing (DHTC) as used by High Energy Physics. Performance-per-watt is a critical metric for the evaluation of computer architectures for cost- efficient computing. Additionally, future performance growth will come from heterogeneous, many-core, and high computing density platforms with specialized processors. In this paper, we examine the Intel Xeon Phi Many Integrated Cores (MIC) co-processor and Applied Micro X-Gene ARMv8 64-bit low-power server system-on-a-chip (SoC) solutions for scientific computing applications. We report our experience on software porting, performance and energy efficiency and evaluate the potential for use of such technologies in the context of distributed computing systems such as the Worldwide LHC Computing Grid (WLCG).

Heterogeneous High Throughput Scientific Computing with APM X-Gene and Intel Xeon Phi

International Nuclear Information System (INIS)

Abdurachmanov, David; Bockelman, Brian; Elmer, Peter; Eulisse, Giulio; Muzaffar, Shahzad; Knight, Robert

2015-01-01

Electrical power requirements will be a constraint on the future growth of Distributed High Throughput Computing (DHTC) as used by High Energy Physics. Performance-per-watt is a critical metric for the evaluation of computer architectures for cost- efficient computing. Additionally, future performance growth will come from heterogeneous, many-core, and high computing density platforms with specialized processors. In this paper, we examine the Intel Xeon Phi Many Integrated Cores (MIC) co-processor and Applied Micro X-Gene ARMv8 64-bit low-power server system-on-a-chip (SoC) solutions for scientific computing applications. We report our experience on software porting, performance and energy efficiency and evaluate the potential for use of such technologies in the context of distributed computing systems such as the Worldwide LHC Computing Grid (WLCG). (paper)

OPENING REMARKS: SciDAC: Scientific Discovery through Advanced Computing

Science.gov (United States)

Strayer, Michael

2005-01-01

with industry and virtual prototyping. New instruments of collaboration will include institutes and centers while summer schools, workshops and outreach will invite new talent and expertise. Computational science adds new dimensions to science and its practice. Disciplines of fusion, accelerator science, and combustion are poised to blur the boundaries between pure and applied science. As we open the door into FY2006 we shall see a landscape of new scientific challenges: in biology, chemistry, materials, and astrophysics to name a few. The enabling technologies of SciDAC have been transformational as drivers of change. Planning for major new software systems assumes a base line employing Common Component Architectures and this has become a household word for new software projects. While grid algorithms and mesh refinement software have transformed applications software, data management and visualization have transformed our understanding of science from data. The Gordon Bell prize now seems to be dominated by computational science and solvers developed by TOPS ISIC. The priorities of the Office of Science in the Department of Energy are clear. The 20 year facilities plan is driven by new science. High performance computing is placed amongst the two highest priorities. Moore's law says that by the end of the next cycle of SciDAC we shall have peta-flop computers. The challenges of petascale computing are enormous. These and the associated computational science are the highest priorities for computing within the Office of Science. Our effort in Leadership Class computing is just a first step towards this goal. Clearly, computational science at this scale will face enormous challenges and possibilities. Performance evaluation and prediction will be critical to unraveling the needed software technologies. We must not lose sight of our overarching goal—that of scientific discovery. Science does not stand still and the landscape of science discovery and computing holds

Compiler Technology for Parallel Scientific Computation

Directory of Open Access Journals (Sweden)

Can Özturan

1994-01-01

Full Text Available There is a need for compiler technology that, given the source program, will generate efficient parallel codes for different architectures with minimal user involvement. Parallel computation is becoming indispensable in solving large-scale problems in science and engineering. Yet, the use of parallel computation is limited by the high costs of developing the needed software. To overcome this difficulty we advocate a comprehensive approach to the development of scalable architecture-independent software for scientific computation based on our experience with equational programming language (EPL. Our approach is based on a program decomposition, parallel code synthesis, and run-time support for parallel scientific computation. The program decomposition is guided by the source program annotations provided by the user. The synthesis of parallel code is based on configurations that describe the overall computation as a set of interacting components. Run-time support is provided by the compiler-generated code that redistributes computation and data during object program execution. The generated parallel code is optimized using techniques of data alignment, operator placement, wavefront determination, and memory optimization. In this article we discuss annotations, configurations, parallel code generation, and run-time support suitable for parallel programs written in the functional parallel programming language EPL and in Fortran.

National facility for advanced computational science: A sustainable path to scientific discovery

Energy Technology Data Exchange (ETDEWEB)

Simon, Horst; Kramer, William; Saphir, William; Shalf, John; Bailey, David; Oliker, Leonid; Banda, Michael; McCurdy, C. William; Hules, John; Canning, Andrew; Day, Marc; Colella, Philip; Serafini, David; Wehner, Michael; Nugent, Peter

2004-04-02

Lawrence Berkeley National Laboratory (Berkeley Lab) proposes to create a National Facility for Advanced Computational Science (NFACS) and to establish a new partnership between the American computer industry and a national consortium of laboratories, universities, and computing facilities. NFACS will provide leadership-class scientific computing capability to scientists and engineers nationwide, independent of their institutional affiliation or source of funding. This partnership will bring into existence a new class of computational capability in the United States that is optimal for science and will create a sustainable path towards petaflops performance.

Scientific computing an introduction using Maple and Matlab

CERN Document Server

Gander, Walter; Kwok, Felix

2014-01-01

Scientific computing is the study of how to use computers effectively to solve problems that arise from the mathematical modeling of phenomena in science and engineering. It is based on mathematics, numerical and symbolic/algebraic computations and visualization. This book serves as an introduction to both the theory and practice of scientific computing, with each chapter presenting the basic algorithms that serve as the workhorses of many scientific codes; we explain both the theory behind these algorithms and how they must be implemented in order to work reliably in finite-precision arithmetic. The book includes many programs written in Matlab and Maple – Maple is often used to derive numerical algorithms, whereas Matlab is used to implement them. The theory is developed in such a way that students can learn by themselves as they work through the text. Each chapter contains numerous examples and problems to help readers understand the material “hands-on”.

Introduction to the LaRC central scientific computing complex

Science.gov (United States)

Shoosmith, John N.

1993-01-01

The computers and associated equipment that make up the Central Scientific Computing Complex of the Langley Research Center are briefly described. The electronic networks that provide access to the various components of the complex and a number of areas that can be used by Langley and contractors staff for special applications (scientific visualization, image processing, software engineering, and grid generation) are also described. Flight simulation facilities that use the central computers are described. Management of the complex, procedures for its use, and available services and resources are discussed. This document is intended for new users of the complex, for current users who wish to keep appraised of changes, and for visitors who need to understand the role of central scientific computers at Langley.

Large-scale computation at PSI scientific achievements and future requirements

International Nuclear Information System (INIS)

Adelmann, A.; Markushin, V.

2008-11-01

Computational modelling and simulation are among the disciplines that have seen the most dramatic growth in capabilities in the 2Oth Century. Within the past two decades, scientific computing has become an important contributor to all scientific research programs. Computational modelling and simulation are particularly indispensable for solving research problems that are unsolvable by traditional theoretical and experimental approaches, hazardous to study, or time consuming or expensive to solve by traditional means. Many such research areas are found in PSI's research portfolio. Advances in computing technologies (including hardware and software) during the past decade have set the stage for a major step forward in modelling and simulation. We have now arrived at a situation where we have a number of otherwise unsolvable problems, where simulations are as complex as the systems under study. In 2008 the High-Performance Computing (HPC) community entered the petascale area with the heterogeneous Opteron/Cell machine, called Road Runner built by IBM for the Los Alamos National Laboratory. We are on the brink of a time where the availability of many hundreds of thousands of cores will open up new challenging possibilities in physics, algorithms (numerical mathematics) and computer science. However, to deliver on this promise, it is not enough to provide 'peak' performance in terms of peta-flops, the maximum theoretical speed a computer can attain. Most important, this must be translated into corresponding increase in the capabilities of scientific codes. This is a daunting problem that can only be solved by increasing investment in hardware, in the accompanying system software that enables the reliable use of high-end computers, in scientific competence i.e. the mathematical (parallel) algorithms that are the basis of the codes, and education. In the case of Switzerland, the white paper 'Swiss National Strategic Plan for High Performance Computing and Networking

Large-scale computation at PSI scientific achievements and future requirements

Energy Technology Data Exchange (ETDEWEB)

Adelmann, A.; Markushin, V

2008-11-15

Computational modelling and simulation are among the disciplines that have seen the most dramatic growth in capabilities in the 2Oth Century. Within the past two decades, scientific computing has become an important contributor to all scientific research programs. Computational modelling and simulation are particularly indispensable for solving research problems that are unsolvable by traditional theoretical and experimental approaches, hazardous to study, or time consuming or expensive to solve by traditional means. Many such research areas are found in PSI's research portfolio. Advances in computing technologies (including hardware and software) during the past decade have set the stage for a major step forward in modelling and simulation. We have now arrived at a situation where we have a number of otherwise unsolvable problems, where simulations are as complex as the systems under study. In 2008 the High-Performance Computing (HPC) community entered the petascale area with the heterogeneous Opteron/Cell machine, called Road Runner built by IBM for the Los Alamos National Laboratory. We are on the brink of a time where the availability of many hundreds of thousands of cores will open up new challenging possibilities in physics, algorithms (numerical mathematics) and computer science. However, to deliver on this promise, it is not enough to provide 'peak' performance in terms of peta-flops, the maximum theoretical speed a computer can attain. Most important, this must be translated into corresponding increase in the capabilities of scientific codes. This is a daunting problem that can only be solved by increasing investment in hardware, in the accompanying system software that enables the reliable use of high-end computers, in scientific competence i.e. the mathematical (parallel) algorithms that are the basis of the codes, and education. In the case of Switzerland, the white paper 'Swiss National Strategic Plan for High Performance Computing

Scientific applications of symbolic computation

International Nuclear Information System (INIS)

Hearn, A.C.

1976-02-01

The use of symbolic computation systems for problem solving in scientific research is reviewed. The nature of the field is described, and particular examples are considered from celestial mechanics, quantum electrodynamics and general relativity. Symbolic integration and some more recent applications of algebra systems are also discussed [fr

Performance of scientific computing platforms with MCNP4B

International Nuclear Information System (INIS)

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

1998-01-01

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

FPS scientific and supercomputers computers in chemistry

International Nuclear Information System (INIS)

Curington, I.J.

1987-01-01

FPS Array Processors, scientific computers, and highly parallel supercomputers are used in nearly all aspects of compute-intensive computational chemistry. A survey is made of work utilizing this equipment, both published and current research. The relationship of the computer architecture to computational chemistry is discussed, with specific reference to Molecular Dynamics, Quantum Monte Carlo simulations, and Molecular Graphics applications. Recent installations of the FPS T-Series are highlighted, and examples of Molecular Graphics programs running on the FPS-5000 are shown

Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters

Energy Technology Data Exchange (ETDEWEB)

Yoo, Wucherl [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Koo, Michelle [Univ. of California, Berkeley, CA (United States); Cao, Yu [California Inst. of Technology (CalTech), Pasadena, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Nugent, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); Wu, Kesheng [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2016-09-17

Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe- art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster. Our study processed many terabytes of system logs and application performance measurements collected on the HPC systems at NERSC. The implementation of our tool is generic enough to be used for analyzing the performance of other HPC systems and Big Data workows.

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.

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 ...

Advanced Scientific Computing Research Exascale Requirements Review. An Office of Science review sponsored by Advanced Scientific Computing Research, September 27-29, 2016, Rockville, Maryland

Energy Technology Data Exchange (ETDEWEB)

Almgren, Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); DeMar, Phil [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Vetter, Jeffrey [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Riley, Katherine [Argonne Leadership Computing Facility, Argonne, IL (United States); Antypas, Katie [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bard, Deborah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Coffey, Richard [Argonne National Lab. (ANL), Argonne, IL (United States); Dart, Eli [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Science Network; Dosanjh, Sudip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Gerber, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hack, James [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Monga, Inder [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Science Network; Papka, Michael E. [Argonne National Lab. (ANL), Argonne, IL (United States); Rotman, Lauren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Science Network; Straatsma, Tjerk [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wells, Jack [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bernholdt, David E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bethel, Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bosilca, George [Univ. of Tennessee, Knoxville, TN (United States); Cappello, Frank [Argonne National Lab. (ANL), Argonne, IL (United States); Gamblin, Todd [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Habib, Salman [Argonne National Lab. (ANL), Argonne, IL (United States); Hill, Judy [Oak Ridge Leadership Computing Facility, Oak Ridge, TN (United States); Hollingsworth, Jeffrey K. [Univ. of Maryland, College Park, MD (United States); McInnes, Lois Curfman [Argonne National Lab. (ANL), Argonne, IL (United States); Mohror, Kathryn [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Moore, Shirley [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Moreland, Ken [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Roser, Rob [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Shende, Sameer [Univ. of Oregon, Eugene, OR (United States); Shipman, Galen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Williams, Samuel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2017-06-20

The widespread use of computing in the American economy would not be possible without a thoughtful, exploratory research and development (R&D) community pushing the performance edge of operating systems, computer languages, and software libraries. These are the tools and building blocks — the hammers, chisels, bricks, and mortar — of the smartphone, the cloud, and the computing services on which we rely. Engineers and scientists need ever-more specialized computing tools to discover new material properties for manufacturing, make energy generation safer and more efficient, and provide insight into the fundamentals of the universe, for example. The research division of the U.S. Department of Energy’s (DOE’s) Office of Advanced Scientific Computing and Research (ASCR Research) ensures that these tools and building blocks are being developed and honed to meet the extreme needs of modern science. See also http://exascaleage.org/ascr/ for additional information.

Scientific Computing in Electrical Engineering

CERN Document Server

Amrhein, Wolfgang; Zulehner, Walter

2018-01-01

This collection of selected papers presented at the 11th International Conference on Scientific Computing in Electrical Engineering (SCEE), held in St. Wolfgang, Austria, in 2016, showcases the state of the art in SCEE. The aim of the SCEE 2016 conference was to bring together scientists from academia and industry, mathematicians, electrical engineers, computer scientists, and physicists, and to promote intensive discussions on industrially relevant mathematical problems, with an emphasis on the modeling and numerical simulation of electronic circuits and devices, electromagnetic fields, and coupled problems. The focus in methodology was on model order reduction and uncertainty quantification. This extensive reference work is divided into six parts: Computational Electromagnetics, Circuit and Device Modeling and Simulation, Coupled Problems and Multi‐Scale Approaches in Space and Time, Mathematical and Computational Methods Including Uncertainty Quantification, Model Order Reduction, and Industrial Applicat...

Advanced scientific computational methods and their applications to nuclear technologies. (4) Overview of scientific computational methods, introduction of continuum simulation methods and their applications (4)

International Nuclear Information System (INIS)

Sekimura, Naoto; Okita, Taira

2006-01-01

Scientific computational methods have advanced remarkably with the progress of nuclear development. They have played the role of weft connecting each realm of nuclear engineering and then an introductory course of advanced scientific computational methods and their applications to nuclear technologies were prepared in serial form. This is the fourth issue showing the overview of scientific computational methods with the introduction of continuum simulation methods and their applications. Simulation methods on physical radiation effects on materials are reviewed based on the process such as binary collision approximation, molecular dynamics, kinematic Monte Carlo method, reaction rate method and dislocation dynamics. (T. Tanaka)

Elastic Scheduling of Scientific Workflows under Deadline Constraints in Cloud Computing Environments

Directory of Open Access Journals (Sweden)

Nazia Anwar

2018-01-01

Full Text Available Scientific workflow applications are collections of several structured activities and fine-grained computational tasks. Scientific workflow scheduling in cloud computing is a challenging research topic due to its distinctive features. In cloud environments, it has become critical to perform efficient task scheduling resulting in reduced scheduling overhead, minimized cost and maximized resource utilization while still meeting the user-specified overall deadline. This paper proposes a strategy, Dynamic Scheduling of Bag of Tasks based workflows (DSB, for scheduling scientific workflows with the aim to minimize financial cost of leasing Virtual Machines (VMs under a user-defined deadline constraint. The proposed model groups the workflow into Bag of Tasks (BoTs based on data dependency and priority constraints and thereafter optimizes the allocation and scheduling of BoTs on elastic, heterogeneous and dynamically provisioned cloud resources called VMs in order to attain the proposed method’s objectives. The proposed approach considers pay-as-you-go Infrastructure as a Service (IaaS clouds having inherent features such as elasticity, abundance, heterogeneity and VM provisioning delays. A trace-based simulation using benchmark scientific workflows representing real world applications, demonstrates a significant reduction in workflow computation cost while the workflow deadline is met. The results validate that the proposed model produces better success rates to meet deadlines and cost efficiencies in comparison to adapted state-of-the-art algorithms for similar problems.

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...

High-performance dual-speed CCD camera system for scientific imaging

Science.gov (United States)

Simpson, Raymond W.

1996-03-01

Traditionally, scientific camera systems were partitioned with a `camera head' containing the CCD and its support circuitry and a camera controller, which provided analog to digital conversion, timing, control, computer interfacing, and power. A new, unitized high performance scientific CCD camera with dual speed readout at 1 X 106 or 5 X 106 pixels per second, 12 bit digital gray scale, high performance thermoelectric cooling, and built in composite video output is described. This camera provides all digital, analog, and cooling functions in a single compact unit. The new system incorporates the A/C converter, timing, control and computer interfacing in the camera, with the power supply remaining a separate remote unit. A 100 Mbyte/second serial link transfers data over copper or fiber media to a variety of host computers, including Sun, SGI, SCSI, PCI, EISA, and Apple Macintosh. Having all the digital and analog functions in the camera made it possible to modify this system for the Woods Hole Oceanographic Institution for use on a remote controlled submersible vehicle. The oceanographic version achieves 16 bit dynamic range at 1.5 X 105 pixels/second, can be operated at depths of 3 kilometers, and transfers data to the surface via a real time fiber optic link.

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.

Position Paper: Applying Machine Learning to Software Analysis to Achieve Trusted, Repeatable Scientific Computing

Energy Technology Data Exchange (ETDEWEB)

Prowell, Stacy J [ORNL; Symons, Christopher T [ORNL

2015-01-01

Producing trusted results from high-performance codes is essential for policy and has significant economic impact. We propose combining rigorous analytical methods with machine learning techniques to achieve the goal of repeatable, trustworthy scientific computing.

Age and Scientific Performance.

Science.gov (United States)

Cole, Stephen

1979-01-01

The long-standing belief that age is negatively associated with scientific productivity and creativity is shown to be based upon incorrect analysis of data. Studies reported in this article suggest that the relationship between age and scientific performance is influenced by the operation of the reward system. (Author)

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.

Software Defects, Scientific Computation and the Scientific Method

CERN Multimedia

CERN. Geneva

2011-01-01

Computation has rapidly grown in the last 50 years so that in many scientific areas it is the dominant partner in the practice of science. Unfortunately, unlike the experimental sciences, it does not adhere well to the principles of the scientific method as espoused by, for example, the philosopher Karl Popper. Such principles are built around the notions of deniability and reproducibility. Although much research effort has been spent on measuring the density of software defects, much less has been spent on the more difficult problem of measuring their effect on the output of a program. This talk explores these issues with numerous examples suggesting how this situation might be improved to match the demands of modern science. Finally it develops a theoretical model based on an amalgam of statistical mechanics and Hartley/Shannon information theory which suggests that software systems have strong implementation independent behaviour and supports the widely observed phenomenon that defects clust...

A Computing Environment to Support Repeatable Scientific Big Data Experimentation of World-Wide Scientific Literature

Energy Technology Data Exchange (ETDEWEB)

Schlicher, Bob G [ORNL; Kulesz, James J [ORNL; Abercrombie, Robert K [ORNL; Kruse, Kara L [ORNL

2015-01-01

A principal tenant of the scientific method is that experiments must be repeatable and relies on ceteris paribus (i.e., all other things being equal). As a scientific community, involved in data sciences, we must investigate ways to establish an environment where experiments can be repeated. We can no longer allude to where the data comes from, we must add rigor to the data collection and management process from which our analysis is conducted. This paper describes a computing environment to support repeatable scientific big data experimentation of world-wide scientific literature, and recommends a system that is housed at the Oak Ridge National Laboratory in order to provide value to investigators from government agencies, academic institutions, and industry entities. The described computing environment also adheres to the recently instituted digital data management plan mandated by multiple US government agencies, which involves all stages of the digital data life cycle including capture, analysis, sharing, and preservation. It particularly focuses on the sharing and preservation of digital research data. The details of this computing environment are explained within the context of cloud services by the three layer classification of Software as a Service , Platform as a Service , and Infrastructure as a Service .

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

DOE Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee Report on Scientific and Technical Information

Energy Technology Data Exchange (ETDEWEB)

Hey, Tony [eScience Institute, University of Washington; Agarwal, Deborah [Lawrence Berkeley National Laboratory; Borgman, Christine [University of California, Los Angeles; Cartaro, Concetta [SLAC National Accelerator Laboratory; Crivelli, Silvia [Lawrence Berkeley National Laboratory; Van Dam, Kerstin Kleese [Pacific Northwest National Laboratory; Luce, Richard [University of Oklahoma; Arjun, Shankar [CADES, Oak Ridge National Laboratory; Trefethen, Anne [University of Oxford; Wade, Alex [Microsoft Research, Microsoft Corporation; Williams, Dean [Lawrence Livermore National Laboratory

2015-09-04

The Advanced Scientific Computing Advisory Committee (ASCAC) was charged to form a standing subcommittee to review the Department of Energy’s Office of Scientific and Technical Information (OSTI) and to begin by assessing the quality and effectiveness of OSTI’s recent and current products and services and to comment on its mission and future directions in the rapidly changing environment for scientific publication and data. The Committee met with OSTI staff and reviewed available products, services and other materials. This report summaries their initial findings and recommendations.

Comparing the performance of SIMD computers by running large air pollution models

DEFF Research Database (Denmark)

Brown, J.; Hansen, Per Christian; Wasniewski, J.

1996-01-01

To compare the performance and use of three massively parallel SIMD computers, we implemented a large air pollution model on these computers. Using a realistic large-scale model, we gained detailed insight about the performance of the computers involved when used to solve large-scale scientific...... problems that involve several types of numerical computations. The computers used in our study are the Connection Machines CM-200 and CM-5, and the MasPar MP-2216...

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...

Scientific Inquiry Self-Efficacy and Computer Game Self-Efficacy as Predictors and Outcomes of Middle School Boys' and Girls' Performance in a Science Assessment in a Virtual Environment

Science.gov (United States)

Bergey, Bradley W.; Ketelhut, Diane Jass; Liang, Senfeng; Natarajan, Uma; Karakus, Melissa

2015-01-01

The primary aim of the study was to examine whether performance on a science assessment in an immersive virtual environment was associated with changes in scientific inquiry self-efficacy. A secondary aim of the study was to examine whether performance on the science assessment was equitable for students with different levels of computer game…

The 12-th INS scientific computational programs

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-06-01

This issue is the collection of the paper on INS scientific computational programs. Separate abstracts were presented for 3 of the papers in this report. The remaining 5 were considered outside the subject scope of INIS. (J.P.N.)

Educational NASA Computational and Scientific Studies (enCOMPASS)

Science.gov (United States)

Memarsadeghi, Nargess

2013-01-01

Educational NASA Computational and Scientific Studies (enCOMPASS) is an educational project of NASA Goddard Space Flight Center aimed at bridging the gap between computational objectives and needs of NASA's scientific research, missions, and projects, and academia's latest advances in applied mathematics and computer science. enCOMPASS achieves this goal via bidirectional collaboration and communication between NASA and academia. Using developed NASA Computational Case Studies in university computer science/engineering and applied mathematics classes is a way of addressing NASA's goals of contributing to the Science, Technology, Education, and Math (STEM) National Objective. The enCOMPASS Web site at http://encompass.gsfc.nasa.gov provides additional information. There are currently nine enCOMPASS case studies developed in areas of earth sciences, planetary sciences, and astrophysics. Some of these case studies have been published in AIP and IEEE's Computing in Science and Engineering magazines. A few university professors have used enCOMPASS case studies in their computational classes and contributed their findings to NASA scientists. In these case studies, after introducing the science area, the specific problem, and related NASA missions, students are first asked to solve a known problem using NASA data and past approaches used and often published in a scientific/research paper. Then, after learning about the NASA application and related computational tools and approaches for solving the proposed problem, students are given a harder problem as a challenge for them to research and develop solutions for. This project provides a model for NASA scientists and engineers on one side, and university students, faculty, and researchers in computer science and applied mathematics on the other side, to learn from each other's areas of work, computational needs and solutions, and the latest advances in research and development. This innovation takes NASA science and

Scientific Computing and Apple's Intel Transition

CERN Document Server

CERN. Geneva

2006-01-01

Intel's published processor roadmap and how it may affect the future of personal and scientific computing About the speaker: Eric Albert is Senior Software Engineer in Apple's Core Technologies group. During Mac OS X's transition to Intel processors he has worked on almost every part of the operating system, from the OS kernel and compiler tools to appli...

Advanced scientific computational methods and their applications of nuclear technologies. (1) Overview of scientific computational methods, introduction of continuum simulation methods and their applications (1)

International Nuclear Information System (INIS)

Oka, Yoshiaki; Okuda, Hiroshi

2006-01-01

Scientific computational methods have advanced remarkably with the progress of nuclear development. They have played the role of weft connecting each realm of nuclear engineering and then an introductory course of advanced scientific computational methods and their applications to nuclear technologies were prepared in serial form. This is the first issue showing their overview and introduction of continuum simulation methods. Finite element method as their applications is also reviewed. (T. Tanaka)

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.

Integrating multiple scientific computing needs via a Private Cloud infrastructure

International Nuclear Information System (INIS)

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

2014-01-01

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

Learning SciPy for numerical and scientific computing

CERN Document Server

Silva

2013-01-01

A step-by-step practical tutorial with plenty of examples on research-based problems from various areas of science, that prove how simple, yet effective, it is to provide solutions based on SciPy. This book is targeted at anyone with basic knowledge of Python, a somewhat advanced command of mathematics/physics, and an interest in engineering or scientific applications---this is broadly what we refer to as scientific computing.This book will be of critical importance to programmers and scientists who have basic Python knowledge and would like to be able to do scientific and numerical computatio

Scientific Computing in the CH Programming Language

Directory of Open Access Journals (Sweden)

Harry H. Cheng

1993-01-01

Full Text Available We have developed a general-purpose block-structured interpretive programming Ianguage. The syntax and semantics of this language called CH are similar to C. CH retains most features of C from the scientific computing point of view. In this paper, the extension of C to CH for numerical computation of real numbers will be described. Metanumbers of −0.0, 0.0, Inf, −Inf, and NaN are introduced in CH. Through these metanumbers, the power of the IEEE 754 arithmetic standard is easily available to the programmer. These metanumbers are extended to commonly used mathematical functions in the spirit of the IEEE 754 standard and ANSI C. The definitions for manipulation of these metanumbers in I/O; arithmetic, relational, and logic operations; and built-in polymorphic mathematical functions are defined. The capabilities of bitwise, assignment, address and indirection, increment and decrement, as well as type conversion operations in ANSI C are extended in CH. In this paper, mainly new linguistic features of CH in comparison to C will be described. Example programs programmed in CH with metanumbers and polymorphic mathematical functions will demonstrate capabilities of CH in scientific computing.

BurstMem: A High-Performance Burst Buffer System for Scientific Applications

Energy Technology Data Exchange (ETDEWEB)

Wang, Teng [Auburn University, Auburn, Alabama; Oral, H Sarp [ORNL; Wang, Yandong [Auburn University, Auburn, Alabama; Settlemyer, Bradley W [ORNL; Atchley, Scott [ORNL; Yu, Weikuan [Auburn University, Auburn, Alabama

2014-01-01

The growth of computing power on large-scale sys- tems requires commensurate high-bandwidth I/O system. Many parallel file systems are designed to provide fast sustainable I/O in response to applications soaring requirements. To meet this need, a novel system is imperative to temporarily buffer the bursty I/O and gradually flush datasets to long-term parallel file systems. In this paper, we introduce the design of BurstMem, a high- performance burst buffer system. BurstMem provides a storage framework with efficient storage and communication manage- ment strategies. Our experiments demonstrate that BurstMem is able to speed up the I/O performance of scientific applications by up to 8.5 on leadership computer systems.

Results of data base management system parameterized performance testing related to GSFC scientific applications

Science.gov (United States)

Carchedi, C. H.; Gough, T. L.; Huston, H. A.

1983-01-01

The results of a variety of tests designed to demonstrate and evaluate the performance of several commercially available data base management system (DBMS) products compatible with the Digital Equipment Corporation VAX 11/780 computer system are summarized. The tests were performed on the INGRES, ORACLE, and SEED DBMS products employing applications that were similar to scientific applications under development by NASA. The objectives of this testing included determining the strength and weaknesses of the candidate systems, performance trade-offs of various design alternatives and the impact of some installation and environmental (computer related) influences.

Assessing Scientific Performance.

Science.gov (United States)

Weiner, John M.; And Others

1984-01-01

A method for assessing scientific performance based on relationships displayed numerically in published documents is proposed and illustrated using published documents in pediatric oncology for the period 1979-1982. Contributions of a major clinical investigations group, the Childrens Cancer Study Group, are analyzed. Twenty-nine references are…

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

NARCIS (Netherlands)

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

2011-01-01

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

Space and Earth Sciences, Computer Systems, and Scientific Data Analysis Support, Volume 1

Science.gov (United States)

Estes, Ronald H. (Editor)

1993-01-01

This Final Progress Report covers the specific technical activities of Hughes STX Corporation for the last contract triannual period of 1 June through 30 Sep. 1993, in support of assigned task activities at Goddard Space Flight Center (GSFC). It also provides a brief summary of work throughout the contract period of performance on each active task. Technical activity is presented in Volume 1, while financial and level-of-effort data is presented in Volume 2. Technical support was provided to all Division and Laboratories of Goddard's Space Sciences and Earth Sciences Directorates. Types of support include: scientific programming, systems programming, computer management, mission planning, scientific investigation, data analysis, data processing, data base creation and maintenance, instrumentation development, and management services. Mission and instruments supported include: ROSAT, Astro-D, BBXRT, XTE, AXAF, GRO, COBE, WIND, UIT, SMM, STIS, HEIDI, DE, URAP, CRRES, Voyagers, ISEE, San Marco, LAGEOS, TOPEX/Poseidon, Pioneer-Venus, Galileo, Cassini, Nimbus-7/TOMS, Meteor-3/TOMS, FIFE, BOREAS, TRMM, AVHRR, and Landsat. Accomplishments include: development of computing programs for mission science and data analysis, supercomputer applications support, computer network support, computational upgrades for data archival and analysis centers, end-to-end management for mission data flow, scientific modeling and results in the fields of space and Earth physics, planning and design of GSFC VO DAAC and VO IMS, fabrication, assembly, and testing of mission instrumentation, and design of mission operations center.

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.

Multidimensional Environmental Data Resource Brokering on Computational Grids and Scientific Clouds

Science.gov (United States)

Montella, Raffaele; Giunta, Giulio; Laccetti, Giuliano

Grid computing has widely evolved over the past years, and its capabilities have found their way even into business products and are no longer relegated to scientific applications. Today, grid computing technology is not restricted to a set of specific grid open source or industrial products, but rather it is comprised of a set of capabilities virtually within any kind of software to create shared and highly collaborative production environments. These environments are focused on computational (workload) capabilities and the integration of information (data) into those computational capabilities. An active grid computing application field is the fully virtualization of scientific instruments in order to increase their availability and decrease operational and maintaining costs. Computational and information grids allow to manage real-world objects in a service-oriented way using industrial world-spread standards.

Computer network access to scientific information systems for minority universities

Science.gov (United States)

Thomas, Valerie L.; Wakim, Nagi T.

1993-08-01

The evolution of computer networking technology has lead to the establishment of a massive networking infrastructure which interconnects various types of computing resources at many government, academic, and corporate institutions. A large segment of this infrastructure has been developed to facilitate information exchange and resource sharing within the scientific community. The National Aeronautics and Space Administration (NASA) supports both the development and the application of computer networks which provide its community with access to many valuable multi-disciplinary scientific information systems and on-line databases. Recognizing the need to extend the benefits of this advanced networking technology to the under-represented community, the National Space Science Data Center (NSSDC) in the Space Data and Computing Division at the Goddard Space Flight Center has developed the Minority University-Space Interdisciplinary Network (MU-SPIN) Program: a major networking and education initiative for Historically Black Colleges and Universities (HBCUs) and Minority Universities (MUs). In this paper, we will briefly explain the various components of the MU-SPIN Program while highlighting how, by providing access to scientific information systems and on-line data, it promotes a higher level of collaboration among faculty and students and NASA scientists.

JINR CLOUD SERVICE FOR SCIENTIFIC AND ENGINEERING COMPUTATIONS

Directory of Open Access Journals (Sweden)

Nikita A. Balashov

2018-03-01

Full Text Available Pretty often small research scientific groups do not have access to powerful enough computational resources required for their research work to be productive. Global computational infrastructures used by large scientific collaborations can be challenging for small research teams because of bureaucracy overhead as well as usage complexity of underlying tools. Some researchers buy a set of powerful servers to cover their own needs in computational resources. A drawback of such approach is a necessity to take care about proper hosting environment for these hardware and maintenance which requires a certain level of expertise. Moreover a lot of time such resources may be underutilized because а researcher needs to spend a certain amount of time to prepare computations and to analyze results as well as he doesn’t always need all resources of modern multi-core CPUs servers. The JINR cloud team developed a service which provides an access for scientists of small research groups from JINR and its Member State organizations to computational resources via problem-oriented (i.e. application-specific web-interface. It allows a scientist to focus on his research domain by interacting with the service in a convenient way via browser and abstracting away from underlying infrastructure as well as its maintenance. A user just sets a required values for his job via web-interface and specify a location for uploading a result. The computational workloads are done on the virtual machines deployed in the JINR cloud infrastructure.

Ontology-Driven Discovery of Scientific Computational Entities

Science.gov (United States)

Brazier, Pearl W.

2010-01-01

Many geoscientists use modern computational resources, such as software applications, Web services, scientific workflows and datasets that are readily available on the Internet, to support their research and many common tasks. These resources are often shared via human contact and sometimes stored in data portals; however, they are not necessarily…

Autonomy vs. dependency of scientific collaboration in scientific performance

Energy Technology Data Exchange (ETDEWEB)

Chinchilla-Rodriguez, Z.; Miguel, S.; Perianes-Rodriguez, A.; Ovalle-Perandones, M.A.; Olmeda-Gomez, C.

2016-07-01

This article explores the capacity of Latin America in the generation of scientific knowledge and its visibility at the global level. The novelty of the contribution lies in the decomposition of leadership, plus its combination with the results of performance indicators. We compare the normalized citation of all output against the leading output, as well as scientific excellence (Chinchilla, et al. 2016a; 2016b), technological impact and the trends in collaboration types and normalized citation. The main goal is to determine to what extent the main Latin American producers of scientific output depend on collaboration to heighten research performance in terms of citation; or to the contrary, whether there is enough autonomy and capacity to leverage its competitiveness through the design of research and development agendas. To the best of our knowledge this is the first study adopting this approach at the country level within the field of N&N. (Author)

Python for Scientific Computing Education: Modeling of Queueing Systems

Directory of Open Access Journals (Sweden)

Vladimiras Dolgopolovas

2014-01-01

Full Text Available In this paper, we present the methodology for the introduction to scientific computing based on model-centered learning. We propose multiphase queueing systems as a basis for learning objects. We use Python and parallel programming for implementing the models and present the computer code and results of stochastic simulations.

Investigation of Storage Options for Scientific Computing on Grid and Cloud Facilities

International Nuclear Information System (INIS)

Garzoglio, Gabriele

2012-01-01

In recent years, several new storage technologies, such as Lustre, Hadoop, OrangeFS, and BlueArc, have emerged. While several groups have run benchmarks to characterize them under a variety of configurations, more work is needed to evaluate these technologies for the use cases of scientific computing on Grid clusters and Cloud facilities. This paper discusses our evaluation of the technologies as deployed on a test bed at FermiCloud, one of the Fermilab infrastructure-as-a-service Cloud facilities. The test bed consists of 4 server-class nodes with 40 TB of disk space and up to 50 virtual machine clients, some running on the storage server nodes themselves. With this configuration, the evaluation compares the performance of some of these technologies when deployed on virtual machines and on “bare metal” nodes. In addition to running standard benchmarks such as IOZone to check the sanity of our installation, we have run I/O intensive tests using physics-analysis applications. This paper presents how the storage solutions perform in a variety of realistic use cases of scientific computing. One interesting difference among the storage systems tested is found in a decrease in total read throughput with increasing number of client processes, which occurs in some implementations but not others.

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm.

Science.gov (United States)

Abdulhamid, Shafi'i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

2016-01-01

Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.

Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm

Science.gov (United States)

Abdulhamid, Shafi’i Muhammad; Abd Latiff, Muhammad Shafie; Abdul-Salaam, Gaddafi; Hussain Madni, Syed Hamid

2016-01-01

Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques. PMID:27384239

Scientific computing with MATLAB and Octave

CERN Document Server

Quarteroni, Alfio; Gervasio, Paola

2014-01-01

This textbook is an introduction to Scientific Computing, in which several numerical methods for the computer-based solution of certain classes of mathematical problems are illustrated. The authors show how to compute the zeros, the extrema, and the integrals of continuous functions, solve linear systems, approximate functions using polynomials and construct accurate approximations for the solution of ordinary and partial differential equations. To make the format concrete and appealing, the programming environments Matlab and Octave are adopted as faithful companions. The book contains the solutions to several problems posed in exercises and examples, often originating from important applications. At the end of each chapter, a specific section is devoted to subjects which were not addressed in the book and contains bibliographical references for a more comprehensive treatment of the material. From the review: ".... This carefully written textbook, the third English edition, contains substantial new developme...

Applications of industrial computed tomography at Los Alamos Scientific Laboratory

International Nuclear Information System (INIS)

Kruger, R.P.; Morris, R.A.; Wecksung, G.W.

1980-01-01

A research and development program was begun three years ago at the Los Alamos Scientific Laboratory (LASL) to study nonmedical applications of computed tomography. This program had several goals. The first goal was to develop the necessary reconstruction algorithms to accurately reconstruct cross sections of nonmedical industrial objects. The second goal was to be able to perform extensive tomographic simulations to determine the efficacy of tomographic reconstruction with a variety of hardware configurations. The final goal was to construct an inexpensive industrial prototype scanner with a high degree of design flexibility. The implementation of these program goals is described

Data management, code deployment, and scientific visualization to enhance scientific discovery in fusion research through advanced computing

International Nuclear Information System (INIS)

Schissel, D.P.; Finkelstein, A.; Foster, I.T.; Fredian, T.W.; Greenwald, M.J.; Hansen, C.D.; Johnson, C.R.; Keahey, K.; Klasky, S.A.; Li, K.; McCune, D.C.; Peng, Q.; Stevens, R.; Thompson, M.R.

2002-01-01

The long-term vision of the Fusion Collaboratory described in this paper is to transform fusion research and accelerate scientific understanding and innovation so as to revolutionize the design of a fusion energy source. The Collaboratory will create and deploy collaborative software tools that will enable more efficient utilization of existing experimental facilities and more effective integration of experiment, theory, and modeling. The computer science research necessary to create the Collaboratory is centered on three activities: security, remote and distributed computing, and scientific visualization. It is anticipated that the presently envisioned Fusion Collaboratory software tools will require 3 years to complete

Technologies for Large Data Management in Scientific Computing

CERN Document Server

Pace, A

2014-01-01

In recent years, intense usage of computing has been the main strategy of investigations in several scientific research projects. The progress in computing technology has opened unprecedented opportunities for systematic collection of experimental data and the associated analysis that were considered impossible only few years ago. This paper focusses on the strategies in use: it reviews the various components that are necessary for an effective solution that ensures the storage, the long term preservation, and the worldwide distribution of large quantities of data that are necessary in a large scientific research project. The paper also mentions several examples of data management solutions used in High Energy Physics for the CERN Large Hadron Collider (LHC) experiments in Geneva, Switzerland which generate more than 30,000 terabytes of data every year that need to be preserved, analyzed, and made available to a community of several tenth of thousands scientists worldwide.

Scholarly literature and the press: scientific impact and social perception of physics computing

CERN Document Server

Pia, Maria Grazia; Bell, Zane W; Dressendorfer, Paul V

2014-01-01

The broad coverage of the search for the Higgs boson in the mainstream media is a relative novelty for high energy physics (HEP) research, whose achievements have traditionally been limited to scholarly literature. This paper illustrates the results of a scientometric analysis of HEP computing in scientific literature, institutional media and the press, and a comparative overview of similar metrics concerning representative particle physics measurements. The picture emerging from these scientometric data documents the scientific impact and social perception of HEP computing. The results of this analysis suggest that improved communication of the scientific and social role of HEP computing would be beneficial to the high energy physics community.

A performance analysis of EC2 cloud computing services for scientific computing

NARCIS (Netherlands)

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

2010-01-01

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

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

Scientific Applications Performance Evaluation on Burst Buffer

KAUST Repository

Markomanolis, George S.

2017-10-19

Parallel I/O is an integral component of modern high performance computing, especially in storing and processing very large datasets, such as the case of seismic imaging, CFD, combustion and weather modeling. The storage hierarchy includes nowadays additional layers, the latest being the usage of SSD-based storage as a Burst Buffer for I/O acceleration. We present an in-depth analysis on how to use Burst Buffer for specific cases and how the internal MPI I/O aggregators operate according to the options that the user provides during his job submission. We analyze the performance of a range of I/O intensive scientific applications, at various scales on a large installation of Lustre parallel file system compared to an SSD-based Burst Buffer. Our results show a performance improvement over Lustre when using Burst Buffer. Moreover, we show results from a data hierarchy library which indicate that the standard I/O approaches are not enough to get the expected performance from this technology. The performance gain on the total execution time of the studied applications is between 1.16 and 3 times compared to Lustre. One of the test cases achieved an impressive I/O throughput of 900 GB/s on Burst Buffer.

Scientific computing in electrical engineering SCEE 2010

Energy Technology Data Exchange (ETDEWEB)

Michielsen, Bastiaan [Office National d' Etudes et de Recherches Aerospatiales (ONERA), 31 - Toulouse (France); Poirier, Jean-Rene (eds.) [LAPLACE-ENSEEIHT, Toulouse (France)

2012-07-01

Selected from papers presented at the 8th Scientific Computation in Electrical Engineering conference in Toulouse in 2010, the contributions to this volume cover every angle of numerically modelling electronic and electrical systems, including computational electromagnetics, circuit theory and simulation and device modelling. On computational electromagnetics, the chapters examine cutting-edge material ranging from low-frequency electrical machine modelling problems to issues in high-frequency scattering. Regarding circuit theory and simulation, the book details the most advanced techniques for modelling networks with many thousands of components. Modelling devices at microscopic levels is covered by a number of fundamental mathematical physics papers, while numerous papers on model order reduction help engineers and systems designers to bring their modelling of industrial-scale systems within the reach of present-day computational power. Complementing these more specific papers, the volume also contains a selection of mathematical methods which can be used in any application domain. (orig.)

Center for Technology for Advanced Scientific Component Software (TASCS)

Energy Technology Data Exchange (ETDEWEB)

Damevski, Kostadin [Virginia State Univ., Petersburg, VA (United States)

2009-03-30

A resounding success of the Scientific Discover through Advanced Computing (SciDAC) program is that high-performance computational science is now universally recognized as a critical aspect of scientific discovery [71], complementing both theoretical and experimental research. As scientific communities prepare to exploit unprecedened computing capabilities of emerging leadership-class machines for multi-model simulations at the extreme scale [72], it is more important than ever to address the technical and social challenges of geographically distributed teams that combine expertise in domain science, applied mathematics, and computer science to build robust and flexible codes that can incorporate changes over time. The Center for Technology for Advanced Scientific Component Software (TASCS) tackles these issues by exploiting component-based software development to facilitate collaborative hig-performance scientific computing.

Emerging Nanophotonic Applications Explored with Advanced Scientific Parallel Computing

Science.gov (United States)

Meng, Xiang

The domain of nanoscale optical science and technology is a combination of the classical world of electromagnetics and the quantum mechanical regime of atoms and molecules. Recent advancements in fabrication technology allows the optical structures to be scaled down to nanoscale size or even to the atomic level, which are far smaller than the wavelength they are designed for. These nanostructures can have unique, controllable, and tunable optical properties and their interactions with quantum materials can have important near-field and far-field optical response. Undoubtedly, these optical properties can have many important applications, ranging from the efficient and tunable light sources, detectors, filters, modulators, high-speed all-optical switches; to the next-generation classical and quantum computation, and biophotonic medical sensors. This emerging research of nanoscience, known as nanophotonics, is a highly interdisciplinary field requiring expertise in materials science, physics, electrical engineering, and scientific computing, modeling and simulation. It has also become an important research field for investigating the science and engineering of light-matter interactions that take place on wavelength and subwavelength scales where the nature of the nanostructured matter controls the interactions. In addition, the fast advancements in the computing capabilities, such as parallel computing, also become as a critical element for investigating advanced nanophotonic devices. This role has taken on even greater urgency with the scale-down of device dimensions, and the design for these devices require extensive memory and extremely long core hours. Thus distributed computing platforms associated with parallel computing are required for faster designs processes. Scientific parallel computing constructs mathematical models and quantitative analysis techniques, and uses the computing machines to analyze and solve otherwise intractable scientific challenges. In

Domain analysis of computational science - Fifty years of a scientific computing group

Energy Technology Data Exchange (ETDEWEB)

Tanaka, M.

2010-02-23

I employed bibliometric- and historical-methods to study the domain of the Scientific Computing group at Brookhaven National Laboratory (BNL) for an extended period of fifty years, from 1958 to 2007. I noted and confirmed the growing emergence of interdisciplinarity within the group. I also identified a strong, consistent mathematics and physics orientation within it.

New tools to aid in scientific computing and visualization

International Nuclear Information System (INIS)

Wallace, M.G.; Christian-Frear, T.L.

1992-01-01

In this paper, two computer programs are described which aid in the pre- and post-processing of computer generated data. CoMeT (Computational Mechanics Toolkit) is a customizable, interactive, graphical, menu-driven program that provides the analyst with a consistent user-friendly interface to analysis codes. Trans Vol (Transparent Volume Visualization) is a specialized tool for the scientific three-dimensional visualization of complex solids by the technique of volume rendering. Both tools are described in basic detail along with an application example concerning the simulation of contaminant migration from an underground nuclear repository

Scientific Services on the Cloud

Science.gov (United States)

Chapman, David; Joshi, Karuna P.; Yesha, Yelena; Halem, Milt; Yesha, Yaacov; Nguyen, Phuong

Scientific Computing was one of the first every applications for parallel and distributed computation. To this date, scientific applications remain some of the most compute intensive, and have inspired creation of petaflop compute infrastructure such as the Oak Ridge Jaguar and Los Alamos RoadRunner. Large dedicated hardware infrastructure has become both a blessing and a curse to the scientific community. Scientists are interested in cloud computing for much the same reason as businesses and other professionals. The hardware is provided, maintained, and administrated by a third party. Software abstraction and virtualization provide reliability, and fault tolerance. Graduated fees allow for multi-scale prototyping and execution. Cloud computing resources are only a few clicks away, and by far the easiest high performance distributed platform to gain access to. There may still be dedicated infrastructure for ultra-scale science, but the cloud can easily play a major part of the scientific computing initiative.

Scholarly literature and the press: scientific impact and social perception of physics computing

International Nuclear Information System (INIS)

Pia, M G; Basaglia, T; Bell, Z W; Dressendorfer, P V

2014-01-01

The broad coverage of the search for the Higgs boson in the mainstream media is a relative novelty for high energy physics (HEP) research, whose achievements have traditionally been limited to scholarly literature. This paper illustrates the results of a scientometric analysis of HEP computing in scientific literature, institutional media and the press, and a comparative overview of similar metrics concerning representative particle physics measurements. The picture emerging from these scientometric data documents the relationship between the scientific impact and the social perception of HEP physics research versus that of HEP computing. The results of this analysis suggest that improved communication of the scientific and social role of HEP computing via press releases from the major HEP laboratories would be beneficial to the high energy physics community.

Data-flow oriented visual programming libraries for scientific computing

NARCIS (Netherlands)

Maubach, J.M.L.; Drenth, W.D.; Sloot, P.M.A.

2002-01-01

The growing release of scientific computational software does not seem to aid the implementation of complex numerical algorithms. Released libraries lack a common standard interface with regard to for instance finite element, difference or volume discretizations. And, libraries written in standard

National Energy Research Scientific Computing Center 2007 Annual Report

Energy Technology Data Exchange (ETDEWEB)

Hules, John A.; Bashor, Jon; Wang, Ucilia; Yarris, Lynn; Preuss, Paul

2008-10-23

This report presents highlights of the research conducted on NERSC computers in a variety of scientific disciplines during the year 2007. It also reports on changes and upgrades to NERSC's systems and services aswell as activities of NERSC staff.

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.

Cyberinfrastructure and Scientific Collaboration: Application of a Virtual Team Performance Framework with Potential Relevance to Education. WCER Working Paper No. 2010-12

Science.gov (United States)

Kraemer, Sara; Thorn, Christopher A.

2010-01-01

The purpose of this exploratory study was to identify and describe some of the dimensions of scientific collaborations using high throughput computing (HTC) through the lens of a virtual team performance framework. A secondary purpose was to assess the viability of using a virtual team performance framework to study scientific collaborations using…

DOE Advanced Scientific Computing Advisory Committee (ASCAC) Report: Exascale Computing Initiative Review

Energy Technology Data Exchange (ETDEWEB)

Reed, Daniel [University of Iowa; Berzins, Martin [University of Utah; Pennington, Robert; Sarkar, Vivek [Rice University; Taylor, Valerie [Texas A& M University

2015-08-01

On November 19, 2014, the Advanced Scientific Computing Advisory Committee (ASCAC) was charged with reviewing the Department of Energy’s conceptual design for the Exascale Computing Initiative (ECI). In particular, this included assessing whether there are significant gaps in the ECI plan or areas that need to be given priority or extra management attention. Given the breadth and depth of previous reviews of the technical challenges inherent in exascale system design and deployment, the subcommittee focused its assessment on organizational and management issues, considering technical issues only as they informed organizational or management priorities and structures. This report presents the observations and recommendations of the subcommittee.

Scientific computing vol II - eigenvalues and optimization

CERN Document Server

Trangenstein, John A

2017-01-01

This is the second of three volumes providing a comprehensive presentation of the fundamentals of scientific computing. This volume discusses more advanced topics than volume one, and is largely not a prerequisite for volume three. This book and its companions show how to determine the quality of computational results, and how to measure the relative efficiency of competing methods. Readers learn how to determine the maximum attainable accuracy of algorithms, and how to select the best method for computing problems. This book also discusses programming in several languages, including C++, Fortran and MATLAB. There are 49 examples, 110 exercises, 66 algorithms, 24 interactive JavaScript programs, 77 references to software programs and 1 case study. Topics are introduced with goals, literature references and links to public software. There are descriptions of the current algorithms in LAPACK, GSLIB and MATLAB. This book could be used for a second course in numerical methods, for either upper level undergraduate...

Scientific computing vol III - approximation and integration

CERN Document Server

Trangenstein, John A

2017-01-01

This is the third of three volumes providing a comprehensive presentation of the fundamentals of scientific computing. This volume discusses topics that depend more on calculus than linear algebra, in order to prepare the reader for solving differential equations. This book and its companions show how to determine the quality of computational results, and how to measure the relative efficiency of competing methods. Readers learn how to determine the maximum attainable accuracy of algorithms, and how to select the best method for computing problems. This book also discusses programming in several languages, including C++, Fortran and MATLAB. There are 90 examples, 200 exercises, 36 algorithms, 40 interactive JavaScript programs, 91 references to software programs and 1 case study. Topics are introduced with goals, literature references and links to public software. There are descriptions of the current algorithms in GSLIB and MATLAB. This book could be used for a second course in numerical methods, for either ...

Construction of Blaze at the University of Illinois at Chicago: A Shared, High-Performance, Visual Computer for Next-Generation Cyberinfrastructure-Accelerated Scientific, Engineering, Medical and Public Policy Research

Energy Technology Data Exchange (ETDEWEB)

Brown, Maxine D. [Acting Director, EVL; Leigh, Jason [PI

2014-02-17

The Blaze high-performance visual computing system serves the high-performance computing research and education needs of University of Illinois at Chicago (UIC). Blaze consists of a state-of-the-art, networked, computer cluster and ultra-high-resolution visualization system called CAVE2(TM) that is currently not available anywhere in Illinois. This system is connected via a high-speed 100-Gigabit network to the State of Illinois' I-WIRE optical network, as well as to national and international high speed networks, such as the Internet2, and the Global Lambda Integrated Facility. This enables Blaze to serve as an on-ramp to national cyberinfrastructure, such as the National Science Foundation’s Blue Waters petascale computer at the National Center for Supercomputing Applications at the University of Illinois at Chicago and the Department of Energy’s Argonne Leadership Computing Facility (ALCF) at Argonne National Laboratory. DOE award # DE-SC005067, leveraged with NSF award #CNS-0959053 for “Development of the Next-Generation CAVE Virtual Environment (NG-CAVE),” enabled us to create a first-of-its-kind high-performance visual computing system. The UIC Electronic Visualization Laboratory (EVL) worked with two U.S. companies to advance their commercial products and maintain U.S. leadership in the global information technology economy. New applications are being enabled with the CAVE2/Blaze visual computing system that is advancing scientific research and education in the U.S. and globally, and help train the next-generation workforce.

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.

UNEDF: Advanced Scientific Computing Collaboration Transforms the Low-Energy Nuclear Many-Body Problem

International Nuclear Information System (INIS)

Nam, H; Stoitsov, M; Nazarewicz, W; Hagen, G; Kortelainen, M; Pei, J C; Bulgac, A; Maris, P; Vary, J P; Roche, K J; Schunck, N; Thompson, I; Wild, S M

2012-01-01

The demands of cutting-edge science are driving the need for larger and faster computing resources. With the rapidly growing scale of computing systems and the prospect of technologically disruptive architectures to meet these needs, scientists face the challenge of effectively using complex computational resources to advance scientific discovery. Multi-disciplinary collaborating networks of researchers with diverse scientific backgrounds are needed to address these complex challenges. The UNEDF SciDAC collaboration of nuclear theorists, applied mathematicians, and computer scientists is developing a comprehensive description of nuclei and their reactions that delivers maximum predictive power with quantified uncertainties. This paper describes UNEDF and identifies attributes that classify it as a successful computational collaboration. We illustrate significant milestones accomplished by UNEDF through integrative solutions using the most reliable theoretical approaches, most advanced algorithms, and leadership-class computational resources.

Scientific Grand Challenges: Challenges in Climate Change Science and the Role of Computing at the Extreme Scale

Energy Technology Data Exchange (ETDEWEB)

Khaleel, Mohammad A.; Johnson, Gary M.; Washington, Warren M.

2009-07-02

The U.S. Department of Energy (DOE) Office of Biological and Environmental Research (BER) in partnership with the Office of Advanced Scientific Computing Research (ASCR) held a workshop on the challenges in climate change science and the role of computing at the extreme scale, November 6-7, 2008, in Bethesda, Maryland. At the workshop, participants identified the scientific challenges facing the field of climate science and outlined the research directions of highest priority that should be pursued to meet these challenges. Representatives from the national and international climate change research community as well as representatives from the high-performance computing community attended the workshop. This group represented a broad mix of expertise. Of the 99 participants, 6 were from international institutions. Before the workshop, each of the four panels prepared a white paper, which provided the starting place for the workshop discussions. These four panels of workshop attendees devoted to their efforts the following themes: Model Development and Integrated Assessment; Algorithms and Computational Environment; Decadal Predictability and Prediction; Data, Visualization, and Computing Productivity. The recommendations of the panels are summarized in the body of this report.

Scientific Grand Challenges: Crosscutting Technologies for Computing at the Exascale - February 2-4, 2010, Washington, D.C.

Energy Technology Data Exchange (ETDEWEB)

Khaleel, Mohammad A.

2011-02-06

The goal of the "Scientific Grand Challenges - Crosscutting Technologies for Computing at the Exascale" workshop in February 2010, jointly sponsored by the U.S. Department of Energy’s Office of Advanced Scientific Computing Research and the National Nuclear Security Administration, was to identify the elements of a research and development agenda that will address these challenges and create a comprehensive exascale computing environment. This exascale computing environment will enable the science applications identified in the eight previously held Scientific Grand Challenges Workshop Series.

Parallel computing works

Energy Technology Data Exchange (ETDEWEB)

1991-10-23

An account of the Caltech Concurrent Computation Program (C{sup 3}P), a five year project that focused on answering the question: Can parallel computers be used to do large-scale scientific computations '' As the title indicates, the question is answered in the affirmative, by implementing numerous scientific applications on real parallel computers and doing computations that produced new scientific results. In the process of doing so, C{sup 3}P helped design and build several new computers, designed and implemented basic system software, developed algorithms for frequently used mathematical computations on massively parallel machines, devised performance models and measured the performance of many computers, and created a high performance computing facility based exclusively on parallel computers. While the initial focus of C{sup 3}P was the hypercube architecture developed by C. Seitz, many of the methods developed and lessons learned have been applied successfully on other massively parallel architectures.

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.

High-integrity software, computation and the scientific method

International Nuclear Information System (INIS)

Hatton, L.

2012-01-01

Computation rightly occupies a central role in modern science. Datasets are enormous and the processing implications of some algorithms are equally staggering. With the continuing difficulties in quantifying the results of complex computations, it is of increasing importance to understand its role in the essentially Popperian scientific method. In this paper, some of the problems with computation, for example the long-term unquantifiable presence of undiscovered defect, problems with programming languages and process issues will be explored with numerous examples. One of the aims of the paper is to understand the implications of trying to produce high-integrity software and the limitations which still exist. Unfortunately Computer Science itself suffers from an inability to be suitably critical of its practices and has operated in a largely measurement-free vacuum since its earliest days. Within computer science itself, this has not been so damaging in that it simply leads to unconstrained creativity and a rapid turnover of new technologies. In the applied sciences however which have to depend on computational results, such unquantifiability significantly undermines trust. It is time this particular demon was put to rest. (author)

Automated and Assistive Tools for Accelerated Code migration of Scientific Computing on to Heterogeneous MultiCore Systems

Science.gov (United States)

2017-04-13

AFRL-AFOSR-UK-TR-2017-0029 Automated and Assistive Tools for Accelerated Code migration of Scientific Computing on to Heterogeneous MultiCore Systems ...2012, “ Automated and Assistive Tools for Accelerated Code migration of Scientific Computing on to Heterogeneous MultiCore Systems .” 2. The objective...2012 - 01/25/2015 4. TITLE AND SUBTITLE Automated and Assistive Tools for Accelerated Code migration of Scientific Computing on to Heterogeneous

I - Template Metaprogramming for Massively Parallel Scientific Computing - Expression Templates

CERN Multimedia

CERN. Geneva

2016-01-01

Large scale scientific computing raises questions on different levels ranging from the fomulation of the problems to the choice of the best algorithms and their implementation for a specific platform. There are similarities in these different topics that can be exploited by modern-style C++ template metaprogramming techniques to produce readable, maintainable and generic code. Traditional low-level code tend to be fast but platform-dependent, and it obfuscates the meaning of the algorithm. On the other hand, object-oriented approach is nice to read, but may come with an inherent performance penalty. These lectures aim to present he basics of the Expression Template (ET) idiom which allows us to keep the object-oriented approach without sacrificing performance. We will in particular show to to enhance ET to include SIMD vectorization. We will then introduce techniques for abstracting iteration, and introduce thread-level parallelism for use in heavy data-centric loads. We will show to to apply these methods i...

International Symposium on Scientific Computing, Computer Arithmetic and Validated Numerics

CERN Document Server

DEVELOPMENTS IN RELIABLE COMPUTING

1999-01-01

The SCAN conference, the International Symposium on Scientific Com­ puting, Computer Arithmetic and Validated Numerics, takes place bian­ nually under the joint auspices of GAMM (Gesellschaft fiir Angewandte Mathematik und Mechanik) and IMACS (International Association for Mathematics and Computers in Simulation). SCAN-98 attracted more than 100 participants from 21 countries all over the world. During the four days from September 22 to 25, nine highlighted, plenary lectures and over 70 contributed talks were given. These figures indicate a large participation, which was partly caused by the attraction of the organizing country, Hungary, but also the effec­ tive support system have contributed to the success. The conference was substantially supported by the Hungarian Research Fund OTKA, GAMM, the National Technology Development Board OMFB and by the J6zsef Attila University. Due to this funding, it was possible to subsidize the participation of over 20 scientists, mainly from Eastern European countries. I...

Computer simulations and the changing face of scientific experimentation

CERN Document Server

Duran, Juan M

2013-01-01

Computer simulations have become a central tool for scientific practice. Their use has replaced, in many cases, standard experimental procedures. This goes without mentioning cases where the target system is empirical but there are no techniques for direct manipulation of the system, such as astronomical observation. To these cases, computer simulations have proved to be of central importance. The question about their use and implementation, therefore, is not only a technical one but represents a challenge for the humanities as well. In this volume, scientists, historians, and philosophers joi

Accelerating the scientific exploration process with scientific workflows

International Nuclear Information System (INIS)

Altintas, Ilkay; Barney, Oscar; Cheng, Zhengang; Critchlow, Terence; Ludaescher, Bertram; Parker, Steve; Shoshani, Arie; Vouk, Mladen

2006-01-01

Although an increasing amount of middleware has emerged in the last few years to achieve remote data access, distributed job execution, and data management, orchestrating these technologies with minimal overhead still remains a difficult task for scientists. Scientific workflow systems improve this situation by creating interfaces to a variety of technologies and automating the execution and monitoring of the workflows. Workflow systems provide domain-independent customizable interfaces and tools that combine different tools and technologies along with efficient methods for using them. As simulations and experiments move into the petascale regime, the orchestration of long running data and compute intensive tasks is becoming a major requirement for the successful steering and completion of scientific investigations. A scientific workflow is the process of combining data and processes into a configurable, structured set of steps that implement semi-automated computational solutions of a scientific problem. Kepler is a cross-project collaboration, co-founded by the SciDAC Scientific Data Management (SDM) Center, whose purpose is to develop a domain-independent scientific workflow system. It provides a workflow environment in which scientists design and execute scientific workflows by specifying the desired sequence of computational actions and the appropriate data flow, including required data transformations, between these steps. Currently deployed workflows range from local analytical pipelines to distributed, high-performance and high-throughput applications, which can be both data- and compute-intensive. The scientific workflow approach offers a number of advantages over traditional scripting-based approaches, including ease of configuration, improved reusability and maintenance of workflows and components (called actors), automated provenance management, 'smart' re-running of different versions of workflow instances, on-the-fly updateable parameters, monitoring

Center for Center for Technology for Advanced Scientific Component Software (TASCS)

Energy Technology Data Exchange (ETDEWEB)

Kostadin, Damevski [Virginia State Univ., Petersburg, VA (United States)

2015-01-25

A resounding success of the Scientific Discovery through Advanced Computing (SciDAC) program is that high-performance computational science is now universally recognized as a critical aspect of scientific discovery [71], complementing both theoretical and experimental research. As scientific communities prepare to exploit unprecedented computing capabilities of emerging leadership-class machines for multi-model simulations at the extreme scale [72], it is more important than ever to address the technical and social challenges of geographically distributed teams that combine expertise in domain science, applied mathematics, and computer science to build robust and flexible codes that can incorporate changes over time. The Center for Technology for Advanced Scientific Component Software (TASCS)1 tackles these these issues by exploiting component-based software development to facilitate collaborative high-performance scientific computing.

PARA'04, State-of-the-art in scientific computing

DEFF Research Database (Denmark)

Madsen, Kaj; Wasniewski, Jerzy

This meeting in the series, the PARA'04 Workshop with the title ``State of the Art in Scientific Computing'', was held in Lyngby, Denmark, June 20-23, 2004. The PARA'04 Workshop was organized by Jack Dongarra from the University of Tennessee and Oak Ridge National Laboratory, and Kaj Madsen and J...

Undergraduate medical academic performance is improved by scientific training.

Science.gov (United States)

Zhang, Lili; Zhang, Wei; Wu, Chong; Liu, Zhongming; Cai, Yunfei; Cao, Xingguo; He, Yushan; Liu, Guoxiang; Miao, Hongming

2017-09-01

The effect of scientific training on course learning in undergraduates is still controversial. In this study, we investigated the academic performance of undergraduate students with and without scientific training. The results show that scientific training improves students' test scores in general medical courses, such as biochemistry and molecular biology, cell biology, physiology, and even English. We classified scientific training into four levels. We found that literature reading could significantly improve students' test scores in general courses. Students who received scientific training carried out experiments more effectively and published articles performed better than their untrained counterparts in biochemistry and molecular biology examinations. The questionnaire survey demonstrated that the trained students were more confident of their course learning, and displayed more interest, motivation and capability in course learning. In summary, undergraduate academic performance is improved by scientific training. Our findings shed light on the novel strategies in the management of undergraduate education in the medical school. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(5):379-384, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

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.

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.

The Observation of Bahasa Indonesia Official Computer Terms Implementation in Scientific Publication

Science.gov (United States)

Gunawan, D.; Amalia, A.; Lydia, M. S.; Muthaqin, M. I.

2018-03-01

The government of the Republic of Indonesia had issued a regulation to substitute computer terms in foreign language that have been used earlier into official computer terms in Bahasa Indonesia. This regulation was stipulated in Presidential Decree No. 2 of 2001 concerning the introduction of official computer terms in Bahasa Indonesia (known as Senarai Padanan Istilah/SPI). After sixteen years, people of Indonesia, particularly for academics, should have implemented the official computer terms in their official publications. This observation is conducted to discover the implementation of official computer terms usage in scientific publications which are written in Bahasa Indonesia. The data source used in this observation are the publications by the academics, particularly in computer science field. The method used in the observation is divided into four stages. The first stage is metadata harvesting by using Open Archive Initiative - Protocol for Metadata Harvesting (OAI-PMH). Second, converting the harvested document (in pdf format) to plain text. The third stage is text-preprocessing as the preparation of string matching. Then the final stage is searching the official computer terms based on 629 SPI terms by using Boyer-Moore algorithm. We observed that there are 240,781 foreign computer terms in 1,156 scientific publications from six universities. This result shows that the foreign computer terms are still widely used by the academics.

From Mars to Minerva: The origins of scientific computing in the AEC labs

Energy Technology Data Exchange (ETDEWEB)

Seidel, R.W. [ERA Land Grant Professor of the History of Technology]|[Charles Babbage Institute, University of Minnesota, Minneapolis, Minnesota (United States)

1996-10-01

Although the AEC laboratories are renowned for the development of nuclear weapons, their largess in promoting scientific computing also had a profound effect on scientific and technological development in the second half of the 20th century. {copyright} {ital 1996 American Institute of Physics.}

OPENING REMARKS: Scientific Discovery through Advanced Computing

Science.gov (United States)

Strayer, Michael

2006-01-01

Good morning. Welcome to SciDAC 2006 and Denver. I share greetings from the new Undersecretary for Energy, Ray Orbach. Five years ago SciDAC was launched as an experiment in computational science. The goal was to form partnerships among science applications, computer scientists, and applied mathematicians to take advantage of the potential of emerging terascale computers. This experiment has been a resounding success. SciDAC has emerged as a powerful concept for addressing some of the biggest challenges facing our world. As significant as these successes were, I believe there is also significance in the teams that achieved them. In addition to their scientific aims these teams have advanced the overall field of computational science and set the stage for even larger accomplishments as we look ahead to SciDAC-2. I am sure that many of you are expecting to hear about the results of our current solicitation for SciDAC-2. I’m afraid we are not quite ready to make that announcement. Decisions are still being made and we will announce the results later this summer. Nearly 250 unique proposals were received and evaluated, involving literally thousands of researchers, postdocs, and students. These collectively requested more than five times our expected budget. This response is a testament to the success of SciDAC in the community. In SciDAC-2 our budget has been increased to about 70 million for FY 2007 and our partnerships have expanded to include the Environment and National Security missions of the Department. The National Science Foundation has also joined as a partner. These new partnerships are expected to expand the application space of SciDAC, and broaden the impact and visibility of the program. We have, with our recent solicitation, expanded to turbulence, computational biology, and groundwater reactive modeling and simulation. We are currently talking with the Department’s applied energy programs about risk assessment, optimization of complex systems - such

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.

Performance Measurements in a High Throughput Computing Environment

CERN Document Server

AUTHOR|(CDS)2145966; Gribaudo, Marco

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

Undergraduate Medical Academic Performance is Improved by Scientific Training

Science.gov (United States)

Zhang, Lili; Zhang, Wei; Wu, Chong; Liu, Zhongming; Cai, Yunfei; Cao, Xingguo; He, Yushan; Liu, Guoxiang; Miao, Hongming

2017-01-01

The effect of scientific training on course learning in undergraduates is still controversial. In this study, we investigated the academic performance of undergraduate students with and without scientific training. The results show that scientific training improves students' test scores in general medical courses, such as biochemistry and…

Topics in numerical partial differential equations and scientific computing

CERN Document Server

2016-01-01

Numerical partial differential equations (PDEs) are an important part of numerical simulation, the third component of the modern methodology for science and engineering, besides the traditional theory and experiment. This volume contains papers that originated with the collaborative research of the teams that participated in the IMA Workshop for Women in Applied Mathematics: Numerical Partial Differential Equations and Scientific Computing in August 2014.

Trend Analysis of the Brazilian Scientific Production in Computer Science

Directory of Open Access Journals (Sweden)

TRUCOLO, C. C.

2014-12-01

Full Text Available The growth of scientific information volume and diversity brings new challenges in order to understand the reasons, the process and the real essence that propel this growth. This information can be used as the basis for the development of strategies and public politics to improve the education and innovation services. Trend analysis is one of the steps in this way. In this work, trend analysis of Brazilian scientific production of graduate programs in the computer science area is made to identify the main subjects being studied by these programs in general and individual ways.

Scientific Computing Strategic Plan for the Idaho National Laboratory

International Nuclear Information System (INIS)

Whiting, Eric Todd

2015-01-01

Scientific computing is a critical foundation of modern science. Without innovations in the field of computational science, the essential missions of the Department of Energy (DOE) would go unrealized. Taking a leadership role in such innovations is Idaho National Laboratory's (INL's) challenge and charge, and is central to INL's ongoing success. Computing is an essential part of INL's future. DOE science and technology missions rely firmly on computing capabilities in various forms. Modeling and simulation, fueled by innovations in computational science and validated through experiment, are a critical foundation of science and engineering. Big data analytics from an increasing number of widely varied sources is opening new windows of insight and discovery. Computing is a critical tool in education, science, engineering, and experiments. Advanced computing capabilities in the form of people, tools, computers, and facilities, will position INL competitively to deliver results and solutions on important national science and engineering challenges. A computing strategy must include much more than simply computers. The foundational enabling component of computing at many DOE national laboratories is the combination of a showcase like data center facility coupled with a very capable supercomputer. In addition, network connectivity, disk storage systems, and visualization hardware are critical and generally tightly coupled to the computer system and co located in the same facility. The existence of these resources in a single data center facility opens the doors to many opportunities that would not otherwise be possible.

Scientific and Computational Challenges of the Fusion Simulation Program (FSP)

International Nuclear Information System (INIS)

Tang, William M.

2011-01-01

This paper highlights the scientific and computational challenges facing the Fusion Simulation Program (FSP) a major national initiative in the United States with the primary objective being to enable scientific discovery of important new plasma phenomena with associated understanding that emerges only upon integration. This requires developing a predictive integrated simulation capability for magnetically-confined fusion plasmas that are properly validated against experiments in regimes relevant for producing practical fusion energy. It is expected to provide a suite of advanced modeling tools for reliably predicting fusion device behavior with comprehensive and targeted science-based simulations of nonlinearly-coupled phenomena in the core plasma, edge plasma, and wall region on time and space scales required for fusion energy production. As such, it will strive to embody the most current theoretical and experimental understanding of magnetic fusion plasmas and to provide a living framework for the simulation of such plasmas as the associated physics understanding continues to advance over the next several decades. Substantive progress on answering the outstanding scientific questions in the field will drive the FSP toward its ultimate goal of developing the ability to predict the behavior of plasma discharges in toroidal magnetic fusion devices with high physics fidelity on all relevant time and space scales. From a computational perspective, this will demand computing resources in the petascale range and beyond together with the associated multi-core algorithmic formulation needed to address burning plasma issues relevant to ITER - a multibillion dollar collaborative experiment involving seven international partners representing over half the world's population. Even more powerful exascale platforms will be needed to meet the future challenges of designing a demonstration fusion reactor (DEMO). Analogous to other major applied physics modeling projects (e

Scientific and computational challenges of the fusion simulation program (FSP)

International Nuclear Information System (INIS)

Tang, William M.

2011-01-01

This paper highlights the scientific and computational challenges facing the Fusion Simulation Program (FSP) - a major national initiative in the United States with the primary objective being to enable scientific discovery of important new plasma phenomena with associated understanding that emerges only upon integration. This requires developing a predictive integrated simulation capability for magnetically-confined fusion plasmas that are properly validated against experiments in regimes relevant for producing practical fusion energy. It is expected to provide a suite of advanced modeling tools for reliably predicting fusion device behavior with comprehensive and targeted science-based simulations of nonlinearly-coupled phenomena in the core plasma, edge plasma, and wall region on time and space scales required for fusion energy production. As such, it will strive to embody the most current theoretical and experimental understanding of magnetic fusion plasmas and to provide a living framework for the simulation of such plasmas as the associated physics understanding continues to advance over the next several decades. Substantive progress on answering the outstanding scientific questions in the field will drive the FSP toward its ultimate goal of developing the ability to predict the behavior of plasma discharges in toroidal magnetic fusion devices with high physics fidelity on all relevant time and space scales. From a computational perspective, this will demand computing resources in the petascale range and beyond together with the associated multi-core algorithmic formulation needed to address burning plasma issues relevant to ITER - a multibillion dollar collaborative experiment involving seven international partners representing over half the world's population. Even more powerful exascale platforms will be needed to meet the future challenges of designing a demonstration fusion reactor (DEMO). Analogous to other major applied physics modeling projects (e

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

Science.gov (United States)

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

2012-01-01

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

Human Computer Music Performance

OpenAIRE

Dannenberg, Roger B.

2012-01-01

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

Designing Scientific Software for Heterogeneous Computing

DEFF Research Database (Denmark)

Glimberg, Stefan Lemvig

, algorithms and data structures must be designed to utilize the underlying parallel architecture. The architectural changes in hardware design within the last decade, from single to multi and many-core architectures, require software developers to identify and properly implement methods that both exploit...... makes parallel software design applicable, but also a challenge for scientific software developers at all levels. We have developed a generic C++ library for fast prototyping of large-scale PDEs solvers based on flexible-order finite difference approximations on structured regular grids. The library...... is designed with a high abstraction interface to improve developer productivity. The library is based on modern template-based design concepts as described in Glimberg, Engsig-Karup, Nielsen & Dammann (2013). The library utilizes heterogeneous CPU/GPU environments in order to maximize computational throughput...

A performance evaluation of the IBM 370/XT personal computer

Science.gov (United States)

Dominick, Wayne D. (Editor); Triantafyllopoulos, Spiros

1984-01-01

An evaluation of the IBM 370/XT personal computer is given. This evaluation focuses primarily on the use of the 370/XT for scientific and technical applications and applications development. A measurement of the capabilities of the 370/XT was performed by means of test programs which are presented. Also included is a review of facilities provided by the operating system (VM/PC), along with comments on the IBM 370/XT hardware configuration.

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.

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

Science.gov (United States)

Moon, Hongsik

What is the impact of multicore and associated advanced technologies on computational software for science? Most researchers and students have multicore laptops or desktops for their research and they need computing power to run computational software packages. Computing power was initially derived from Central Processing Unit (CPU) clock speed. That changed when increases in clock speed became constrained by power requirements. Chip manufacturers turned to multicore CPU architectures and associated technological advancements to create the CPUs for the future. Most software applications benefited by the increased computing power the same way that increases in clock speed helped applications run faster. However, for Computational ElectroMagnetics (CEM) software developers, this change was not an obvious benefit - it appeared to be a detriment. Developers were challenged to find a way to correctly utilize the advancements in hardware so that their codes could benefit. The solution was parallelization and this dissertation details the investigation to address these challenges. Prior to multicore CPUs, advanced computer technologies were compared with the performance using benchmark software and the metric was FLoting-point Operations Per Seconds (FLOPS) which indicates system performance for scientific applications that make heavy use of floating-point calculations. Is FLOPS an effective metric for parallelized CEM simulation tools on new multicore system? Parallel CEM software needs to be benchmarked not only by FLOPS but also by the performance of other parameters related to type and utilization of the hardware, such as CPU, Random Access Memory (RAM), hard disk, network, etc. The codes need to be optimized for more than just FLOPs and new parameters must be included in benchmarking. In this dissertation, the parallel CEM software named High Order Basis Based Integral Equation Solver (HOBBIES) is introduced. This code was developed to address the needs of the

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...

Computer-Supported Aids to Making Sense of Scientific Articles: Cognitive, Motivational, and Attitudinal Effects

Science.gov (United States)

Gegner, Julie A.; Mackay, Donald H. J.; Mayer, Richard E.

2009-01-01

High school students can access original scientific research articles on the Internet, but may have trouble understanding them. To address this problem of online literacy, the authors developed a computer-based prototype for guiding students' comprehension of scientific articles. High school students were asked to read an original scientific…

Certainty in Stockpile Computing: Recommending a Verification and Validation Program for Scientific Software

Energy Technology Data Exchange (ETDEWEB)

Lee, J.R.

1998-11-01

As computing assumes a more central role in managing the nuclear stockpile, the consequences of an erroneous computer simulation could be severe. Computational failures are common in other endeavors and have caused project failures, significant economic loss, and loss of life. This report examines the causes of software failure and proposes steps to mitigate them. A formal verification and validation program for scientific software is recommended and described.

[Text mining, a method for computer-assisted analysis of scientific texts, demonstrated by an analysis of author networks].

Science.gov (United States)

Hahn, P; Dullweber, F; Unglaub, F; Spies, C K

2014-06-01

Searching for relevant publications is becoming more difficult with the increasing number of scientific articles. Text mining as a specific form of computer-based data analysis may be helpful in this context. Highlighting relations between authors and finding relevant publications concerning a specific subject using text analysis programs are illustrated graphically by 2 performed examples. © Georg Thieme Verlag KG Stuttgart · New York.

Frontiers of massively parallel scientific computation

International Nuclear Information System (INIS)

Fischer, J.R.

1987-07-01

Practical applications using massively parallel computer hardware first appeared during the 1980s. Their development was motivated by the need for computing power orders of magnitude beyond that available today for tasks such as numerical simulation of complex physical and biological processes, generation of interactive visual displays, satellite image analysis, and knowledge based systems. Representative of the first generation of this new class of computers is the Massively Parallel Processor (MPP). A team of scientists was provided the opportunity to test and implement their algorithms on the MPP. The first results are presented. The research spans a broad variety of applications including Earth sciences, physics, signal and image processing, computer science, and graphics. The performance of the MPP was very good. Results obtained using the Connection Machine and the Distributed Array Processor (DAP) are presented

Computer-assisted estimating for the Los Alamos Scientific Laboratory

International Nuclear Information System (INIS)

Spooner, J.E.

1976-02-01

An analysis is made of the cost estimating system currently in use at the Los Alamos Scientific Laboratory (LASL) and the benefits of computer assistance are evaluated. A computer-assisted estimating system (CAE) is proposed for LASL. CAE can decrease turnaround and provide more flexible response to management requests for cost information and analyses. It can enhance value optimization at the design stage, improve cost control and change-order justification, and widen the use of cost information in the design process. CAE costs are not well defined at this time although they appear to break even with present operations. It is recommended that a CAE system description be submitted for contractor consideration and bid while LASL system development continues concurrently

Computer-Related Task Performance

DEFF Research Database (Denmark)

Longstreet, Phil; Xiao, Xiao; Sarker, Saonee

2016-01-01

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

Efficient Machine Learning Approach for Optimizing Scientific Computing Applications on Emerging HPC Architectures

Energy Technology Data Exchange (ETDEWEB)

Arumugam, Kamesh [Old Dominion Univ., Norfolk, VA (United States)

2017-05-01

Efficient parallel implementations of scientific applications on multi-core CPUs with accelerators such as GPUs and Xeon Phis is challenging. This requires - exploiting the data parallel architecture of the accelerator along with the vector pipelines of modern x86 CPU architectures, load balancing, and efficient memory transfer between different devices. It is relatively easy to meet these requirements for highly structured scientific applications. In contrast, a number of scientific and engineering applications are unstructured. Getting performance on accelerators for these applications is extremely challenging because many of these applications employ irregular algorithms which exhibit data-dependent control-ow and irregular memory accesses. Furthermore, these applications are often iterative with dependency between steps, and thus making it hard to parallelize across steps. As a result, parallelism in these applications is often limited to a single step. Numerical simulation of charged particles beam dynamics is one such application where the distribution of work and memory access pattern at each time step is irregular. Applications with these properties tend to present significant branch and memory divergence, load imbalance between different processor cores, and poor compute and memory utilization. Prior research on parallelizing such irregular applications have been focused around optimizing the irregular, data-dependent memory accesses and control-ow during a single step of the application independent of the other steps, with the assumption that these patterns are completely unpredictable. We observed that the structure of computation leading to control-ow divergence and irregular memory accesses in one step is similar to that in the next step. It is possible to predict this structure in the current step by observing the computation structure of previous steps. In this dissertation, we present novel machine learning based optimization techniques to address

Strategic Plan for a Scientific Cloud Computing infrastructure for Europe

CERN Document Server

Lengert, Maryline

2011-01-01

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

II - Template Metaprogramming for Massively Parallel Scientific Computing - Vectorization with Expression Templates

CERN Multimedia

CERN. Geneva

2016-01-01

Large scale scientific computing raises questions on different levels ranging from the fomulation of the problems to the choice of the best algorithms and their implementation for a specific platform. There are similarities in these different topics that can be exploited by modern-style C++ template metaprogramming techniques to produce readable, maintainable and generic code. Traditional low-level code tend to be fast but platform-dependent, and it obfuscates the meaning of the algorithm. On the other hand, object-oriented approach is nice to read, but may come with an inherent performance penalty. These lectures aim to present he basics of the Expression Template (ET) idiom which allows us to keep the object-oriented approach without sacrificing performance. We will in particular show to to enhance ET to include SIMD vectorization. We will then introduce techniques for abstracting iteration, and introduce thread-level parallelism for use in heavy data-centric loads. We will show to to apply these methods i...

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

Mastering scientific computing with R

CERN Document Server

Gerrard, Paul

2015-01-01

If you want to learn how to quantitatively answer scientific questions for practical purposes using the powerful R language and the open source R tool ecosystem, this book is ideal for you. It is ideally suited for scientists who understand scientific concepts, know a little R, and want to be able to start applying R to be able to answer empirical scientific questions. Some R exposure is helpful, but not compulsory.

Optimal Design of Fixed-Point and Floating-Point Arithmetic Units for Scientific Applications

OpenAIRE

Pongyupinpanich, Surapong

2012-01-01

The challenge in designing a floating-point arithmetic co-processor/processor for scientific and engineering applications is to improve the performance, efficiency, and computational accuracy of the arithmetic unit. The arithmetic unit should efficiently support several mathematical functions corresponding to scientific and engineering computation demands. Moreover, the computations should be performed as fast as possible with a high degree of accuracy. Thus, this thesis proposes algorithm, d...

Center for Technology for Advanced Scientific Component Software (TASCS) Consolidated Progress Report July 2006 - March 2009

Energy Technology Data Exchange (ETDEWEB)

Bernholdt, D E; McInnes, L C; Govindaraju, M; Bramley, R; Epperly, T; Kohl, J A; Nieplocha, J; Armstrong, R; Shasharina, S; Sussman, A L; Sottile, M; Damevski, K

2009-04-14

A resounding success of the Scientific Discovery through Advanced Computing (SciDAC) program is that high-performance computational science is now universally recognized as a critical aspect of scientific discovery [71], complementing both theoretical and experimental research. As scientific communities prepare to exploit unprecedented computing capabilities of emerging leadership-class machines for multi-model simulations at the extreme scale [72], it is more important than ever to address the technical and social challenges of geographically distributed teams that combine expertise in domain science, applied mathematics, and computer science to build robust and flexible codes that can incorporate changes over time. The Center for Technology for Advanced Scientific Component Software (TASCS) tackles these issues by exploiting component-based software development to facilitate collaborative high-performance scientific computing.

Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows

International Nuclear Information System (INIS)

Mhashilkar, Parag; Tiradani, Anthony; Holzman, Burt; Larson, Krista; Sfiligoi, Igor; Rynge, Mats

2014-01-01

Scientific communities have been in the forefront of adopting new technologies and methodologies in the computing. Scientific computing has influenced how science is done today, achieving breakthroughs that were impossible to achieve several decades ago. For the past decade several such communities in the Open Science Grid (OSG) and the European Grid Infrastructure (EGI) have been using GlideinWMS to run complex application workflows to effectively share computational resources over the grid. GlideinWMS is a pilot-based workload management system (WMS) that creates on demand, a dynamically sized overlay HTCondor batch system on grid resources. At present, the computational resources shared over the grid are just adequate to sustain the computing needs. We envision that the complexity of the science driven by 'Big Data' will further push the need for computational resources. To fulfill their increasing demands and/or to run specialized workflows, some of the big communities like CMS are investigating the use of cloud computing as Infrastructure-As-A-Service (IAAS) with GlideinWMS as a potential alternative to fill the void. Similarly, communities with no previous access to computing resources can use GlideinWMS to setup up a batch system on the cloud infrastructure. To enable this, the architecture of GlideinWMS has been extended to enable support for interfacing GlideinWMS with different Scientific and commercial cloud providers like HLT, FutureGrid, FermiCloud and Amazon EC2. In this paper, we describe a solution for cloud bursting with GlideinWMS. The paper describes the approach, architectural changes and lessons learned while enabling support for cloud infrastructures in GlideinWMS.

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.)

10th International Conference on Scientific Computing in Electrical Engineering

CERN Document Server

Clemens, Markus; Günther, Michael; Maten, E

2016-01-01

This book is a collection of selected papers presented at the 10th International Conference on Scientific Computing in Electrical Engineering (SCEE), held in Wuppertal, Germany in 2014. The book is divided into five parts, reflecting the main directions of SCEE 2014: 1. Device Modeling, Electric Circuits and Simulation, 2. Computational Electromagnetics, 3. Coupled Problems, 4. Model Order Reduction, and 5. Uncertainty Quantification. Each part starts with a general introduction followed by the actual papers. The aim of the SCEE 2014 conference was to bring together scientists from academia and industry, mathematicians, electrical engineers, computer scientists, and physicists, with the goal of fostering intensive discussions on industrially relevant mathematical problems, with an emphasis on the modeling and numerical simulation of electronic circuits and devices, electromagnetic fields, and coupled problems. The methodological focus was on model order reduction and uncertainty quantification.

Using Just-in-Time Information to Support Scientific Discovery Learning in a Computer-Based Simulation

Science.gov (United States)

Hulshof, Casper D.; de Jong, Ton

2006-01-01

Students encounter many obstacles during scientific discovery learning with computer-based simulations. It is hypothesized that an effective type of support, that does not interfere with the scientific discovery learning process, should be delivered on a "just-in-time" base. This study explores the effect of facilitating access to…

Scalability of Parallel Scientific Applications on the Cloud

Directory of Open Access Journals (Sweden)

Satish Narayana Srirama

2011-01-01

Full Text Available Cloud computing, with its promise of virtually infinite resources, seems to suit well in solving resource greedy scientific computing problems. To study the effects of moving parallel scientific applications onto the cloud, we deployed several benchmark applications like matrix–vector operations and NAS parallel benchmarks, and DOUG (Domain decomposition On Unstructured Grids on the cloud. DOUG is an open source software package for parallel iterative solution of very large sparse systems of linear equations. The detailed analysis of DOUG on the cloud showed that parallel applications benefit a lot and scale reasonable on the cloud. We could also observe the limitations of the cloud and its comparison with cluster in terms of performance. However, for efficiently running the scientific applications on the cloud infrastructure, the applications must be reduced to frameworks that can successfully exploit the cloud resources, like the MapReduce framework. Several iterative and embarrassingly parallel algorithms are reduced to the MapReduce model and their performance is measured and analyzed. The analysis showed that Hadoop MapReduce has significant problems with iterative methods, while it suits well for embarrassingly parallel algorithms. Scientific computing often uses iterative methods to solve large problems. Thus, for scientific computing on the cloud, this paper raises the necessity for better frameworks or optimizations for MapReduce.

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...

[Performance analysis of scientific researchers in biomedicine].

Science.gov (United States)

Gamba, Gerardo

2013-01-01

There is no data about the performance of scientific researchers in biomedicine in our environment that can be use by individual subjects to compare their execution with their pairs. Using the Scopus browser the following data from 115 scientific researchers in biomedicine were obtained: actual institution, number of articles published, place on each article within the author list as first, last or unique author, total number of citations, percentage of citations due to the most cited paper, and h-index. Results were analyzed with descriptive statistics and simple lineal regressions. Most of scientific researches in the sample are from the National Institutes of the Health Ministry or some of the research institutes or faculties at the Universidad Nacional Autónoma de México. Total number of publications was biomedicine in Mexico City, which can be used to compare the productivity of individual subjects with their pairs.

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

New Chicago-Indiana computer network will handle dataflow from world's largest scientific experiment

CERN Multimedia

2006-01-01

"Massive quantities of data will soon begin flowing from the largest scientific instrument ever built into an international netword of computer centers, including one operated jointly by the University of Chicago and Indiana University." (1,5 page)

Scientific Data Services -- A High-Performance I/O System with Array Semantics

Energy Technology Data Exchange (ETDEWEB)

Wu, Kesheng; Byna, Surendra; Rotem, Doron; Shoshani, Arie

2011-09-21

As high-performance computing approaches exascale, the existing I/O system design is having trouble keeping pace in both performance and scalability. We propose to address this challenge by adopting database principles and techniques in parallel I/O systems. First, we propose to adopt an array data model because many scientific applications represent their data in arrays. This strategy follows a cardinal principle from database research, which separates the logical view from the physical layout of data. This high-level data model gives the underlying implementation more freedom to optimize the physical layout and to choose the most effective way of accessing the data. For example, knowing that a set of write operations is working on a single multi-dimensional array makes it possible to keep the subarrays in a log structure during the write operations and reassemble them later into another physical layout as resources permit. While maintaining the high-level view, the storage system could compress the user data to reduce the physical storage requirement, collocate data records that are frequently used together, or replicate data to increase availability and fault-tolerance. Additionally, the system could generate secondary data structures such as database indexes and summary statistics. We expect the proposed Scientific Data Services approach to create a “live” storage system that dynamically adjusts to user demands and evolves with the massively parallel storage hardware.

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.

Computational Simulations and the Scientific Method

Science.gov (United States)

Kleb, Bil; Wood, Bill

2005-01-01

As scientific simulation software becomes more complicated, the scientific-software implementor's need for component tests from new model developers becomes more crucial. The community's ability to follow the basic premise of the Scientific Method requires independently repeatable experiments, and model innovators are in the best position to create these test fixtures. Scientific software developers also need to quickly judge the value of the new model, i.e., its cost-to-benefit ratio in terms of gains provided by the new model and implementation risks such as cost, time, and quality. This paper asks two questions. The first is whether other scientific software developers would find published component tests useful, and the second is whether model innovators think publishing test fixtures is a feasible approach.

[Earth Science Technology Office's Computational Technologies Project

Science.gov (United States)

Fischer, James (Technical Monitor); Merkey, Phillip

2005-01-01

This grant supported the effort to characterize the problem domain of the Earth Science Technology Office's Computational Technologies Project, to engage the Beowulf Cluster Computing Community as well as the High Performance Computing Research Community so that we can predict the applicability of said technologies to the scientific community represented by the CT project and formulate long term strategies to provide the computational resources necessary to attain the anticipated scientific objectives of the CT project. Specifically, the goal of the evaluation effort is to use the information gathered over the course of the Round-3 investigations to quantify the trends in scientific expectations, the algorithmic requirements and capabilities of high-performance computers to satisfy this anticipated need.

Improving Performances in the Public Sector: The Scientific ...

African Journals Online (AJOL)

Improving Performances in the Public Sector: The Scientific Management Theory ... adopts the principles for enhanced productivity, efficiency and the attainment of ... of the public sector, as observed and reported by several scholars over time.

Visual computing scientific visualization and imaging systems

CERN Document Server

2014-01-01

This volume aims to stimulate discussions on research involving the use of data and digital images as an understanding approach for analysis and visualization of phenomena and experiments. The emphasis is put not only on graphically representing data as a way of increasing its visual analysis, but also on the imaging systems which contribute greatly to the comprehension of real cases. Scientific Visualization and Imaging Systems encompass multidisciplinary areas, with applications in many knowledge fields such as Engineering, Medicine, Material Science, Physics, Geology, Geographic Information Systems, among others. This book is a selection of 13 revised and extended research papers presented in the International Conference on Advanced Computational Engineering and Experimenting -ACE-X conferences 2010 (Paris), 2011 (Algarve), 2012 (Istanbul) and 2013 (Madrid). The examples were particularly chosen from materials research, medical applications, general concepts applied in simulations and image analysis and ot...

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.

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.

An integrated IaaS and PaaS architecture for scientific computing

OpenAIRE

Donvito, Giacinto; Blanquer, Ignacio

2015-01-01

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

Scientific and computational challenges of the fusion simulation project (FSP)

International Nuclear Information System (INIS)

Tang, W M

2008-01-01

This paper highlights the scientific and computational challenges facing the Fusion Simulation Project (FSP). The primary objective is to develop advanced software designed to use leadership-class computers for carrying out multiscale physics simulations to provide information vital to delivering a realistic integrated fusion simulation model with unprecedented physics fidelity. This multiphysics capability will be unprecedented in that in the current FES applications domain, the largest-scale codes are used to carry out first-principles simulations of mostly individual phenomena in realistic 3D geometry while the integrated models are much smaller-scale, lower-dimensionality codes with significant empirical elements used for modeling and designing experiments. The FSP is expected to be the most up-to-date embodiment of the theoretical and experimental understanding of magnetically confined thermonuclear plasmas and to provide a living framework for the simulation of such plasmas as the associated physics understanding continues to advance over the next several decades. Substantive progress on answering the outstanding scientific questions in the field will drive the FSP toward its ultimate goal of developing a reliable ability to predict the behavior of plasma discharges in toroidal magnetic fusion devices on all relevant time and space scales. From a computational perspective, the fusion energy science application goal to produce high-fidelity, whole-device modeling capabilities will demand computing resources in the petascale range and beyond, together with the associated multicore algorithmic formulation needed to address burning plasma issues relevant to ITER - a multibillion dollar collaborative device involving seven international partners representing over half the world's population. Even more powerful exascale platforms will be needed to meet the future challenges of designing a demonstration fusion reactor (DEMO). Analogous to other major applied physics

Power-Efficient Computing: Experiences from the COSA Project

Directory of Open Access Journals (Sweden)

Daniele Cesini

2017-01-01

Full Text Available Energy consumption is today one of the most relevant issues in operating HPC systems for scientific applications. The use of unconventional computing systems is therefore of great interest for several scientific communities looking for a better tradeoff between time-to-solution and energy-to-solution. In this context, the performance assessment of processors with a high ratio of performance per watt is necessary to understand how to realize energy-efficient computing systems for scientific applications, using this class of processors. Computing On SOC Architecture (COSA is a three-year project (2015–2017 funded by the Scientific Commission V of the Italian Institute for Nuclear Physics (INFN, which aims to investigate the performance and the total cost of ownership offered by computing systems based on commodity low-power Systems on Chip (SoCs and high energy-efficient systems based on GP-GPUs. In this work, we present the results of the project analyzing the performance of several scientific applications on several GPU- and SoC-based systems. We also describe the methodology we have used to measure energy performance and the tools we have implemented to monitor the power drained by applications while running.

Second Annual AEC Scientific Computer Information Exhange Meeting. Proceedings of the technical program theme: computer graphics

Energy Technology Data Exchange (ETDEWEB)

Peskin,A.M.; Shimamoto, Y.

1974-01-01

The topic of computer graphics serves well to illustrate that AEC affiliated scientific computing installations are well represented in the forefront of computing science activities. The participant response to the technical program was overwhelming--both in number of contributions and quality of the work described. Session I, entitled Advanced Systems, contains presentations describing systems that contain features not generally found in graphics facilities. These features can be roughly classified as extensions of standard two-dimensional monochromatic imaging to higher dimensions including color and time as well as multidimensional metrics. Session II presents seven diverse applications ranging from high energy physics to medicine. Session III describes a number of important developments in establishing facilities, techniques and enhancements in the computer graphics area. Although an attempt was made to schedule as many of these worthwhile presentations as possible, it appeared impossible to do so given the scheduling constraints of the meeting. A number of prospective presenters 'came to the rescue' by graciously withdrawing from the sessions. Some of their abstracts have been included in the Proceedings.

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.

NCI's Transdisciplinary High Performance Scientific Data Platform

Science.gov (United States)

Evans, Ben; Antony, Joseph; Bastrakova, Irina; Car, Nicholas; Cox, Simon; Druken, Kelsey; Evans, Bradley; Fraser, Ryan; Ip, Alex; Kemp, Carina; King, Edward; Minchin, Stuart; Larraondo, Pablo; Pugh, Tim; Richards, Clare; Santana, Fabiana; Smillie, Jon; Trenham, Claire; Wang, Jingbo; Wyborn, Lesley

2016-04-01

The Australian National Computational Infrastructure (NCI) manages Earth Systems data collections sourced from several domains and organisations onto a single High Performance Data (HPD) Node to further Australia's national priority research and innovation agenda. The NCI HPD Node has rapidly established its value, currently managing over 10 PBytes of datasets from collections that span a wide range of disciplines including climate, weather, environment, geoscience, geophysics, water resources and social sciences. Importantly, in order to facilitate broad user uptake, maximise reuse and enable transdisciplinary access through software and standardised interfaces, the datasets, associated information systems and processes have been incorporated into the design and operation of a unified platform that NCI has called, the National Environmental Research Data Interoperability Platform (NERDIP). The key goal of the NERDIP is to regularise data access so that it is easily discoverable, interoperable for different domains and enabled for high performance methods. It adopts and implements international standards and data conventions, and promotes scientific integrity within a high performance computing and data analysis environment. NCI has established a rich and flexible computing environment to access to this data, through the NCI supercomputer; a private cloud that supports both domain focused virtual laboratories and in-common interactive analysis interfaces; as well as remotely through scalable data services. Data collections of this importance must be managed with careful consideration of both their current use and the needs of the end-communities, as well as its future potential use, such as transitioning to more advanced software and improved methods. It is therefore critical that the data platform is both well-managed and trusted for stable production use (including transparency and reproducibility), agile enough to incorporate new technological advances and

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

Accelerating Scientific Applications using High Performance Dense and Sparse Linear Algebra Kernels on GPUs

KAUST Repository

Abdelfattah, Ahmad

2015-01-15

High performance computing (HPC) platforms are evolving to more heterogeneous configurations to support the workloads of various applications. The current hardware landscape is composed of traditional multicore CPUs equipped with hardware accelerators that can handle high levels of parallelism. Graphical Processing Units (GPUs) are popular high performance hardware accelerators in modern supercomputers. GPU programming has a different model than that for CPUs, which means that many numerical kernels have to be redesigned and optimized specifically for this architecture. GPUs usually outperform multicore CPUs in some compute intensive and massively parallel applications that have regular processing patterns. However, most scientific applications rely on crucial memory-bound kernels and may witness bottlenecks due to the overhead of the memory bus latency. They can still take advantage of the GPU compute power capabilities, provided that an efficient architecture-aware design is achieved. This dissertation presents a uniform design strategy for optimizing critical memory-bound kernels on GPUs. Based on hierarchical register blocking, double buffering and latency hiding techniques, this strategy leverages the performance of a wide range of standard numerical kernels found in dense and sparse linear algebra libraries. The work presented here focuses on matrix-vector multiplication kernels (MVM) as repre- sentative and most important memory-bound operations in this context. Each kernel inherits the benefits of the proposed strategies. By exposing a proper set of tuning parameters, the strategy is flexible enough to suit different types of matrices, ranging from large dense matrices, to sparse matrices with dense block structures, while high performance is maintained. Furthermore, the tuning parameters are used to maintain the relative performance across different GPU architectures. Multi-GPU acceleration is proposed to scale the performance on several devices. The

The graphics future in scientific applications-trends and developments in computer graphics

CERN Document Server

Enderle, G

1982-01-01

Computer graphics methods and tools are being used to a great extent in scientific research. The future development in this area will be influenced both by new hardware developments and by software advances. On the hardware sector, the development of the raster technology will lead to the increased use of colour workstations with more local processing power. Colour hardcopy devices for creating plots, slides, or movies will be available at a lower price than today. The first real 3D-workstations will appear on the marketplace. One of the main activities on the software sector is the standardization of computer graphics systems, graphical files, and device interfaces. This will lead to more portable graphical application programs and to a common base for computer graphics education.

Computational science: Emerging opportunities and challenges

International Nuclear Information System (INIS)

Hendrickson, Bruce

2009-01-01

In the past two decades, computational methods have emerged as an essential component of the scientific and engineering enterprise. A diverse assortment of scientific applications has been simulated and explored via advanced computational techniques. Computer vendors have built enormous parallel machines to support these activities, and the research community has developed new algorithms and codes, and agreed on standards to facilitate ever more ambitious computations. However, this track record of success will be increasingly hard to sustain in coming years. Power limitations constrain processor clock speeds, so further performance improvements will need to come from ever more parallelism. This higher degree of parallelism will require new thinking about algorithms, programming models, and architectural resilience. Simultaneously, cutting edge science increasingly requires more complex simulations with unstructured and adaptive grids, and multi-scale and multi-physics phenomena. These new codes will push existing parallelization strategies to their limits and beyond. Emerging data-rich scientific applications are also in need of high performance computing, but their complex spatial and temporal data access patterns do not perform well on existing machines. These interacting forces will reshape high performance computing in the coming years.

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

Visualization in scientific computing

National Research Council Canada - National Science Library

Nielson, Gregory M; Shriver, Bruce D; Rosenblum, Lawrence J

1990-01-01

The purpose of this text is to provide a reference source to scientists, engineers, and students who are new to scientific visualization or who are interested in expanding their knowledge in this subject...

Applied and numerical partial differential equations scientific computing in simulation, optimization and control in a multidisciplinary context

CERN Document Server

Glowinski, R; Kuznetsov, Y A; Periaux, Jacques; Neittaanmaki, Pekka; Pironneau, Olivier

2010-01-01

Standing at the intersection of mathematics and scientific computing, this collection of state-of-the-art papers in nonlinear PDEs examines their applications to subjects as diverse as dynamical systems, computational mechanics, and the mathematics of finance.

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.

III - Template Metaprogramming for massively parallel scientific computing - Templates for Iteration; Thread-level Parallelism

CERN Multimedia

CERN. Geneva

2016-01-01

Large scale scientific computing raises questions on different levels ranging from the fomulation of the problems to the choice of the best algorithms and their implementation for a specific platform. There are similarities in these different topics that can be exploited by modern-style C++ template metaprogramming techniques to produce readable, maintainable and generic code. Traditional low-level code tend to be fast but platform-dependent, and it obfuscates the meaning of the algorithm. On the other hand, object-oriented approach is nice to read, but may come with an inherent performance penalty. These lectures aim to present he basics of the Expression Template (ET) idiom which allows us to keep the object-oriented approach without sacrificing performance. We will in particular show to to enhance ET to include SIMD vectorization. We will then introduce techniques for abstracting iteration, and introduce thread-level parallelism for use in heavy data-centric loads. We will show to to apply these methods i...

Evaluating computer program performance on the CRAY-1

International Nuclear Information System (INIS)

Rudsinski, L.; Pieper, G.W.

1979-01-01

The Advanced Scientific Computers Project of Argonne's Applied Mathematics Division has two objectives: to evaluate supercomputers and to determine their effect on Argonne's computing workload. Initial efforts have focused on the CRAY-1, which is the only advanced computer currently available. Users from seven Argonne divisions executed test programs on the CRAY and made performance comparisons with the IBM 370/195 at Argonne. This report describes these experiences and discusses various techniques for improving run times on the CRAY. Direct translations of code from scalar to vector processor reduced running times as much as two-fold, and this reduction will become more pronounced as the CRAY compiler is developed. Further improvement (two- to ten-fold) was realized by making minor code changes to facilitate compiler recognition of the parallel and vector structure within the programs. Finally, extensive rewriting of the FORTRAN code structure reduced execution times dramatically, in three cases by a factor of more than 20; and even greater reduction should be possible by changing algorithms within a production code. It is condluded that the CRAY-1 would be of great benefit to Argonne researchers. Existing codes could be modified with relative ease to run significantly faster than on the 370/195. More important, the CRAY would permit scientists to investigate complex problems currently deemed infeasibile on traditional scalar machines. Finally, an interface between the CRAY-1 and IBM computers such as the 370/195, scheduled by Cray Research for the first quarter of 1979, would considerably facilitate the task of integrating the CRAY into Argonne's Central Computing Facility. 13 tables

Designing scientific applications on GPUs

CERN Document Server

Couturier, Raphael

2013-01-01

Many of today's complex scientific applications now require a vast amount of computational power. General purpose graphics processing units (GPGPUs) enable researchers in a variety of fields to benefit from the computational power of all the cores available inside graphics cards.Understand the Benefits of Using GPUs for Many Scientific ApplicationsDesigning Scientific Applications on GPUs shows you how to use GPUs for applications in diverse scientific fields, from physics and mathematics to computer science. The book explains the methods necessary for designing or porting your scientific appl

Cloud Computing in Science and Engineering and the “SciShop.ru” Computer Simulation Center

Directory of Open Access Journals (Sweden)

E. V. Vorozhtsov

2011-12-01

Full Text Available Various aspects of cloud computing applications for scientific research, applied design, and remote education are described in this paper. An analysis of the different aspects is performed based on the experience from the “SciShop.ru” Computer Simulation Center. This analysis shows that cloud computing technology has wide prospects in scientific research applications, applied developments and also remote education of specialists, postgraduates, and students.

Applications of computer algebra

CERN Document Server

1985-01-01

Today, certain computer software systems exist which surpass the computational ability of researchers when their mathematical techniques are applied to many areas of science and engineering. These computer systems can perform a large portion of the calculations seen in mathematical analysis. Despite this massive power, thousands of people use these systems as a routine resource for everyday calculations. These software programs are commonly called "Computer Algebra" systems. They have names such as MACSYMA, MAPLE, muMATH, REDUCE and SMP. They are receiving credit as a computational aid with in­ creasing regularity in articles in the scientific and engineering literature. When most people think about computers and scientific research these days, they imagine a machine grinding away, processing numbers arithmetically. It is not generally realized that, for a number of years, computers have been performing non-numeric computations. This means, for example, that one inputs an equa­ tion and obtains a closed for...

Sign use and cognition in automated scientific discovery: are computers only special kinds of signs?

Science.gov (United States)

Giza, Piotr

2018-04-01

James Fetzer criticizes the computational paradigm, prevailing in cognitive science by questioning, what he takes to be, its most elementary ingredient: that cognition is computation across representations. He argues that if cognition is taken to be a purposive, meaningful, algorithmic problem solving activity, then computers are incapable of cognition. Instead, they appear to be signs of a special kind, that can facilitate computation. He proposes the conception of minds as semiotic systems as an alternative paradigm for understanding mental phenomena, one that seems to overcome the difficulties of computationalism. Now, I argue, that with computer systems dealing with scientific discovery, the matter is not so simple as that. The alleged superiority of humans using signs to stand for something other over computers being merely "physical symbol systems" or "automatic formal systems" is only easy to establish in everyday life, but becomes far from obvious when scientific discovery is at stake. In science, as opposed to everyday life, the meaning of symbols is, apart from very low-level experimental investigations, defined implicitly by the way the symbols are used in explanatory theories or experimental laws relevant to the field, and in consequence, human and machine discoverers are much more on a par. Moreover, the great practical success of the genetic programming method and recent attempts to apply it to automatic generation of cognitive theories seem to show, that computer systems are capable of very efficient problem solving activity in science, which is neither purposive nor meaningful, nor algorithmic. This, I think, undermines Fetzer's argument that computer systems are incapable of cognition because computation across representations is bound to be a purposive, meaningful, algorithmic problem solving activity.

Accelerating scientific discovery : 2007 annual report.

Energy Technology Data Exchange (ETDEWEB)

Beckman, P.; Dave, P.; Drugan, C.

2008-11-14

As a gateway for scientific discovery, the Argonne Leadership Computing Facility (ALCF) works hand in hand with the world's best computational scientists to advance research in a diverse span of scientific domains, ranging from chemistry, applied mathematics, and materials science to engineering physics and life sciences. Sponsored by the U.S. Department of Energy's (DOE) Office of Science, researchers are using the IBM Blue Gene/L supercomputer at the ALCF to study and explore key scientific problems that underlie important challenges facing our society. For instance, a research team at the University of California-San Diego/ SDSC is studying the molecular basis of Parkinson's disease. The researchers plan to use the knowledge they gain to discover new drugs to treat the disease and to identify risk factors for other diseases that are equally prevalent. Likewise, scientists from Pratt & Whitney are using the Blue Gene to understand the complex processes within aircraft engines. Expanding our understanding of jet engine combustors is the secret to improved fuel efficiency and reduced emissions. Lessons learned from the scientific simulations of jet engine combustors have already led Pratt & Whitney to newer designs with unprecedented reductions in emissions, noise, and cost of ownership. ALCF staff members provide in-depth expertise and assistance to those using the Blue Gene/L and optimizing user applications. Both the Catalyst and Applications Performance Engineering and Data Analytics (APEDA) teams support the users projects. In addition to working with scientists running experiments on the Blue Gene/L, we have become a nexus for the broader global community. In partnership with the Mathematics and Computer Science Division at Argonne National Laboratory, we have created an environment where the world's most challenging computational science problems can be addressed. Our expertise in high-end scientific computing enables us to provide

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

Cray XT4: An Early Evaluation for Petascale Scientific Simulation

International Nuclear Information System (INIS)

Alam, Sadaf R.; Barrett, Richard F.; Fahey, Mark R.; Kuehn, Jeffery A.; Sankaran, Ramanan; Worley, Patrick H.; Larkin, Jeffrey M.

2007-01-01

The scientific simulation capabilities of next generation high-end computing technology will depend on striking a balance among memory, processor, I/O, and local and global network performance across the breadth of the scientific simulation space. The Cray XT4 combines commodity AMD dual core Opteron processor technology with the second generation of Cray's custom communication accelerator in a system design whose balance is claimed to be driven by the demands of scientific simulation. This paper presents an evaluation of the Cray XT4 using microbenchmarks to develop a controlled understanding of individual system components, providing the context for analyzing and comprehending the performance of several petascale-ready applications. Results gathered from several strategic application domains are compared with observations on the previous generation Cray XT3 and other high-end computing systems, demonstrating performance improvements across a wide variety of application benchmark problems.

Study on availability of GPU for scientific and engineering calculations

International Nuclear Information System (INIS)

Sakamoto, Kensaku; Kobayashi, Seiji

2009-07-01

Recently, the number of scientific and engineering calculations on GPUs (Graphic Processing Units) is increasing. It is said that GPUs have much higher peak floating-point processing power and memory bandwidth than CPUs (Central Processing Units). We have studied the effectiveness of GPUs by applying them to fundamental scientific and engineering calculations with CUDA (Compute Unified Device Architecture) development tools. The results have shown as follows: 1) Computations on GPUs are effective for such calculations as matrix operation, FFT (Fast Fourier Transform) and CFD (Computational Fluid Dynamics) in nuclear research region. 2) Highly-advanced programming is required for bringing out high performance of GPUs. 3) Double-precision performance is low and ECC (Error Correction Code) in graphic memory systems supports are lacking. (author)

Science on Stage: Engaging and teaching scientific content through performance art

Science.gov (United States)

Posner, Esther

2016-04-01

Engaging teaching material through performance art and music can improve the long-term retention of scientific content. Additionally, the development of effective performance skills are a powerful tool to communicate scientific concepts and information to a broader audience that can have many positive benefits in terms of career development and the delivery of professional presentations. While arts integration has been shown to increase student engagement and achievement, relevant artistic materials are still required for use as supplemental activities in STEM (science, technology, engineering, mathematics) courses. I will present an original performance poem, "Tectonic Petrameter: A Journey Through Earth History," with instructions for its implementation as a play in pre-university and undergraduate geoscience classrooms. "Tectonic Petrameter" uses a dynamic combination of rhythm and rhyme to teach the geological time scale, fundamental concepts in geology and important events in Earth history. I propose that using performance arts, such as "Tectonic Petrameter" and other creative art forms, may be an avenue for breaking down barriers related to teaching students and the broader non-scientific community about Earth's long and complex history.

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

Science.gov (United States)

Alameda, J. C.

2011-12-01

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

Cloud-based opportunities in scientific computing: insights from processing Suomi National Polar-Orbiting Partnership (S-NPP) Direct Broadcast data

Science.gov (United States)

Evans, J. D.; Hao, W.; Chettri, S.

2013-12-01

The cloud is proving to be a uniquely promising platform for scientific computing. Our experience with processing satellite data using Amazon Web Services highlights several opportunities for enhanced performance, flexibility, and cost effectiveness in the cloud relative to traditional computing -- for example: - Direct readout from a polar-orbiting satellite such as the Suomi National Polar-Orbiting Partnership (S-NPP) requires bursts of processing a few times a day, separated by quiet periods when the satellite is out of receiving range. In the cloud, by starting and stopping virtual machines in minutes, we can marshal significant computing resources quickly when needed, but not pay for them when not needed. To take advantage of this capability, we are automating a data-driven approach to the management of cloud computing resources, in which new data availability triggers the creation of new virtual machines (of variable size and processing power) which last only until the processing workflow is complete. - 'Spot instances' are virtual machines that run as long as one's asking price is higher than the provider's variable spot price. Spot instances can greatly reduce the cost of computing -- for software systems that are engineered to withstand unpredictable interruptions in service (as occurs when a spot price exceeds the asking price). We are implementing an approach to workflow management that allows data processing workflows to resume with minimal delays after temporary spot price spikes. This will allow systems to take full advantage of variably-priced 'utility computing.' - Thanks to virtual machine images, we can easily launch multiple, identical machines differentiated only by 'user data' containing individualized instructions (e.g., to fetch particular datasets or to perform certain workflows or algorithms) This is particularly useful when (as is the case with S-NPP data) we need to launch many very similar machines to process an unpredictable number of

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)

Performance Engineering Technology for Scientific Component Software

Energy Technology Data Exchange (ETDEWEB)

Malony, Allen D.

2007-05-08

Large-scale, complex scientific applications are beginning to benefit from the use of component software design methodology and technology for software development. Integral to the success of component-based applications is the ability to achieve high-performing code solutions through the use of performance engineering tools for both intra-component and inter-component analysis and optimization. Our work on this project aimed to develop performance engineering technology for scientific component software in association with the DOE CCTTSS SciDAC project (active during the contract period) and the broader Common Component Architecture (CCA) community. Our specific implementation objectives were to extend the TAU performance system and Program Database Toolkit (PDT) to support performance instrumentation, measurement, and analysis of CCA components and frameworks, and to develop performance measurement and monitoring infrastructure that could be integrated in CCA applications. These objectives have been met in the completion of all project milestones and in the transfer of the technology into the continuing CCA activities as part of the DOE TASCS SciDAC2 effort. In addition to these achievements, over the past three years, we have been an active member of the CCA Forum, attending all meetings and serving in several working groups, such as the CCA Toolkit working group, the CQoS working group, and the Tutorial working group. We have contributed significantly to CCA tutorials since SC'04, hosted two CCA meetings, participated in the annual ACTS workshops, and were co-authors on the recent CCA journal paper [24]. There are four main areas where our project has delivered results: component performance instrumentation and measurement, component performance modeling and optimization, performance database and data mining, and online performance monitoring. This final report outlines the achievements in these areas for the entire project period. The submitted progress

Techniques and tools for measuring energy efficiency of scientific software applications

International Nuclear Information System (INIS)

Abdurachmanov, David; Elmer, Peter; Eulisse, Giulio; Knight, Robert; Niemi, Tapio; Pestana, Gonçalo; Khan, Kashif; Nurminen, Jukka K; Nyback, Filip; Ou, Zhonghong

2015-01-01

The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost. Energy-efficiency has thus become an important concern in scientific fields such as High Energy Physics (HEP). There has been a growing interest in utilizing alternate architectures, such as low power ARM processors, to replace traditional Intel x86 architectures. Nevertheless, even though such solutions have been successfully used in mobile applications with low I/O and memory demands, it is unclear if they are suitable and more energy-efficient in the scientific computing environment. Furthermore, there is a lack of tools and experience to derive and compare power consumption between the architectures for various workloads, and eventually to support software optimizations for energy efficiency. To that end, we have performed several physical and software-based measurements of workloads from HEP applications running on ARM and Intel architectures, and compare their power consumption and performance. We leverage several profiling tools (both in hardware and software) to extract different characteristics of the power use. We report the results of these measurements and the experience gained in developing a set of measurement techniques and profiling tools to accurately assess the power consumption for scientific workloads. (paper)

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

Smolyak's algorithm: A powerful black box for the acceleration of scientific computations

KAUST Repository

Tempone, Raul; Wolfers, Soeren

2017-01-01

We provide a general discussion of Smolyak's algorithm for the acceleration of scientific computations. The algorithm first appeared in Smolyak's work on multidimensional integration and interpolation. Since then, it has been generalized in multiple directions and has been associated with the keywords: sparse grids, hyperbolic cross approximation, combination technique, and multilevel methods. Variants of Smolyak's algorithm have been employed in the computation of high-dimensional integrals in finance, chemistry, and physics, in the numerical solution of partial and stochastic differential equations, and in uncertainty quantification. Motivated by this broad and ever-increasing range of applications, we describe a general framework that summarizes fundamental results and assumptions in a concise application-independent manner.

Smolyak's algorithm: A powerful black box for the acceleration of scientific computations

KAUST Repository

Tempone, Raul

2017-03-26

We provide a general discussion of Smolyak\\'s algorithm for the acceleration of scientific computations. The algorithm first appeared in Smolyak\\'s work on multidimensional integration and interpolation. Since then, it has been generalized in multiple directions and has been associated with the keywords: sparse grids, hyperbolic cross approximation, combination technique, and multilevel methods. Variants of Smolyak\\'s algorithm have been employed in the computation of high-dimensional integrals in finance, chemistry, and physics, in the numerical solution of partial and stochastic differential equations, and in uncertainty quantification. Motivated by this broad and ever-increasing range of applications, we describe a general framework that summarizes fundamental results and assumptions in a concise application-independent manner.

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

Techniques and tools for measuring energy efficiency of scientific software applications

CERN Document Server

Abdurachmanov, David; Eulisse, Giulio; Knight, Robert; Niemi, Tapio; Nurminen, Jukka K.; Nyback, Filip; Pestana, Goncalo; Ou, Zhonghong; Khan, Kashif

2014-01-01

The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost. Energy-efficiency has thus become an important concern in scientific fields such as High Energy Physics (HEP). There has been a growing interest in utilizing alternate architectures, such as low power ARM processors, to replace traditional Intel x86 architectures. Nevertheless, even though such solutions have been successfully used in mobile applications with low I/O and memory demands, it is unclear if they are suitable and more energy-efficient in the scientific computing environment. Furthermore, there is a lack of tools and experience to derive and compare power consumption between the architectures for various workloads, and eventually to support software optimizations for energy efficiency. To that end, we have performed several physical and software-based measurements of workloads from HEP applications running o...

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

International Nuclear Information System (INIS)

Fujii, Minoru; Asai, Kiyoshi

1980-08-01

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

Energy Smart Management of Scientific Data

Energy Technology Data Exchange (ETDEWEB)

Otoo, Ekow; Rotem, Dron; Tsao, Shih-Chiang

2009-04-12

Scientific data centers comprised of high-powered computing equipment and large capacity disk storage systems consume considerable amount of energy. Dynamic power management techniques (DPM) are commonly used for saving energy in disk systems. These involve powering down disks that exhibit long idle periods and placing them in standby mode. A file request from a disk in standby mode will incur both energy and performance penalties as it takes energy (and time) to spin up the disk before it can serve a file. For this reason, DPM has to make decisions as to when to transition the disk into standby mode such that the energy saved is greater than the energy needed to spin it up again and the performance penalty is tolerable. The length of the idle period until the DPM decides to power down a disk is called idlenessthreshold. In this paper, we study both analytically and experimentally dynamic power management techniques that save energy subject to performance constraints on file access costs. Based on observed workloads of scientific applications and disk characteristics, we provide a methodology for determining file assignment to disks and computing idleness thresholds that result in significant improvements to the energy saved by existing DPMsolutions while meeting response time constraints. We validate our methods with simulations that use traces taken from scientific applications.

The radar signature of revolution objects in scientific computing

International Nuclear Information System (INIS)

Bonnemason, P.; Le Martret, R.; Scheurer, B.; Stupfel, B.

1990-12-01

This work is motivated by the study of stealthy (or discrete) revolution objects vis-a-vis a radar. Efficient algorithms, specific numerical methods and two original industrial software (SHF 89 and SHF C) have been developed. These are reliable tools in intensive scientific computing. In particular, they have enabled the precise numerical modeling of complex objects, of very general forms, in the field of high frequencies and a thorough understanding of the physics of the problems involved. The purpose of this note is a general description of the work and its context, which is illustrated by examples of numerical applications (presented in Appendix 4). The technical aspects are detailed in reports and publications (a list is attached to this note) [fr

Enhancing reproducibility in scientific computing: Metrics and registry for Singularity containers

Science.gov (United States)

Prybol, Cameron J.; Kurtzer, Gregory M.

2017-01-01

Here we present Singularity Hub, a framework to build and deploy Singularity containers for mobility of compute, and the singularity-python software with novel metrics for assessing reproducibility of such containers. Singularity containers make it possible for scientists and developers to package reproducible software, and Singularity Hub adds automation to this workflow by building, capturing metadata for, visualizing, and serving containers programmatically. Our novel metrics, based on custom filters of content hashes of container contents, allow for comparison of an entire container, including operating system, custom software, and metadata. First we will review Singularity Hub’s primary use cases and how the infrastructure has been designed to support modern, common workflows. Next, we conduct three analyses to demonstrate build consistency, reproducibility metric and performance and interpretability, and potential for discovery. This is the first effort to demonstrate a rigorous assessment of measurable similarity between containers and operating systems. We provide these capabilities within Singularity Hub, as well as the source software singularity-python that provides the underlying functionality. Singularity Hub is available at https://singularity-hub.org, and we are excited to provide it as an openly available platform for building, and deploying scientific containers. PMID:29186161

Enhancing reproducibility in scientific computing: Metrics and registry for Singularity containers.

Directory of Open Access Journals (Sweden)

Vanessa V Sochat

Full Text Available Here we present Singularity Hub, a framework to build and deploy Singularity containers for mobility of compute, and the singularity-python software with novel metrics for assessing reproducibility of such containers. Singularity containers make it possible for scientists and developers to package reproducible software, and Singularity Hub adds automation to this workflow by building, capturing metadata for, visualizing, and serving containers programmatically. Our novel metrics, based on custom filters of content hashes of container contents, allow for comparison of an entire container, including operating system, custom software, and metadata. First we will review Singularity Hub's primary use cases and how the infrastructure has been designed to support modern, common workflows. Next, we conduct three analyses to demonstrate build consistency, reproducibility metric and performance and interpretability, and potential for discovery. This is the first effort to demonstrate a rigorous assessment of measurable similarity between containers and operating systems. We provide these capabilities within Singularity Hub, as well as the source software singularity-python that provides the underlying functionality. Singularity Hub is available at https://singularity-hub.org, and we are excited to provide it as an openly available platform for building, and deploying scientific containers.

Advanced scientific computational methods and their applications to nuclear technologies. (3) Introduction of continuum simulation methods and their applications (3)

International Nuclear Information System (INIS)

Satake, Shin-ichi; Kunugi, Tomoaki

2006-01-01

Scientific computational methods have advanced remarkably with the progress of nuclear development. They have played the role of weft connecting each realm of nuclear engineering and then an introductory course of advanced scientific computational methods and their applications to nuclear technologies were prepared in serial form. This is the third issue showing the introduction of continuum simulation methods and their applications. Spectral methods and multi-interface calculation methods in fluid dynamics are reviewed. (T. Tanaka)

Instrumentation for Scientific Computing in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics.

Science.gov (United States)

1987-10-01

include Security Classification) Instrumentation for scientific computing in neural networks, information science, artificial intelligence, and...instrumentation grant to purchase equipment for support of research in neural networks, information science, artificail intellignece , and applied mathematics...in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics Contract AFOSR 86-0282 Principal Investigator: Stephen

Computer simulation, rhetoric, and the scientific imagination how virtual evidence shapes science in the making and in the news

CERN Document Server

Roundtree, Aimee Kendall

2013-01-01

Computer simulations help advance climatology, astrophysics, and other scientific disciplines. They are also at the crux of several high-profile cases of science in the news. How do simulation scientists, with little or no direct observations, make decisions about what to represent? What is the nature of simulated evidence, and how do we evaluate its strength? Aimee Kendall Roundtree suggests answers in Computer Simulation, Rhetoric, and the Scientific Imagination. She interprets simulations in the sciences by uncovering the argumentative strategies that underpin the production and disseminati

Studying Scientific Discovery by Computer Simulation.

Science.gov (United States)

1983-03-30

Mendel’s laws of inheritance, the law of Gay- Lussac for gaseous reactions, tile law of Dulong and Petit, the derivation of atomic weights by Avogadro...neceseary mid identify by block number) scientific discovery -ittri sic properties physical laws extensive terms data-driven heuristics intensive...terms theory-driven heuristics conservation laws 20. ABSTRACT (Continue on revere. side It necessary and identify by block number) Scientific discovery

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.

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

Software support for students engaging in scientific activity and scientific controversy

Science.gov (United States)

Cavalli-Sforza, Violetta; Weiner, Arlene W.; Lesgold, Alan M.

Computer environments could support students in engaging in cognitive activities that are essential to scientific practice and to the understanding of the nature of scientific knowledge, but that are difficult to manage in science classrooms. The authors describe a design for a computer-based environment to assist students in conducting dialectical activities of constructing, comparing, and evaluating arguments for competing scientific theories. Their choice of activities and their design respond to educators' and theorists' criticisms of current science curricula. They give detailed specifications of portions of the environment.

Advanced Scientific Computing Research Network Requirements: ASCR Network Requirements Review Final Report

Energy Technology Data Exchange (ETDEWEB)

Bacon, Charles [Argonne National Lab. (ANL), Argonne, IL (United States); Bell, Greg [ESnet, Berkeley, CA (United States); Canon, Shane [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dart, Eli [ESnet, Berkeley, CA (United States); Dattoria, Vince [Dept. of Energy (DOE), Washington DC (United States). Office of Science. Advanced Scientific Computing Research (ASCR); Goodwin, Dave [Dept. of Energy (DOE), Washington DC (United States). Office of Science. Advanced Scientific Computing Research (ASCR); Lee, Jason [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hicks, Susan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Holohan, Ed [Argonne National Lab. (ANL), Argonne, IL (United States); Klasky, Scott [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lauzon, Carolyn [Dept. of Energy (DOE), Washington DC (United States). Office of Science. Advanced Scientific Computing Research (ASCR); Rogers, Jim [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Shipman, Galen [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Skinner, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Tierney, Brian [ESnet, Berkeley, CA (United States)

2013-03-08

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In October 2012, ESnet and the Office of Advanced Scientific Computing Research (ASCR) of the DOE SC organized a review to characterize the networking requirements of the programs funded by the ASCR program office. The requirements identified at the review are summarized in the Findings section, and are described in more detail in the body of the report.

Evaluating the Efficacy of the Cloud for Cluster Computation

Science.gov (United States)

Knight, David; Shams, Khawaja; Chang, George; Soderstrom, Tom

2012-01-01

Computing requirements vary by industry, and it follows that NASA and other research organizations have computing demands that fall outside the mainstream. While cloud computing made rapid inroads for tasks such as powering web applications, performance issues on highly distributed tasks hindered early adoption for scientific computation. One venture to address this problem is Nebula, NASA's homegrown cloud project tasked with delivering science-quality cloud computing resources. However, another industry development is Amazon's high-performance computing (HPC) instances on Elastic Cloud Compute (EC2) that promises improved performance for cluster computation. This paper presents results from a series of benchmarks run on Amazon EC2 and discusses the efficacy of current commercial cloud technology for running scientific applications across a cluster. In particular, a 240-core cluster of cloud instances achieved 2 TFLOPS on High-Performance Linpack (HPL) at 70% of theoretical computational performance. The cluster's local network also demonstrated sub-100 ?s inter-process latency with sustained inter-node throughput in excess of 8 Gbps. Beyond HPL, a real-world Hadoop image processing task from NASA's Lunar Mapping and Modeling Project (LMMP) was run on a 29 instance cluster to process lunar and Martian surface images with sizes on the order of tens of gigapixels. These results demonstrate that while not a rival of dedicated supercomputing clusters, commercial cloud technology is now a feasible option for moderately demanding scientific workloads.

Computer application in scientific investigations

International Nuclear Information System (INIS)

Govorun, N.N.

1981-01-01

A short review of the computer development and application and software in JINR for the last 15 years is presented. Main trends of studies on computer application in experimental and theoretical investigations are enumerated: software of computers and their systems, software of data processing systems, designing automatic and automized systems for measuring track detectors images, development of technique of carrying out experiments on computer line, packets of applied computer codes and specialized systems. The development of the on line technique is successfully used in investigations of nuclear processes at relativistic energies. The new trend is the development of television methods of data output and its computer recording [ru

"Enheduanna-A Manifesto of Falling" Live Brain-Computer Cinema Performance: Performer and Audience Participation, Cognition and Emotional Engagement Using Multi-Brain BCI Interaction.

Science.gov (United States)

Zioga, Polina; Pollick, Frank; Ma, Minhua; Chapman, Paul; Stefanov, Kristian

2018-01-01

The fields of neural prosthetic technologies and Brain-Computer Interfaces (BCIs) have witnessed in the past 15 years an unprecedented development, bringing together theories and methods from different scientific fields, digital media, and the arts. More in particular, artists have been amongst the pioneers of the design of relevant applications since their emergence in the 1960s, pushing the boundaries of applications in real-life contexts. With the new research, advancements, and since 2007, the new low-cost commercial-grade wireless devices, there is a new increasing number of computer games, interactive installations, and performances that involve the use of these interfaces, combining scientific, and creative methodologies. The vast majority of these works use the brain-activity of a single participant. However, earlier, as well as recent examples, involve the simultaneous interaction of more than one participants or performers with the use of Electroencephalography (EEG)-based multi-brain BCIs. In this frame, we discuss and evaluate "Enheduanna-A Manifesto of Falling," a live brain-computer cinema performance that enables for the first time the simultaneous real-time multi-brain interaction of more than two participants, including a performer and members of the audience, using a passive EEG-based BCI system in the context of a mixed-media performance. The performance was realised as a neuroscientific study conducted in a real-life setting. The raw EEG data of seven participants, one performer and two different members of the audience for each performance, were simultaneously recorded during three live events. The results reveal that the majority of the participants were able to successfully identify whether their brain-activity was interacting with the live video projections or not. A correlation has been found between their answers to the questionnaires, the elements of the performance that they identified as most special, and the audience's indicators of

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

File-System Workload on a Scientific Multiprocessor

Science.gov (United States)

Kotz, David; Nieuwejaar, Nils

1995-01-01

Many scientific applications have intense computational and I/O requirements. Although multiprocessors have permitted astounding increases in computational performance, the formidable I/O needs of these applications cannot be met by current multiprocessors a their I/O subsystems. To prevent I/O subsystems from forever bottlenecking multiprocessors and limiting the range of feasible applications, new I/O subsystems must be designed. The successful design of computer systems (both hardware and software) depends on a thorough understanding of their intended use. A system designer optimizes the policies and mechanisms for the cases expected to most common in the user's workload. In the case of multiprocessor file systems, however, designers have been forced to build file systems based only on speculation about how they would be used, extrapolating from file-system characterizations of general-purpose workloads on uniprocessor and distributed systems or scientific workloads on vector supercomputers (see sidebar on related work). To help these system designers, in June 1993 we began the Charisma Project, so named because the project sought to characterize 1/0 in scientific multiprocessor applications from a variety of production parallel computing platforms and sites. The Charisma project is unique in recording individual read and write requests-in live, multiprogramming, parallel workloads (rather than from selected or nonparallel applications). In this article, we present the first results from the project: a characterization of the file-system workload an iPSC/860 multiprocessor running production, parallel scientific applications at NASA's Ames Research Center.

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.

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 ...

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.

THE CENTER FOR DATA INTENSIVE COMPUTING

Energy Technology Data Exchange (ETDEWEB)

GLIMM,J.

2002-11-01

CDIC will provide state-of-the-art computational and computer science for the Laboratory and for the broader DOE and scientific community. We achieve this goal by performing advanced scientific computing research in the Laboratory's mission areas of High Energy and Nuclear Physics, Biological and Environmental Research, and Basic Energy Sciences. We also assist other groups at the Laboratory to reach new levels of achievement in computing. We are ''data intensive'' because the production and manipulation of large quantities of data are hallmarks of scientific research in the 21st century and are intrinsic features of major programs at Brookhaven. An integral part of our activity to accomplish this mission will be a close collaboration with the University at Stony Brook.

THE CENTER FOR DATA INTENSIVE COMPUTING

Energy Technology Data Exchange (ETDEWEB)

GLIMM,J.

2001-11-01

CDIC will provide state-of-the-art computational and computer science for the Laboratory and for the broader DOE and scientific community. We achieve this goal by performing advanced scientific computing research in the Laboratory's mission areas of High Energy and Nuclear Physics, Biological and Environmental Research, and Basic Energy Sciences. We also assist other groups at the Laboratory to reach new levels of achievement in computing. We are ''data intensive'' because the production and manipulation of large quantities of data are hallmarks of scientific research in the 21st century and are intrinsic features of major programs at Brookhaven. An integral part of our activity to accomplish this mission will be a close collaboration with the University at Stony Brook.

THE CENTER FOR DATA INTENSIVE COMPUTING

International Nuclear Information System (INIS)

GLIMM, J.

2001-01-01

CDIC will provide state-of-the-art computational and computer science for the Laboratory and for the broader DOE and scientific community. We achieve this goal by performing advanced scientific computing research in the Laboratory's mission areas of High Energy and Nuclear Physics, Biological and Environmental Research, and Basic Energy Sciences. We also assist other groups at the Laboratory to reach new levels of achievement in computing. We are ''data intensive'' because the production and manipulation of large quantities of data are hallmarks of scientific research in the 21st century and are intrinsic features of major programs at Brookhaven. An integral part of our activity to accomplish this mission will be a close collaboration with the University at Stony Brook

THE CENTER FOR DATA INTENSIVE COMPUTING

Energy Technology Data Exchange (ETDEWEB)

GLIMM,J.

2003-11-01

CDIC will provide state-of-the-art computational and computer science for the Laboratory and for the broader DOE and scientific community. We achieve this goal by performing advanced scientific computing research in the Laboratory's mission areas of High Energy and Nuclear Physics, Biological and Environmental Research, and Basic Energy Sciences. We also assist other groups at the Laboratory to reach new levels of achievement in computing. We are ''data intensive'' because the production and manipulation of large quantities of data are hallmarks of scientific research in the 21st century and are intrinsic features of major programs at Brookhaven. An integral part of our activity to accomplish this mission will be a close collaboration with the University at Stony Brook.

N286.7-99, A Canadian standard specifying software quality management system requirements for analytical, scientific, and design computer programs and its implementation at AECL

International Nuclear Information System (INIS)

Abel, R.

2000-01-01

Analytical, scientific, and design computer programs (referred to in this paper as 'scientific computer programs') are developed for use in a large number of ways by the user-engineer to support and prove engineering calculations and assumptions. These computer programs are subject to frequent modifications inherent in their application and are often used for critical calculations and analysis relative to safety and functionality of equipment and systems. N286.7-99(4) was developed to establish appropriate quality management system requirements to deal with the development, modification, and application of scientific computer programs. N286.7-99 provides particular guidance regarding the treatment of legacy codes

Computer technique for evaluating collimator performance

International Nuclear Information System (INIS)

Rollo, F.D.

1975-01-01

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

An Analysis on the Effect of Computer Self-Efficacy over Scientific Research Self-Efficacy and Information Literacy Self-Efficacy

Science.gov (United States)

Tuncer, Murat

2013-01-01

Present research investigates reciprocal relations amidst computer self-efficacy, scientific research and information literacy self-efficacy. Research findings have demonstrated that according to standardized regression coefficients, computer self-efficacy has a positive effect on information literacy self-efficacy. Likewise it has been detected…

DB90: A Fortran Callable Relational Database Routine for Scientific and Engineering Computer Programs

Science.gov (United States)

Wrenn, Gregory A.

2005-01-01

This report describes a database routine called DB90 which is intended for use with scientific and engineering computer programs. The software is written in the Fortran 90/95 programming language standard with file input and output routines written in the C programming language. These routines should be completely portable to any computing platform and operating system that has Fortran 90/95 and C compilers. DB90 allows a program to supply relation names and up to 5 integer key values to uniquely identify each record of each relation. This permits the user to select records or retrieve data in any desired order.

A Secure Web Application Providing Public Access to High-Performance Data Intensive Scientific Resources - ScalaBLAST Web Application

International Nuclear Information System (INIS)

Curtis, Darren S.; Peterson, Elena S.; Oehmen, Chris S.

2008-01-01

This work presents the ScalaBLAST Web Application (SWA), a web based application implemented using the PHP script language, MySQL DBMS, and Apache web server under a GNU/Linux platform. SWA is an application built as part of the Data Intensive Computer for Complex Biological Systems (DICCBS) project at the Pacific Northwest National Laboratory (PNNL). SWA delivers accelerated throughput of bioinformatics analysis via high-performance computing through a convenient, easy-to-use web interface. This approach greatly enhances emerging fields of study in biology such as ontology-based homology, and multiple whole genome comparisons which, in the absence of a tool like SWA, require a heroic effort to overcome the computational bottleneck associated with genome analysis. The current version of SWA includes a user account management system, a web based user interface, and a backend process that generates the files necessary for the Internet scientific community to submit a ScalaBLAST parallel processing job on a dedicated cluster

Scientific Applications Performance Evaluation on Burst Buffer

KAUST Repository

Markomanolis, George S.; Hadri, Bilel; Khurram, Rooh Ul Amin; Feki, Saber

2017-01-01

Parallel I/O is an integral component of modern high performance computing, especially in storing and processing very large datasets, such as the case of seismic imaging, CFD, combustion and weather modeling. The storage hierarchy includes nowadays

A Hybrid Metaheuristic for Multi-Objective Scientific Workflow Scheduling in a Cloud Environment

Directory of Open Access Journals (Sweden)

Nazia Anwar

2018-03-01

Full Text Available Cloud computing has emerged as a high-performance computing environment with a large pool of abstracted, virtualized, flexible, and on-demand resources and services. Scheduling of scientific workflows in a distributed environment is a well-known NP-complete problem and therefore intractable with exact solutions. It becomes even more challenging in the cloud computing platform due to its dynamic and heterogeneous nature. The aim of this study is to optimize multi-objective scheduling of scientific workflows in a cloud computing environment based on the proposed metaheuristic-based algorithm, Hybrid Bio-inspired Metaheuristic for Multi-objective Optimization (HBMMO. The strong global exploration ability of the nature-inspired metaheuristic Symbiotic Organisms Search (SOS is enhanced by involving an efficient list-scheduling heuristic, Predict Earliest Finish Time (PEFT, in the proposed algorithm to obtain better convergence and diversity of the approximate Pareto front in terms of reduced makespan, minimized cost, and efficient load balance of the Virtual Machines (VMs. The experiments using different scientific workflow applications highlight the effectiveness, practicality, and better performance of the proposed algorithm.

Computer graphics and research projects

International Nuclear Information System (INIS)

Ingtrakul, P.

1994-01-01

This report was prepared as an account of scientific visualization tools and application tools for scientists and engineers. It is provided a set of tools to create pictures and to interact with them in natural ways. It applied many techniques of computer graphics and computer animation through a number of full-color presentations as computer animated commercials, 3D computer graphics, dynamic and environmental simulations, scientific modeling and visualization, physically based modelling, and beavioral, skelatal, dynamics, and particle animation. It took in depth at original hardware and limitations of existing PC graphics adapters contain syste m performance, especially with graphics intensive application programs and user interfaces

SCEE 2008 book of abstracts. The 7. international conference on scientific computing in electrical engineering (SCEE 2008)

Energy Technology Data Exchange (ETDEWEB)

Roos, J.; Costa, L.R.J. (ed.)

2008-09-15

SCEE is an international conference series dedicated to Scientific Computing in Electrical Engineering. The 7th International Conference on Scientific Computing in Electrical Engineering (SCEE 2008) in Espoo, Finland, is organized by the Helsinki University of Technology (TKK); Faculty of Electronics, Communications and Automation (ECA); Department of Radio Science and Engineering (RAD); Circuit Theory Group. (SCEE 2008 web site: http://www.ct.tkk.fi/scee2008/). The aim of the SCEE 2008 conference is to bring together scientists from academia and industry with the goal of intensive discussions on modeling and numerical simulation of electronic circuits and of electromagnetic fields. The conference is mainly directed towards mathematicians and electrical engineers. The SCEE 2008 conference has the following four main topics: 1. Computational Electromagnetics (CE), 2. Circuit Simulation (CS), 3. Coupled Problems (CP), 4. Mathematical and Computational Methods (CM). The selection of abstracts in this book was carried out by the Program Committee; each abstract was reviewed by two or three reviewers. The authors of all accepted abstracts were invited to submit an extended full paper, which will be reviewed as well. The accepted full papers will later on be published in a separate post-conference book

Parallel visualization on leadership computing resources

Energy Technology Data Exchange (ETDEWEB)

Peterka, T; Ross, R B [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439 (United States); Shen, H-W [Department of Computer Science and Engineering, Ohio State University, Columbus, OH 43210 (United States); Ma, K-L [Department of Computer Science, University of California at Davis, Davis, CA 95616 (United States); Kendall, W [Department of Electrical Engineering and Computer Science, University of Tennessee at Knoxville, Knoxville, TN 37996 (United States); Yu, H, E-mail: tpeterka@mcs.anl.go [Sandia National Laboratories, California, Livermore, CA 94551 (United States)

2009-07-01

Changes are needed in the way that visualization is performed, if we expect the analysis of scientific data to be effective at the petascale and beyond. By using similar techniques as those used to parallelize simulations, such as parallel I/O, load balancing, and effective use of interprocess communication, the supercomputers that compute these datasets can also serve as analysis and visualization engines for them. Our team is assessing the feasibility of performing parallel scientific visualization on some of the most powerful computational resources of the U.S. Department of Energy's National Laboratories in order to pave the way for analyzing the next generation of computational results. This paper highlights some of the conclusions of that research.

Parallel visualization on leadership computing resources

International Nuclear Information System (INIS)

Peterka, T; Ross, R B; Shen, H-W; Ma, K-L; Kendall, W; Yu, H

2009-01-01

Changes are needed in the way that visualization is performed, if we expect the analysis of scientific data to be effective at the petascale and beyond. By using similar techniques as those used to parallelize simulations, such as parallel I/O, load balancing, and effective use of interprocess communication, the supercomputers that compute these datasets can also serve as analysis and visualization engines for them. Our team is assessing the feasibility of performing parallel scientific visualization on some of the most powerful computational resources of the U.S. Department of Energy's National Laboratories in order to pave the way for analyzing the next generation of computational results. This paper highlights some of the conclusions of that research.

“Enheduanna—A Manifesto of Falling” Live Brain-Computer Cinema Performance: Performer and Audience Participation, Cognition and Emotional Engagement Using Multi-Brain BCI Interaction

Science.gov (United States)

Zioga, Polina; Pollick, Frank; Ma, Minhua; Chapman, Paul; Stefanov, Kristian

2018-01-01

The fields of neural prosthetic technologies and Brain-Computer Interfaces (BCIs) have witnessed in the past 15 years an unprecedented development, bringing together theories and methods from different scientific fields, digital media, and the arts. More in particular, artists have been amongst the pioneers of the design of relevant applications since their emergence in the 1960s, pushing the boundaries of applications in real-life contexts. With the new research, advancements, and since 2007, the new low-cost commercial-grade wireless devices, there is a new increasing number of computer games, interactive installations, and performances that involve the use of these interfaces, combining scientific, and creative methodologies. The vast majority of these works use the brain-activity of a single participant. However, earlier, as well as recent examples, involve the simultaneous interaction of more than one participants or performers with the use of Electroencephalography (EEG)-based multi-brain BCIs. In this frame, we discuss and evaluate “Enheduanna—A Manifesto of Falling,” a live brain-computer cinema performance that enables for the first time the simultaneous real-time multi-brain interaction of more than two participants, including a performer and members of the audience, using a passive EEG-based BCI system in the context of a mixed-media performance. The performance was realised as a neuroscientific study conducted in a real-life setting. The raw EEG data of seven participants, one performer and two different members of the audience for each performance, were simultaneously recorded during three live events. The results reveal that the majority of the participants were able to successfully identify whether their brain-activity was interacting with the live video projections or not. A correlation has been found between their answers to the questionnaires, the elements of the performance that they identified as most special, and the audience's indicators

“Enheduanna—A Manifesto of Falling” Live Brain-Computer Cinema Performance: Performer and Audience Participation, Cognition and Emotional Engagement Using Multi-Brain BCI Interaction

Directory of Open Access Journals (Sweden)

Polina Zioga

2018-04-01

Full Text Available The fields of neural prosthetic technologies and Brain-Computer Interfaces (BCIs have witnessed in the past 15 years an unprecedented development, bringing together theories and methods from different scientific fields, digital media, and the arts. More in particular, artists have been amongst the pioneers of the design of relevant applications since their emergence in the 1960s, pushing the boundaries of applications in real-life contexts. With the new research, advancements, and since 2007, the new low-cost commercial-grade wireless devices, there is a new increasing number of computer games, interactive installations, and performances that involve the use of these interfaces, combining scientific, and creative methodologies. The vast majority of these works use the brain-activity of a single participant. However, earlier, as well as recent examples, involve the simultaneous interaction of more than one participants or performers with the use of Electroencephalography (EEG-based multi-brain BCIs. In this frame, we discuss and evaluate “Enheduanna—A Manifesto of Falling,” a live brain-computer cinema performance that enables for the first time the simultaneous real-time multi-brain interaction of more than two participants, including a performer and members of the audience, using a passive EEG-based BCI system in the context of a mixed-media performance. The performance was realised as a neuroscientific study conducted in a real-life setting. The raw EEG data of seven participants, one performer and two different members of the audience for each performance, were simultaneously recorded during three live events. The results reveal that the majority of the participants were able to successfully identify whether their brain-activity was interacting with the live video projections or not. A correlation has been found between their answers to the questionnaires, the elements of the performance that they identified as most special, and the

Teaching Scientific Computing: A Model-Centered Approach to Pipeline and Parallel Programming with C

Directory of Open Access Journals (Sweden)

Vladimiras Dolgopolovas

2015-01-01

Full Text Available The aim of this study is to present an approach to the introduction into pipeline and parallel computing, using a model of the multiphase queueing system. Pipeline computing, including software pipelines, is among the key concepts in modern computing and electronics engineering. The modern computer science and engineering education requires a comprehensive curriculum, so the introduction to pipeline and parallel computing is the essential topic to be included in the curriculum. At the same time, the topic is among the most motivating tasks due to the comprehensive multidisciplinary and technical requirements. To enhance the educational process, the paper proposes a novel model-centered framework and develops the relevant learning objects. It allows implementing an educational platform of constructivist learning process, thus enabling learners’ experimentation with the provided programming models, obtaining learners’ competences of the modern scientific research and computational thinking, and capturing the relevant technical knowledge. It also provides an integral platform that allows a simultaneous and comparative introduction to pipelining and parallel computing. The programming language C for developing programming models and message passing interface (MPI and OpenMP parallelization tools have been chosen for implementation.

A data management system for engineering and scientific computing

Science.gov (United States)

Elliot, L.; Kunii, H. S.; Browne, J. C.

1978-01-01

Data elements and relationship definition capabilities for this data management system are explicitly tailored to the needs of engineering and scientific computing. System design was based upon studies of data management problems currently being handled through explicit programming. The system-defined data element types include real scalar numbers, vectors, arrays and special classes of arrays such as sparse arrays and triangular arrays. The data model is hierarchical (tree structured). Multiple views of data are provided at two levels. Subschemas provide multiple structural views of the total data base and multiple mappings for individual record types are supported through the use of a REDEFINES capability. The data definition language and the data manipulation language are designed as extensions to FORTRAN. Examples of the coding of real problems taken from existing practice in the data definition language and the data manipulation language are given.

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.

11th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing

CERN Document Server

Nuyens, Dirk

2016-01-01

This book presents the refereed proceedings of the Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Leuven (Belgium) in April 2014. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.

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

Science.gov (United States)

Faraj, Ahmad [Rochester, MN

2012-04-17

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

The role of dedicated data computing centers in the age of cloud computing

Science.gov (United States)

Caramarcu, Costin; Hollowell, Christopher; Strecker-Kellogg, William; Wong, Antonio; Zaytsev, Alexandr

2017-10-01

Brookhaven National Laboratory (BNL) anticipates significant growth in scientific programs with large computing and data storage needs in the near future and has recently reorganized support for scientific computing to meet these needs. A key component is the enhanced role of the RHIC-ATLAS Computing Facility (RACF) in support of high-throughput and high-performance computing (HTC and HPC) at BNL. This presentation discusses the evolving role of the RACF at BNL, in light of its growing portfolio of responsibilities and its increasing integration with cloud (academic and for-profit) computing activities. We also discuss BNL’s plan to build a new computing center to support the new responsibilities of the RACF and present a summary of the cost benefit analysis done, including the types of computing activities that benefit most from a local data center vs. cloud computing. This analysis is partly based on an updated cost comparison of Amazon EC2 computing services and the RACF, which was originally conducted in 2012.

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

Performance-Driven Interface Contract Enforcement for Scientific Components

Energy Technology Data Exchange (ETDEWEB)

Dahlgren, Tamara Lynn [Univ. of California, Davis, CA (United States)

2008-01-01

Performance-driven interface contract enforcement research aims to improve the quality of programs built from plug-and-play scientific components. Interface contracts make the obligations on the caller and all implementations of the specified methods explicit. Runtime contract enforcement is a well-known technique for enhancing testing and debugging. However, checking all of the associated constraints during deployment is generally considered too costly from a performance stand point. Previous solutions enforced subsets of constraints without explicit consideration of their performance implications. Hence, this research measures the impacts of different interface contract sampling strategies and compares results with new techniques driven by execution time estimates. Results from three studies indicate automatically adjusting the level of checking based on performance constraints improves the likelihood of detecting contract violations under certain circumstances. Specifically, performance-driven enforcement is better suited to programs exercising constraints whose costs are at most moderately expensive relative to normal program execution.

CÓMPUTO DE ALTO DESEMPEÑO PARA OPERACIONES VECTORIALES EN BLAS-1 // INCREASED COMPUTATIONAL PERFORMANCE FOR VECTOR OPERATIONS ON BLAS-1

OpenAIRE

José Antonio Muñoz Gómez; Abimael Jiménez Pérez; Gustavo Rodríguez Gómez

2014-01-01

The functions library, called Basic Linear Algebra Subprograms (BLAS-1), is considered the programming standard in scientific computing. In this work, we focus on the analysis of various code optimization techniques to increase the computational performance of BLAS-1. In particular, we address a combinational approach to explore possible methods of encoding using unroll technique with different levels of depth, vector data programming with MMX and SSE for Intel processors. Using the main func...

MATLAB-Like Scripting of Java Scientific Libraries in ScalaLab

Directory of Open Access Journals (Sweden)

Stergios Papadimitriou

2014-01-01

Full Text Available Although there are a lot of robust and effective scientific libraries in Java, the utilization of these libraries in pure Java is difficult and cumbersome, especially for the average scientist that does not expertise in software development. We illustrate that ScalaLab presents an easier and productive MATLAB like front end. Also, the main strengths and weaknesses of the core Java libraries of ScalaLab are elaborated. Since performance is of paramount importance for scientific computation, the article discusses extensively performance aspects of the ScalaLab environment. Also, Java bytecode performance is compared to native code.

Facilitating Preschoolers' Scientific Knowledge Construction via Computer Games Regarding Light and Shadow: The Effect of the Prediction-Observation-Explanation (POE) Strategy

Science.gov (United States)

Hsu, Chung-Yuan; Tsai, Chin-Chung; Liang, Jyh-Chong

2011-10-01

Educational researchers have suggested that computer games have a profound influence on students' motivation, knowledge construction, and learning performance, but little empirical research has targeted preschoolers. Thus, the purpose of the present study was to investigate the effects of implementing a computer game that integrates the prediction-observation-explanation (POE) strategy (White and Gunstone in Probing understanding. Routledge, New York, 1992) on facilitating preschoolers' acquisition of scientific concepts regarding light and shadow. The children's alternative conceptions were explored as well. Fifty participants were randomly assigned into either an experimental group that played a computer game integrating the POE model or a control group that played a non-POE computer game. By assessing the students' conceptual understanding through interviews, this study revealed that the students in the experimental group significantly outperformed their counterparts in the concepts regarding "shadow formation in daylight" and "shadow orientation." However, children in both groups, after playing the games, still expressed some alternative conceptions such as "Shadows always appear behind a person" and "Shadows should be on the same side as the sun."

Final Report for 'Center for Technology for Advanced Scientific Component Software'

International Nuclear Information System (INIS)

Shasharina, Svetlana

2010-01-01

The goal of the Center for Technology for Advanced Scientific Component Software is to fundamentally changing the way scientific software is developed and used by bringing component-based software development technologies to high-performance scientific and engineering computing. The role of Tech-X work in TASCS project is to provide an outreach to accelerator physics and fusion applications by introducing TASCS tools into applications, testing tools in the applications and modifying the tools to be more usable.

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.

The PBase Scientific Workflow Provenance Repository

Directory of Open Access Journals (Sweden)

Víctor Cuevas-Vicenttín

2014-10-01

Full Text Available Scientific workflows and their supporting systems are becoming increasingly popular for compute-intensive and data-intensive scientific experiments. The advantages scientific workflows offer include rapid and easy workflow design, software and data reuse, scalable execution, sharing and collaboration, and other advantages that altogether facilitate “reproducible science”. In this context, provenance – information about the origin, context, derivation, ownership, or history of some artifact – plays a key role, since scientists are interested in examining and auditing the results of scientific experiments. However, in order to perform such analyses on scientific results as part of extended research collaborations, an adequate environment and tools are required. Concretely, the need arises for a repository that will facilitate the sharing of scientific workflows and their associated execution traces in an interoperable manner, also enabling querying and visualization. Furthermore, such functionality should be supported while taking performance and scalability into account. With this purpose in mind, we introduce PBase: a scientific workflow provenance repository implementing the ProvONE proposed standard, which extends the emerging W3C PROV standard for provenance data with workflow specific concepts. PBase is built on the Neo4j graph database, thus offering capabilities such as declarative and efficient querying. Our experiences demonstrate the power gained by supporting various types of queries for provenance data. In addition, PBase is equipped with a user friendly interface tailored for the visualization of scientific workflow provenance data, making the specification of queries and the interpretation of their results easier and more effective.

Engineering of systems for application of scientific computing in industry

OpenAIRE

Loeve, W.; Loeve,　W.

1992-01-01

Mathematics software is of growing importance for computer simulation in industrial computer aided engineering. To be applicable in industry the mathematics software and supporting software must be structured in such a way that functions and performance can be maintained easily. In the present paper a method is described for development of mathematics software in such a way that this requirement can be met.

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

Science.gov (United States)

Nishiura, Daisuke; Furuichi, Mikito; Sakaguchi, Hide

2015-09-01

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

Assessing Scientific Practices Using Machine-Learning Methods: How Closely Do They Match Clinical Interview Performance?

Science.gov (United States)

Beggrow, Elizabeth P.; Ha, Minsu; Nehm, Ross H.; Pearl, Dennis; Boone, William J.

2014-02-01

The landscape of science education is being transformed by the new Framework for Science Education (National Research Council, A framework for K-12 science education: practices, crosscutting concepts, and core ideas. The National Academies Press, Washington, DC, 2012), which emphasizes the centrality of scientific practices—such as explanation, argumentation, and communication—in science teaching, learning, and assessment. A major challenge facing the field of science education is developing assessment tools that are capable of validly and efficiently evaluating these practices. Our study examined the efficacy of a free, open-source machine-learning tool for evaluating the quality of students' written explanations of the causes of evolutionary change relative to three other approaches: (1) human-scored written explanations, (2) a multiple-choice test, and (3) clinical oral interviews. A large sample of undergraduates (n = 104) exposed to varying amounts of evolution content completed all three assessments: a clinical oral interview, a written open-response assessment, and a multiple-choice test. Rasch analysis was used to compute linear person measures and linear item measures on a single logit scale. We found that the multiple-choice test displayed poor person and item fit (mean square outfit >1.3), while both oral interview measures and computer-generated written response measures exhibited acceptable fit (average mean square outfit for interview: person 0.97, item 0.97; computer: person 1.03, item 1.06). Multiple-choice test measures were more weakly associated with interview measures (r = 0.35) than the computer-scored explanation measures (r = 0.63). Overall, Rasch analysis indicated that computer-scored written explanation measures (1) have the strongest correspondence to oral interview measures; (2) are capable of capturing students' normative scientific and naive ideas as accurately as human-scored explanations, and (3) more validly detect understanding

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

Science.gov (United States)

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

2012-09-01

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

Computational Science in Armenia (Invited Talk)

Science.gov (United States)

Marandjian, H.; Shoukourian, Yu.

This survey is devoted to the development of informatics and computer science in Armenia. The results in theoretical computer science (algebraic models, solutions to systems of general form recursive equations, the methods of coding theory, pattern recognition and image processing), constitute the theoretical basis for developing problem-solving-oriented environments. As examples can be mentioned: a synthesizer of optimized distributed recursive programs, software tools for cluster-oriented implementations of two-dimensional cellular automata, a grid-aware web interface with advanced service trading for linear algebra calculations. In the direction of solving scientific problems that require high-performance computing resources, examples of completed projects include the field of physics (parallel computing of complex quantum systems), astrophysics (Armenian virtual laboratory), biology (molecular dynamics study of human red blood cell membrane), meteorology (implementing and evaluating the Weather Research and Forecast Model for the territory of Armenia). The overview also notes that the Institute for Informatics and Automation Problems of the National Academy of Sciences of Armenia has established a scientific and educational infrastructure, uniting computing clusters of scientific and educational institutions of the country and provides the scientific community with access to local and international computational resources, that is a strong support for computational science in Armenia.

The Goal Specificity Effect on Strategy Use and Instructional Efficiency during Computer-Based Scientific Discovery Learning

Science.gov (United States)

Kunsting, Josef; Wirth, Joachim; Paas, Fred

2011-01-01

Using a computer-based scientific discovery learning environment on buoyancy in fluids we investigated the "effects of goal specificity" (nonspecific goals vs. specific goals) for two goal types (problem solving goals vs. learning goals) on "strategy use" and "instructional efficiency". Our empirical findings close an important research gap,…

Availability measurement of grid services from the perspective of a scientific computing centre

International Nuclear Information System (INIS)

Marten, H; Koenig, T

2011-01-01

The Karlsruhe Institute of Technology (KIT) is the merger of Forschungszentrum Karlsruhe and the Technical University Karlsruhe. The Steinbuch Centre for Computing (SCC) was one of the first new organizational units of KIT, combining the former Institute for Scientific Computing of Forschungszentrum Karlsruhe and the Computing Centre of the University. IT service management according to the worldwide de-facto-standard 'IT Infrastructure Library (ITIL)' was chosen by SCC as a strategic element to support the merging of the two existing computing centres located at a distance of about 10 km. The availability and reliability of IT services directly influence the customer satisfaction as well as the reputation of the service provider, and unscheduled loss of availability due to hardware or software failures may even result in severe consequences like data loss. Fault tolerant and error correcting design features are reducing the risk of IT component failures and help to improve the delivered availability. The ITIL process controlling the respective design is called Availability Management. This paper discusses Availability Management regarding grid services delivered to WLCG and provides a few elementary guidelines for availability measurements and calculations of services consisting of arbitrary numbers of components.

Large Scale Computing and Storage Requirements for Fusion Energy Sciences: Target 2017

Energy Technology Data Exchange (ETDEWEB)

Gerber, Richard

2014-05-02

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 March 2013, NERSC, DOE?s Office of Advanced Scientific Computing Research (ASCR) and DOE?s Office of Fusion Energy Sciences (FES) held a review to characterize High Performance Computing (HPC) and storage requirements for FES research through 2017. This report is the result.

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.

Final Report: Performance Engineering Research Institute

Energy Technology Data Exchange (ETDEWEB)

Mellor-Crummey, John [Rice Univ., Houston, TX (United States)

2014-10-27

This document is a final report about the work performed for cooperative agreement DE-FC02-06ER25764, the Rice University effort of Performance Engineering Research Institute (PERI). PERI was an Enabling Technologies Institute of the Scientific Discovery through Advanced Computing (SciDAC-2) program supported by the Department of Energy's Office of Science Advanced Scientific Computing Research (ASCR) program. The PERI effort at Rice University focused on (1) research and development of tools for measurement and analysis of application program performance, and (2) engagement with SciDAC-2 application teams.

Are Cloud Environments Ready for Scientific Applications?

Science.gov (United States)

Mehrotra, P.; Shackleford, K.

2011-12-01

Cloud computing environments are becoming widely available both in the commercial and government sectors. They provide flexibility to rapidly provision resources in order to meet dynamic and changing computational needs without the customers incurring capital expenses and/or requiring technical expertise. Clouds also provide reliable access to resources even though the end-user may not have in-house expertise for acquiring or operating such resources. Consolidation and pooling in a cloud environment allow organizations to achieve economies of scale in provisioning or procuring computing resources and services. Because of these and other benefits, many businesses and organizations are migrating their business applications (e.g., websites, social media, and business processes) to cloud environments-evidenced by the commercial success of offerings such as the Amazon EC2. In this paper, we focus on the feasibility of utilizing cloud environments for scientific workloads and workflows particularly of interest to NASA scientists and engineers. There is a wide spectrum of such technical computations. These applications range from small workstation-level computations to mid-range computing requiring small clusters to high-performance simulations requiring supercomputing systems with high bandwidth/low latency interconnects. Data-centric applications manage and manipulate large data sets such as satellite observational data and/or data previously produced by high-fidelity modeling and simulation computations. Most of the applications are run in batch mode with static resource requirements. However, there do exist situations that have dynamic demands, particularly ones with public-facing interfaces providing information to the general public, collaborators and partners, as well as to internal NASA users. In the last few months we have been studying the suitability of cloud environments for NASA's technical and scientific workloads. We have ported several applications to

How does the entrepreneurial orientation of scientists affect their scientific performance? Evidence from the Quadrant Model

OpenAIRE

Naohiro Shichijo; Silvia Rita Sedita; Yasunori Baba

2013-01-01

Using Stokes's (1997) "quadrant model of scientific research", this paper deals with how the entrepreneurial orientation of scientists affects their scientific performance by considering its impact on scientific production (number of publications), scientific prestige (number of forward citations), and breadth of research activities (interdisciplinarity). The results of a quantitative analysis applied to a sample of 1,957 scientific papers published by 66 scientists active in advanced materia...

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.  

Analysis of parallel computing performance of the code MCNP

International Nuclear Information System (INIS)

Wang Lei; Wang Kan; Yu Ganglin

2006-01-01

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

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

Exploring the Performance of Spark for a Scientific Use Case

Energy Technology Data Exchange (ETDEWEB)

Sehrish, Saba [Fermilab; Kowalkowski, Jim [Fermilab; Paterno, Marc [Fermilab

2016-01-01

We present an evaluation of the performance of a Spark implementation of a classification algorithm in the domain of High Energy Physics (HEP). Spark is a general engine for in-memory, large-scale data processing, and is designed for applications where similar repeated analysis is performed on the same large data sets. Classification problems are one of the most common and critical data processing tasks across many domains. Many of these data processing tasks are both computation- and data-intensive, involving complex numerical computations employing extremely large data sets. We evaluated the performance of the Spark implementation on Cori, a NERSC resource, and compared the results to an untuned MPI implementation of the same algorithm. While the Spark implementation scaled well, it is not competitive in speed to our MPI implementation, even when using significantly greater computational resources.

Amplify scientific discovery with artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Gil, Yolanda; Greaves, Mark T.; Hendler, James; Hirsch, Hyam

2014-10-10

Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automated language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.

Computing on Knights and Kepler Architectures

International Nuclear Information System (INIS)

Bortolotti, G; Caberletti, M; Ferraro, A; Giacomini, F; Manzali, M; Maron, G; Salomoni, D; Crimi, G; Zanella, M

2014-01-01

A recent trend in scientific computing is the increasingly important role of co-processors, originally built to accelerate graphics rendering, and now used for general high-performance computing. The INFN Computing On Knights and Kepler Architectures (COKA) project focuses on assessing the suitability of co-processor boards for scientific computing in a wide range of physics applications, and on studying the best programming methodologies for these systems. Here we present in a comparative way our results in porting a Lattice Boltzmann code on two state-of-the-art accelerators: the NVIDIA K20X, and the Intel Xeon-Phi. We describe our implementations, analyze results and compare with a baseline architecture adopting Intel Sandy Bridge CPUs.

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.

Computer sciences

Science.gov (United States)

Smith, Paul H.

1988-01-01

The Computer Science Program provides advanced concepts, techniques, system architectures, algorithms, and software for both space and aeronautics information sciences and computer systems. The overall goal is to provide the technical foundation within NASA for the advancement of computing technology in aerospace applications. The research program is improving the state of knowledge of fundamental aerospace computing principles and advancing computing technology in space applications such as software engineering and information extraction from data collected by scientific instruments in space. The program includes the development of special algorithms and techniques to exploit the computing power provided by high performance parallel processors and special purpose architectures. Research is being conducted in the fundamentals of data base logic and improvement techniques for producing reliable computing systems.

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.

The OSG Open Facility: an on-ramp for opportunistic scientific computing

Science.gov (United States)

Jayatilaka, B.; Levshina, T.; Sehgal, C.; Gardner, R.; Rynge, M.; Würthwein, F.

2017-10-01

The Open Science Grid (OSG) is a large, robust computing grid that started primarily as a collection of sites associated with large HEP experiments such as ATLAS, CDF, CMS, and DZero, but has evolved in recent years to a much larger user and resource platform. In addition to meeting the US LHC community’s computational needs, the OSG continues to be one of the largest providers of distributed high-throughput computing (DHTC) to researchers from a wide variety of disciplines via the OSG Open Facility. The Open Facility consists of OSG resources that are available opportunistically to users other than resource owners and their collaborators. In the past two years, the Open Facility has doubled its annual throughput to over 200 million wall hours. More than half of these resources are used by over 100 individual researchers from over 60 institutions in fields such as biology, medicine, math, economics, and many others. Over 10% of these individual users utilized in excess of 1 million computational hours each in the past year. The largest source of these cycles is temporary unused capacity at institutions affiliated with US LHC computational sites. An increasing fraction, however, comes from university HPC clusters and large national infrastructure supercomputers offering unused capacity. Such expansions have allowed the OSG to provide ample computational resources to both individual researchers and small groups as well as sizable international science collaborations such as LIGO, AMS, IceCube, and sPHENIX. Opening up access to the Fermilab FabrIc for Frontier Experiments (FIFE) project has also allowed experiments such as mu2e and NOvA to make substantial use of Open Facility resources, the former with over 40 million wall hours in a year. We present how this expansion was accomplished as well as future plans for keeping the OSG Open Facility at the forefront of enabling scientific research by way of DHTC.

The OSG Open Facility: An On-Ramp for Opportunistic Scientific Computing

Energy Technology Data Exchange (ETDEWEB)

Jayatilaka, B. [Fermilab; Levshina, T. [Fermilab; Sehgal, C. [Fermilab; Gardner, R. [Chicago U.; Rynge, M. [USC - ISI, Marina del Rey; Würthwein, F. [UC, San Diego

2017-11-22

The Open Science Grid (OSG) is a large, robust computing grid that started primarily as a collection of sites associated with large HEP experiments such as ATLAS, CDF, CMS, and DZero, but has evolved in recent years to a much larger user and resource platform. In addition to meeting the US LHC community’s computational needs, the OSG continues to be one of the largest providers of distributed high-throughput computing (DHTC) to researchers from a wide variety of disciplines via the OSG Open Facility. The Open Facility consists of OSG resources that are available opportunistically to users other than resource owners and their collaborators. In the past two years, the Open Facility has doubled its annual throughput to over 200 million wall hours. More than half of these resources are used by over 100 individual researchers from over 60 institutions in fields such as biology, medicine, math, economics, and many others. Over 10% of these individual users utilized in excess of 1 million computational hours each in the past year. The largest source of these cycles is temporary unused capacity at institutions affiliated with US LHC computational sites. An increasing fraction, however, comes from university HPC clusters and large national infrastructure supercomputers offering unused capacity. Such expansions have allowed the OSG to provide ample computational resources to both individual researchers and small groups as well as sizable international science collaborations such as LIGO, AMS, IceCube, and sPHENIX. Opening up access to the Fermilab FabrIc for Frontier Experiments (FIFE) project has also allowed experiments such as mu2e and NOvA to make substantial use of Open Facility resources, the former with over 40 million wall hours in a year. We present how this expansion was accomplished as well as future plans for keeping the OSG Open Facility at the forefront of enabling scientific research by way of DHTC.

Performing stencil computations

Energy Technology Data Exchange (ETDEWEB)

Donofrio, David

2018-01-16

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

The Julia programming language: the future of scientific computing

Science.gov (United States)

Gibson, John

2017-11-01

Julia is an innovative new open-source programming language for high-level, high-performance numerical computing. Julia combines the general-purpose breadth and extensibility of Python, the ease-of-use and numeric focus of Matlab, the speed of C and Fortran, and the metaprogramming power of Lisp. Julia uses type inference and just-in-time compilation to compile high-level user code to machine code on the fly. A rich set of numeric types and extensive numerical libraries are built-in. As a result, Julia is competitive with Matlab for interactive graphical exploration and with C and Fortran for high-performance computing. This talk interactively demonstrates Julia's numerical features and benchmarks Julia against C, C++, Fortran, Matlab, and Python on a spectral time-stepping algorithm for a 1d nonlinear partial differential equation. The Julia code is nearly as compact as Matlab and nearly as fast as Fortran. This material is based upon work supported by the National Science Foundation under Grant No. 1554149.

Cloud Computing for Complex Performance Codes.

Energy Technology Data Exchange (ETDEWEB)

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

2017-02-01

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

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

An Adaptive Middleware for Improved Computational Performance

DEFF Research Database (Denmark)

Bonnichsen, Lars Frydendal

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

Crosscut report: Exascale Requirements Reviews, March 9–10, 2017 – Tysons Corner, Virginia. An Office of Science review sponsored by: Advanced Scientific Computing Research, Basic Energy Sciences, Biological and Environmental Research, Fusion Energy Sciences, High Energy Physics, Nuclear Physics

Energy Technology Data Exchange (ETDEWEB)

Gerber, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Hack, James [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Riley, Katherine [Argonne National Lab., IL (United States). Argonne Leadership Computing Facility (ALCF); Antypas, Katie [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Coffey, Richard [Argonne National Lab. (ANL), Argonne, IL (United States). Argonne Leadership Computing Facility (ALCF); Dart, Eli [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). ESnet; Straatsma, Tjerk [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Wells, Jack [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Bard, Deborah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Dosanjh, Sudip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Monga, Inder [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). ESnet; Papka, Michael E. [Argonne National Lab. (ANL), Argonne, IL (United States). Argonne Leadership Computing Facility; Rotman, Lauren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). ESnet

2018-01-22

The mission of the U.S. Department of Energy Office of Science (DOE SC) is the delivery of scientific discoveries and major scientific tools to transform our understanding of nature and to advance the energy, economic, and national security missions of the United States. To achieve these goals in today’s world requires investments in not only the traditional scientific endeavors of theory and experiment, but also in computational science and the facilities that support large-scale simulation and data analysis. The Advanced Scientific Computing Research (ASCR) program addresses these challenges in the Office of Science. ASCR’s mission is to discover, develop, and deploy computational and networking capabilities to analyze, model, simulate, and predict complex phenomena important to DOE. ASCR supports research in computational science, three high-performance computing (HPC) facilities — the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory and Leadership Computing Facilities at Argonne (ALCF) and Oak Ridge (OLCF) National Laboratories — and the Energy Sciences Network (ESnet) at Berkeley Lab. ASCR is guided by science needs as it develops research programs, computers, and networks at the leading edge of technologies. As we approach the era of exascale computing, technology changes are creating challenges for science programs in SC for those who need to use high performance computing and data systems effectively. Numerous significant modifications to today’s tools and techniques will be needed to realize the full potential of emerging computing systems and other novel computing architectures. To assess these needs and challenges, ASCR held a series of Exascale Requirements Reviews in 2015–2017, one with each of the six SC program offices,1 and a subsequent Crosscut Review that sought to integrate the findings from each. Participants at the reviews were drawn from the communities of leading domain

2004 Annual Scientific Conference. Program and Abstracts

International Nuclear Information System (INIS)

Barborica, Andrei; Bulinski, Mircea; Stefan, Sabina

2005-01-01

As consequence of a long experience in educational as well as research field the Physics Department of the Bucharest University is offering high-standard undergraduate and graduate programs of higher education in physical sciences. The long-term strategy adopted by the faculty was focused on developing scientific research in modern topics of theoretical, experimental and applied physics as well as in inter-disciplinary fields as biophysics, medical physics, physics and protection of environment, physics-computer science. Following this strategy the Faculty of Physics has diversified the research activity, developing new research laboratories and encouraging the academic community to approach modern and competitive research projects. Every year the Physics Department of the University of Bucharest organizes the 'Annual Scientific Conference' to present the most interesting scientific results, obtained within the department. This 2004 scientific session is opened also to the interested physics researchers from other institutes and universities in the country. This scientific event represents a recognition and a continuation of the prestigious tradition of physics research performed within University. The scientific research in the Physics Department is performed in groups and research centers, the terminal year undergraduate students and graduate students being involved in a high extent in the research works. There are 5 research centers with the status of Center of excellence in research. The long-term strategy adopted by the faculty was focused on developing the scientific research in modern topics of theoretical, experimental and applied physics, as well as in inter-disciplinary fields as biophysics, medical physics, physics and protection of the environment, physics - computer science. Following this strategy, the Faculty of Physics has diversified the research activity, developing new research laboratories and encouraging the academic community to perform modern

2003 Annual Scientific Conference. Program and Abstracts

International Nuclear Information System (INIS)

Barborica, Andrei; Bulinski, Mircea

2003-01-01

As consequence of a long experience in educational as well as research field the Physics Department of the Bucharest University is offering high-standard undergraduate and graduate programs of higher education in physical sciences. The long-term strategy adopted by the faculty was focused on developing scientific research in modern topics of theoretical, experimental and applied physics as well as in inter-disciplinary fields as biophysics, medical physics, physics and protection of environment, physics-computer science. Following this strategy the Faculty of Physics has diversified the research activity, developing new research laboratories and encouraging the academic community to approach modern and competitive research projects. Every year the Physics Department of the University of Bucharest organizes the 'Annual Scientific Conference' to present the most interesting scientific results, obtained within the department. This scientific session is opened also to the interested physics researchers from other institutes and universities in the country. This scientific event represents a recognition and a continuation of the prestigious tradition of physics research performed within University. The scientific research in the Physics Department is performed in groups and research centers, the terminal year undergraduate students and graduate students being involved in a high extent in the research works. There are 5 research centers with the status of Center of excellence in research. The long-term strategy adopted by the faculty was focused on developing the scientific research in modern topics of theoretical, experimental and applied physics, as well as in inter-disciplinary fields as biophysics, medical physics, physics and protection of the environment, physics - computer science. Following this strategy, the Faculty of Physics has diversified the research activity, developing new research laboratories and encouraging the academic community to perform modern and

2002 Annual Scientific Conference. Program and Abstracts

International Nuclear Information System (INIS)

Barborica, Andrei; Bulinski, Mircea; Dinca, Mihai P.

2002-01-01

As consequence of a long experience in educational as well as research field the Physics Department of the Bucharest University is offering high-standard undergraduate and graduate programs of higher education in physical sciences. The long-term strategy adopted by the faculty was focused on developing scientific research in modern topics of theoretical, experimental and applied physics as well as in inter-disciplinary fields as biophysics, medical physics, physics and protection of environment, physics-computer science. Following this strategy the Faculty of Physics has diversified the research activity, developing new research laboratories and encouraging the academic community to approach modern and competitive research projects. Every year the Physics Department of the University of Bucharest organizes the 'Annual Scientific Conference' to present the most interesting scientific results, obtained within the department. This scientific session is opened also to the interested physics researchers from other institutes and universities in the country. This scientific event represents a recognition and a continuation of the prestigious tradition of physics research performed within University. The scientific research in the Physics Department is performed in groups and research centers, the terminal year undergraduate students and graduate students being involved in a high extent in the research works. There are 5 research centers with the status of Center of excellence in research. The long-term strategy adopted by the faculty was focused on developing the scientific research in modern topics of theoretical, experimental and applied physics, as well as in inter-disciplinary fields as biophysics, medical physics, physics and protection of the environment, physics - computer science. Following this strategy, the Faculty of Physics has diversified the research activity, developing new research laboratories and encouraging the academic community to perform modern and

SciSpark's SRDD : A Scientific Resilient Distributed Dataset for Multidimensional Data

Science.gov (United States)

Palamuttam, R. S.; Wilson, B. D.; Mogrovejo, R. M.; Whitehall, K. D.; Mattmann, C. A.; McGibbney, L. J.; Ramirez, P.

2015-12-01

Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We have developed SciSpark, a robust Big Data framework, that extends ApacheTM Spark for scaling scientific computations. Apache Spark improves the map-reduce implementation in ApacheTM Hadoop for parallel computing on a cluster, by emphasizing in-memory computation, "spilling" to disk only as needed, and relying on lazy evaluation. Central to Spark is the Resilient Distributed Dataset (RDD), an in-memory distributed data structure that extends the functional paradigm provided by the Scala programming language. However, RDDs are ideal for tabular or unstructured data, and not for highly dimensional data. The SciSpark project introduces the Scientific Resilient Distributed Dataset (sRDD), a distributed-computing array structure which supports iterative scientific algorithms for multidimensional data. SciSpark processes data stored in NetCDF and HDF files by partitioning them across time or space and distributing the partitions among a cluster of compute nodes. We show usability and extensibility of SciSpark by implementing distributed algorithms for geospatial operations on large collections of multi-dimensional grids. In particular we address the problem of scaling an automated method for finding Mesoscale Convective Complexes. SciSpark provides a tensor interface to support the pluggability of different matrix libraries. We evaluate performance of the various matrix libraries in distributed pipelines, such as Nd4jTM and BreezeTM. We detail the architecture and design of SciSpark, our efforts to integrate climate science algorithms, parallel ingest and partitioning (sharding) of A-Train satellite observations from model grids. These

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

Good enough practices in scientific computing.

Science.gov (United States)

Wilson, Greg; Bryan, Jennifer; Cranston, Karen; Kitzes, Justin; Nederbragt, Lex; Teal, Tracy K

2017-06-01

Computers are now essential in all branches of science, but most researchers are never taught the equivalent of basic lab skills for research computing. As a result, data can get lost, analyses can take much longer than necessary, and researchers are limited in how effectively they can work with software and data. Computing workflows need to follow the same practices as lab projects and notebooks, with organized data, documented steps, and the project structured for reproducibility, but researchers new to computing often don't know where to start. This paper presents a set of good computing practices that every researcher can adopt, regardless of their current level of computational skill. These practices, which encompass data management, programming, collaborating with colleagues, organizing projects, tracking work, and writing manuscripts, are drawn from a wide variety of published sources from our daily lives and from our work with volunteer organizations that have delivered workshops to over 11,000 people since 2010.

PS3 CELL Development for Scientific Computation and Research

Science.gov (United States)

Christiansen, M.; Sevre, E.; Wang, S. M.; Yuen, D. A.; Liu, S.; Lyness, M. D.; Broten, M.

2007-12-01

The Cell processor is one of the most powerful processors on the market, and researchers in the earth sciences may find its parallel architecture to be very useful. A cell processor, with 7 cores, can easily be obtained for experimentation by purchasing a PlayStation 3 (PS3) and installing linux and the IBM SDK. Each core of the PS3 is capable of 25 GFLOPS giving a potential limit of 150 GFLOPS when using all 6 SPUs (synergistic processing units) by using vectorized algorithms. We have used the Cell's computational power to create a program which takes simulated tsunami datasets, parses them, and returns a colorized height field image using ray casting techniques. As expected, the time required to create an image is inversely proportional to the number of SPUs used. We believe that this trend will continue when multiple PS3s are chained using OpenMP functionality and are in the process of researching this. By using the Cell to visualize tsunami data, we have found that its greatest feature is its power. This fact entwines well with the needs of the scientific community where the limiting factor is time. Any algorithm, such as the heat equation, that can be subdivided into multiple parts can take advantage of the PS3 Cell's ability to split the computations across the 6 SPUs reducing required run time by one sixth. Further vectorization of the code can allow for 4 simultanious floating point operations by using the SIMD (single instruction multiple data) capabilities of the SPU increasing efficiency 24 times.

Using Cloud-Computing Applications to Support Collaborative Scientific Inquiry: Examining Pre-Service Teachers' Perceived Barriers to Integration

Science.gov (United States)

Donna, Joel D.; Miller, Brant G.

2013-01-01

Technology plays a crucial role in facilitating collaboration within the scientific community. Cloud-computing applications, such as Google Drive, can be used to model such collaboration and support inquiry within the secondary science classroom. Little is known about pre-service teachers' beliefs related to the envisioned use of collaborative,…

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)

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.

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

Science.gov (United States)

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

2017-04-01

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

Computer-supported analysis of scientific measurements

NARCIS (Netherlands)

de Jong, Hidde

1998-01-01

In the past decade, large-scale databases and knowledge bases have become available to researchers working in a range of scientific disciplines. In many cases these databases and knowledge bases contain measurements of properties of physical objects which have been obtained in experiments or at

2005 Annual Scientific Conference. Program and Abstracts

International Nuclear Information System (INIS)

Barborica, Andrei; Bulinski, Mircea; Stefan, Sabina

2005-01-01

Every year the Physics Department of the University of Bucharest organizes the 'Annual Scientific Conference' to present the most interesting scientific results, obtained within the department. This scientific session is opened also to the interested physics researchers from other institutes and universities in the country. This scientific event represents a recognition and a continuation of the prestigious tradition of physics research performed within University. The scientific research in the Physics Department is performed in groups and research centers, the terminal year undergraduate students and graduate students being involved in a high extent in the research works. There are 5 research centers with the status of Center of excellence in research. The long-term strategy adopted by the faculty was focused on developing the scientific research in modern topics of theoretical, experimental and applied physics, as well as in inter-disciplinary fields as biophysics, medical physics, physics and protection of the environment, physics - computer science. Following this strategy, the Faculty of Physics has diversified the research activity, developing new research laboratories and encouraging the academic community to perform modern and competitive research projects. The Faculty of Physics is a partner in many common research programs with prestigious foreign universities and institutes. The 2005 session covered the following 8 topics: 1. Atmosphere and Earth Science; Environment Protection (21 papers); 2. Atomic and Molecular Physics; Astrophysics (12 papers); 3. Electricity and Biophysics (19 papers); 4. Nuclear and Elementary Particles Physics (17 papers); 5. Optics, Spectroscopy, Plasma and Lasers (19 papers); 6. Polymer Physics (10 papers); 7. Solid State Physics and Materials Science (10 papers); 8. Theoretical Physics and Applied Mathematics Seminar (12 papers)

COMPUTER-ASSISTED ACCOUNTING

Directory of Open Access Journals (Sweden)

SORIN-CIPRIAN TEIUŞAN

2009-01-01

Full Text Available What is computer-assisted accounting? Where is the place and what is the role of the computer in the financial-accounting activity? What is the position and importance of the computer in the accountant’s activity? All these are questions that require scientific research in order to find the answers. The paper approaches the issue of the support granted to the accountant to organize and manage the accounting activity by the computer. Starting from the notions of accounting and computer, the concept of computer-assisted accounting is introduced, it has a general character and it refers to the accounting performed with the help of the computer or using the computer to automate the procedures performed by the person who is doing the accounting activity; this is a concept used to define the computer applications of the accounting activity. The arguments regarding the use of the computer to assist accounting targets the accounting informatization, the automating of the financial-accounting activities and the endowment with modern technology of the contemporary accounting.

Designing a High Performance Parallel Personal Cluster

OpenAIRE

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

2016-01-01

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

Scientific data analysis on data-parallel platforms.

Energy Technology Data Exchange (ETDEWEB)

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

2010-09-01

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

Certification of version 1.2 of the PORFLO-3 code for the WHC scientific and engineering computational center

International Nuclear Information System (INIS)

Kline, N.W.

1994-01-01

Version 1.2 of the PORFLO-3 Code has migrated from the Hanford Cray computer to workstations in the WHC Scientific and Engineering Computational Center. The workstation-based configuration and acceptance testing are inherited from the CRAY-based configuration. The purpose of this report is to document differences in the new configuration as compared to the parent Cray configuration, and summarize some of the acceptance test results which have shown that the migrated code is functioning correctly in the new environment

A document-driven method for certifying scientific computing software for use in nuclear safety analysis

International Nuclear Information System (INIS)

Smith, W. Spencer; Koothoor, Mimitha

2016-01-01

This paper presents a documentation and development method to facilitate the certification of scientific computing software used in the safety analysis of nuclear facilities. To study the problems faced during quality assurance and certification activities, a case study was performed on legacy software used for thermal analysis of a fuel pin in a nuclear reactor. Although no errors were uncovered in the code, 27 issues of incompleteness and inconsistency were found with the documentation. This work proposes that software documentation follow a rational process, which includes a software requirements specification following a template that is reusable, maintainable, and understandable. To develop the design and implementation, this paper suggests literate programming as an alternative to traditional structured programming. Literate programming allows for documenting of numerical algorithms and code together in what is termed the literate programmer's manual. This manual is developed with explicit traceability to the software requirements specification. The traceability between the theory, numerical algorithms, and implementation facilitates achieving completeness and consistency, as well as simplifies the process of verification and the associated certification

A document-driven method for certifying scientific computing software for use in nuclear safety analysis

Energy Technology Data Exchange (ETDEWEB)

Smith, W. Spencer; Koothoor, Mimitha [Computing and Software Department, McMaster University, Hamilton (Canada)

2016-04-15

This paper presents a documentation and development method to facilitate the certification of scientific computing software used in the safety analysis of nuclear facilities. To study the problems faced during quality assurance and certification activities, a case study was performed on legacy software used for thermal analysis of a fuel pin in a nuclear reactor. Although no errors were uncovered in the code, 27 issues of incompleteness and inconsistency were found with the documentation. This work proposes that software documentation follow a rational process, which includes a software requirements specification following a template that is reusable, maintainable, and understandable. To develop the design and implementation, this paper suggests literate programming as an alternative to traditional structured programming. Literate programming allows for documenting of numerical algorithms and code together in what is termed the literate programmer's manual. This manual is developed with explicit traceability to the software requirements specification. The traceability between the theory, numerical algorithms, and implementation facilitates achieving completeness and consistency, as well as simplifies the process of verification and the associated certification.

Expert opinions and scientific evidence for colonoscopy key performance indicators.

Science.gov (United States)

Rees, Colin J; Bevan, Roisin; Zimmermann-Fraedrich, Katharina; Rutter, Matthew D; Rex, Douglas; Dekker, Evelien; Ponchon, Thierry; Bretthauer, Michael; Regula, Jaroslaw; Saunders, Brian; Hassan, Cesare; Bourke, Michael J; Rösch, Thomas

2016-12-01

Colonoscopy is a widely performed procedure with procedural volumes increasing annually throughout the world. Many procedures are now performed as part of colorectal cancer screening programmes. Colonoscopy should be of high quality and measures of this quality should be evidence based. New UK key performance indicators and quality assurance standards have been developed by a working group with consensus agreement on each standard reached. This paper reviews the scientific basis for each of the quality measures published in the UK standards. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Impact of configuration management system of computer center on support of scientific projects throughout their lifecycle

International Nuclear Information System (INIS)

Bogdanov, A.V.; Yuzhanin, N.V.; Zolotarev, V.I.; Ezhakova, T.R.

2017-01-01

In this article the problem of scientific projects support throughout their lifecycle in the computer center is considered in every aspect of support. Configuration Management system plays a connecting role in processes related to the provision and support of services of a computer center. In view of strong integration of IT infrastructure components with the use of virtualization, control of infrastructure becomes even more critical to the support of research projects, which means higher requirements for the Configuration Management system. For every aspect of research projects support, the influence of the Configuration Management system is reviewed and development of the corresponding elements of the system is described in the present paper.

Misleading Performance Claims in Parallel Computations

Energy Technology Data Exchange (ETDEWEB)

Bailey, David H.

2009-05-29

In a previous humorous note entitled 'Twelve Ways to Fool the Masses,' I outlined twelve common ways in which performance figures for technical computer systems can be distorted. In this paper and accompanying conference talk, I give a reprise of these twelve 'methods' and give some actual examples that have appeared in peer-reviewed literature in years past. I then propose guidelines for reporting performance, the adoption of which would raise the level of professionalism and reduce the level of confusion, not only in the world of device simulation but also in the larger arena of technical computing.

Contributing to the design of run-time systems dedicated to high performance computing; Contribution a l'elaboration d'environnements de programmation dedies au calcul scientifique hautes performances

Energy Technology Data Exchange (ETDEWEB)

Perache, M

2006-10-15

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)

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.

The Magellan Final Report on Cloud Computing

Energy Technology Data Exchange (ETDEWEB)

,; Coghlan, Susan; Yelick, Katherine

2011-12-21

The goal of Magellan, a project funded through the U.S. Department of Energy (DOE) Office of Advanced Scientific Computing Research (ASCR), was to investigate the potential role of cloud computing in addressing the computing needs for the DOE Office of Science (SC), particularly related to serving the needs of mid- range computing and future data-intensive computing workloads. A set of research questions was formed to probe various aspects of cloud computing from performance, usability, and cost. To address these questions, a distributed testbed infrastructure was deployed at the Argonne Leadership Computing Facility (ALCF) and the National Energy Research Scientific Computing Center (NERSC). The testbed was designed to be flexible and capable enough to explore a variety of computing models and hardware design points in order to understand the impact for various scientific applications. During the project, the testbed also served as a valuable resource to application scientists. Applications from a diverse set of projects such as MG-RAST (a metagenomics analysis server), the Joint Genome Institute, the STAR experiment at the Relativistic Heavy Ion Collider, and the Laser Interferometer Gravitational Wave Observatory (LIGO), were used by the Magellan project for benchmarking within the cloud, but the project teams were also able to accomplish important production science utilizing the Magellan cloud resources.

Challenges and opportunities of cloud computing for atmospheric sciences

Science.gov (United States)

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

2016-04-01

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

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

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.

Sudden Cardiac Risk Stratification with Electrocardiographic Indices - A Review on Computational Processing, Technology Transfer, and Scientific Evidence

Directory of Open Access Journals (Sweden)

Francisco Javier eGimeno-Blanes

2016-03-01

Full Text Available Great effort has been devoted in recent years to the development of sudden cardiac risk predictors as a function of electric cardiac signals, mainly obtained from the electrocardiogram (ECG analysis. But these prediction techniques are still seldom used in clinical practice, partly due to its limited diagnostic accuracy and to the lack of consensus about the appropriate computational signal processing implementation. This paper addresses a three-fold approach, based on ECG indexes, to structure this review on sudden cardiac risk stratification. First, throughout the computational techniques that had been widely proposed for obtaining these indexes in technical literature. Second, over the scientific evidence, that although is supported by observational clinical studies, they are not always representative enough. And third, via the limited technology transfer of academy-accepted algorithms, requiring further meditation for future systems. We focus on three families of ECG derived indexes which are tackled from the aforementioned viewpoints, namely, heart rate turbulence, heart rate variability, and T-wave alternans. In terms of computational algorithms, we still need clearer scientific evidence, standardizing, and benchmarking, siting on advanced algorithms applied over large and representative datasets. New scenarios like electronic health recordings, big data, long-term monitoring, and cloud databases, will eventually open new frameworks to foresee suitable new paradigms in the near future.

Computational Methods and Function Theory

CERN Document Server

Saff, Edward; Salinas, Luis; Varga, Richard

1990-01-01

The volume is devoted to the interaction of modern scientific computation and classical function theory. Many problems in pure and more applied function theory can be tackled using modern computing facilities: numerically as well as in the sense of computer algebra. On the other hand, computer algorithms are often based on complex function theory, and dedicated research on their theoretical foundations can lead to great enhancements in performance. The contributions - original research articles, a survey and a collection of problems - cover a broad range of such problems.

Computer task performance by subjects with Duchenne muscular dystrophy.

Science.gov (United States)

Malheiros, Silvia Regina Pinheiro; da Silva, Talita Dias; Favero, Francis Meire; de Abreu, Luiz Carlos; Fregni, Felipe; Ribeiro, Denise Cardoso; de Mello Monteiro, Carlos Bandeira

2016-01-01

Two specific objectives were established to quantify computer task performance among people with Duchenne muscular dystrophy (DMD). First, we compared simple computational task performance between subjects with DMD and age-matched typically developing (TD) subjects. Second, we examined correlations between the ability of subjects with DMD to learn the computational task and their motor functionality, age, and initial task performance. The study included 84 individuals (42 with DMD, mean age of 18±5.5 years, and 42 age-matched controls). They executed a computer maze task; all participants performed the acquisition (20 attempts) and retention (five attempts) phases, repeating the same maze. A different maze was used to verify transfer performance (five attempts). The Motor Function Measure Scale was applied, and the results were compared with maze task performance. In the acquisition phase, a significant decrease was found in movement time (MT) between the first and last acquisition block, but only for the DMD group. For the DMD group, MT during transfer was shorter than during the first acquisition block, indicating improvement from the first acquisition block to transfer. In addition, the TD group showed shorter MT than the DMD group across the study. DMD participants improved their performance after practicing a computational task; however, the difference in MT was present in all attempts among DMD and control subjects. Computational task improvement was positively influenced by the initial performance of individuals with DMD. In turn, the initial performance was influenced by their distal functionality but not their age or overall functionality.

Human performance models for computer-aided engineering

Science.gov (United States)

Elkind, Jerome I. (Editor); Card, Stuart K. (Editor); Hochberg, Julian (Editor); Huey, Beverly Messick (Editor)

1989-01-01

This report discusses a topic important to the field of computational human factors: models of human performance and their use in computer-based engineering facilities for the design of complex systems. It focuses on a particular human factors design problem -- the design of cockpit systems for advanced helicopters -- and on a particular aspect of human performance -- vision and related cognitive functions. By focusing in this way, the authors were able to address the selected topics in some depth and develop findings and recommendations that they believe have application to many other aspects of human performance and to other design domains.

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.

Performative Computation-aided Design Optimization

Directory of Open Access Journals (Sweden)

Ming Tang

2012-12-01

Full Text Available This article discusses a collaborative research and teaching project between the University of Cincinnati, Perkins+Will’s Tech Lab, and the University of North Carolina Greensboro. The primary investigation focuses on the simulation, optimization, and generation of architectural designs using performance-based computational design approaches. The projects examine various design methods, including relationships between building form, performance and the use of proprietary software tools for parametric design.

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.

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

Impact of configuration management system of computer center on support of scientific projects throughout their lifecycle

Science.gov (United States)

Bogdanov, A. V.; Iuzhanin, N. V.; Zolotarev, V. I.; Ezhakova, T. R.

2017-12-01

In this article the problem of scientific projects support throughout their lifecycle in the computer center is considered in every aspect of support. Configuration Management system plays a connecting role in processes related to the provision and support of services of a computer center. In view of strong integration of IT infrastructure components with the use of virtualization, control of infrastructure becomes even more critical to the support of research projects, which means higher requirements for the Configuration Management system. For every aspect of research projects support, the influence of the Configuration Management system is being reviewed and development of the corresponding elements of the system is being described in the present paper.

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

Molecular Science Computing: 2010 Greenbook

Energy Technology Data Exchange (ETDEWEB)

De Jong, Wibe A.; Cowley, David E.; Dunning, Thom H.; Vorpagel, Erich R.

2010-04-02

This 2010 Greenbook outlines the science drivers for performing integrated computational environmental molecular research at EMSL and defines the next-generation HPC capabilities that must be developed at the MSC to address this critical research. The EMSL MSC Science Panel used EMSL’s vision and science focus and white papers from current and potential future EMSL scientific user communities to define the scientific direction and resulting HPC resource requirements presented in this 2010 Greenbook.

Improving the Efficiency of the Nodal Integral Method With the Portable, Extensible Tool-kit for Scientific Computation

International Nuclear Information System (INIS)

Toreja, Allen J.; Uddin, Rizwan

2002-01-01

An existing implementation of the nodal integral method for the time-dependent convection-diffusion equation is modified to incorporate various PETSc (Portable, Extensible Tool-kit for Scientific Computation) solver and pre-conditioner routines. In the modified implementation, the default iterative Gauss-Seidel solver is replaced with one of the following PETSc iterative linear solver routines: Generalized Minimal Residuals, Stabilized Bi-conjugate Gradients, or Transpose-Free Quasi-Minimal Residuals. For each solver, a Jacobi or a Successive Over-Relaxation pre-conditioner is used. Two sample problems, one with a low Peclet number and one with a high Peclet number, are solved using the new implementation. In all the cases tested, the new implementation with the PETSc solver routines outperforms the original Gauss-Seidel implementation. Moreover, the PETSc Stabilized Bi-conjugate Gradients routine performs the best on the two sample problems leading to CPU times that are less than half the CPU times of the original implementation. (authors)

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...

Scientific Grand Challenges: Discovery In Basic Energy Sciences: The Role of Computing at the Extreme Scale - August 13-15, 2009, Washington, D.C.

Energy Technology Data Exchange (ETDEWEB)

Galli, Giulia [Univ. of California, Davis, CA (United States). Workshop Chair; Dunning, Thom [Univ. of Illinois, Urbana, IL (United States). Workshop Chair

2009-08-13

The U.S. Department of Energy’s (DOE) Office of Basic Energy Sciences (BES) and Office of Advanced Scientific Computing Research (ASCR) workshop in August 2009 on extreme-scale computing provided a forum for more than 130 researchers to explore the needs and opportunities that will arise due to expected dramatic advances in computing power over the next decade. This scientific community firmly believes that the development of advanced theoretical tools within chemistry, physics, and materials science—combined with the development of efficient computational techniques and algorithms—has the potential to revolutionize the discovery process for materials and molecules with desirable properties. Doing so is necessary to meet the energy and environmental challenges of the 21^st century as described in various DOE BES Basic Research Needs reports. Furthermore, computational modeling and simulation are a crucial complement to experimental studies, particularly when quantum mechanical processes controlling energy production, transformations, and storage are not directly observable and/or controllable. Many processes related to the Earth’s climate and subsurface need better modeling capabilities at the molecular level, which will be enabled by extreme-scale computing.

Neuromorphic Computing, Architectures, Models, and Applications. A Beyond-CMOS Approach to Future Computing, June 29-July 1, 2016, Oak Ridge, TN

Energy Technology Data Exchange (ETDEWEB)

Potok, Thomas [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Schuman, Catherine [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Patton, Robert [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hylton, Todd [Brain Corporation, San Diego, CA (United States); Li, Hai [Univ. of Pittsburgh, PA (United States); Pino, Robinson [US Dept. of Energy, Washington, DC (United States)

2016-12-31

The White House and Department of Energy have been instrumental in driving the development of a neuromorphic computing program to help the United States continue its lead in basic research into (1) Beyond Exascale—high performance computing beyond Moore’s Law and von Neumann architectures, (2) Scientific Discovery—new paradigms for understanding increasingly large and complex scientific data, and (3) Emerging Architectures—assessing the potential of neuromorphic and quantum architectures. Neuromorphic computing spans a broad range of scientific disciplines from materials science to devices, to computer science, to neuroscience, all of which are required to solve the neuromorphic computing grand challenge. In our workshop we focus on the computer science aspects, specifically from a neuromorphic device through an application. Neuromorphic devices present a very different paradigm to the computer science community from traditional von Neumann architectures, which raises six major questions about building a neuromorphic application from the device level. We used these fundamental questions to organize the workshop program and to direct the workshop panels and discussions. From the white papers, presentations, panels, and discussions, there emerged several recommendations on how to proceed.

Berkeley Lab Computing Sciences: Accelerating Scientific Discovery

International Nuclear Information System (INIS)

Hules, John A.

2008-01-01

Scientists today rely on advances in computer science, mathematics, and computational science, as well as large-scale computing and networking facilities, to increase our understanding of ourselves, our planet, and our universe. Berkeley Lab's Computing Sciences organization researches, develops, and deploys new tools and technologies to meet these needs and to advance research in such areas as global climate change, combustion, fusion energy, nanotechnology, biology, and astrophysics

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.

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.

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.

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.

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

Performance analysis and acceleration of explicit integration for large kinetic networks using batched GPU computations

Energy Technology Data Exchange (ETDEWEB)

Shyles, Daniel [University of Tennessee (UT); Dongarra, Jack J. [University of Tennessee, Knoxville (UTK); Guidry, Mike W. [ORNL; Tomov, Stanimire Z. [ORNL; Billings, Jay Jay [ORNL; Brock, Benjamin A. [ORNL; Haidar Ahmad, Azzam A. [ORNL

2016-09-01

Abstract—We demonstrate the systematic implementation of recently-developed fast explicit kinetic integration algorithms that solve efficiently N coupled ordinary differential equations (subject to initial conditions) on modern GPUs. We take representative test cases (Type Ia supernova explosions) and demonstrate two or more orders of magnitude increase in efficiency for solving such systems (of realistic thermonuclear networks coupled to fluid dynamics). This implies that important coupled, multiphysics problems in various scientific and technical disciplines that were intractable, or could be simulated only with highly schematic kinetic networks, are now computationally feasible. As examples of such applications we present the computational techniques developed for our ongoing deployment of these new methods on modern GPU accelerators. We show that similarly to many other scientific applications, ranging from national security to medical advances, the computation can be split into many independent computational tasks, each of relatively small-size. As the size of each individual task does not provide sufficient parallelism for the underlying hardware, especially for accelerators, these tasks must be computed concurrently as a single routine, that we call batched routine, in order to saturate the hardware with enough work.

Contributing to the design of run-time systems dedicated to high performance computing; Contribution a l'elaboration d'environnements de programmation dedies au calcul scientifique hautes performances

Energy Technology Data Exchange (ETDEWEB)

Perache, M

2006-10-15

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)

Toward executable scientific publications

NARCIS (Netherlands)

Strijkers, R.J.; Cushing, R.; Vasyunin, D.; Laat, C. de; Belloum, A.S.Z.; Meijer, R.J.

2011-01-01

Reproducibility of experiments is considered as one of the main principles of the scientific method. Recent developments in data and computation intensive science, i.e. e-Science, and state of the art in Cloud computing provide the necessary components to preserve data sets and re-run code and

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.

National Laboratory for Advanced Scientific Visualization at UNAM - Mexico

Science.gov (United States)

Manea, Marina; Constantin Manea, Vlad; Varela, Alfredo

2016-04-01

In 2015, the National Autonomous University of Mexico (UNAM) joined the family of Universities and Research Centers where advanced visualization and computing plays a key role to promote and advance missions in research, education, community outreach, as well as business-oriented consulting. This initiative provides access to a great variety of advanced hardware and software resources and offers a range of consulting services that spans a variety of areas related to scientific visualization, among which are: neuroanatomy, embryonic development, genome related studies, geosciences, geography, physics and mathematics related disciplines. The National Laboratory for Advanced Scientific Visualization delivers services through three main infrastructure environments: the 3D fully immersive display system Cave, the high resolution parallel visualization system Powerwall, the high resolution spherical displays Earth Simulator. The entire visualization infrastructure is interconnected to a high-performance-computing-cluster (HPCC) called ADA in honor to Ada Lovelace, considered to be the first computer programmer. The Cave is an extra large 3.6m wide room with projected images on the front, left and right, as well as floor walls. Specialized crystal eyes LCD-shutter glasses provide a strong stereo depth perception, and a variety of tracking devices allow software to track the position of a user's hand, head and wand. The Powerwall is designed to bring large amounts of complex data together through parallel computing for team interaction and collaboration. This system is composed by 24 (6x4) high-resolution ultra-thin (2 mm) bezel monitors connected to a high-performance GPU cluster. The Earth Simulator is a large (60") high-resolution spherical display used for global-scale data visualization like geophysical, meteorological, climate and ecology data. The HPCC-ADA, is a 1000+ computing core system, which offers parallel computing resources to applications that requires

Scientific performances of the XAA1.2 front-end chip for silicon microstrip detectors

International Nuclear Information System (INIS)

Del Monte, Ettore; Soffitta, Paolo; Morelli, Ennio; Pacciani, Luigi; Porrovecchio, Geiland; Rubini, Alda; Uberti, Olga; Costa, Enrico; Di Persio, Giuseppe; Donnarumma, Immacolata; Evangelista, Yuri; Feroci, Marco; Lazzarotto, Francesco; Mastropietro, Marcello; Rapisarda, Massimo

2007-01-01

The XAA1.2 is a custom ASIC chip for silicon microstrip detectors adapted by Ideas for the SuperAGILE instrument on board the AGILE space mission. The chip is equipped with 128 input channels, each one containing a charge preamplifier, shaper, peak detector and stretcher. The most important features of the ASIC are the extended linearity, low noise and low power consumption. The XAA1.2 underwent extensive laboratory testing in order to study its commandability and functionality and evaluate its scientific performances. In this paper we describe the XAA1.2 features, report the laboratory measurements and discuss the results emphasizing the scientific performances in the context of the SuperAGILE front-end electronics

Performance modeling of hybrid MPI/OpenMP scientific applications on large-scale multicore supercomputers

KAUST Repository

Wu, Xingfu; Taylor, Valerie

2013-01-01

In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore supercomputers: IBM POWER4, POWER5+ and BlueGene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks and Intel's MPI benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore supercomputers because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyrokinetic Toroidal Code (GTC) in magnetic fusion to validate our performance model of the hybrid application on these multicore supercomputers. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore supercomputers. © 2013 Elsevier Inc.

Performance modeling of hybrid MPI/OpenMP scientific applications on large-scale multicore supercomputers

KAUST Repository

Wu, Xingfu

2013-12-01

In this paper, we present a performance modeling framework based on memory bandwidth contention time and a parameterized communication model to predict the performance of OpenMP, MPI and hybrid applications with weak scaling on three large-scale multicore supercomputers: IBM POWER4, POWER5+ and BlueGene/P, and analyze the performance of these MPI, OpenMP and hybrid applications. We use STREAM memory benchmarks and Intel\\'s MPI benchmarks to provide initial performance analysis and model validation of MPI and OpenMP applications on these multicore supercomputers because the measured sustained memory bandwidth can provide insight into the memory bandwidth that a system should sustain on scientific applications with the same amount of workload per core. In addition to using these benchmarks, we also use a weak-scaling hybrid MPI/OpenMP large-scale scientific application: Gyrokinetic Toroidal Code (GTC) in magnetic fusion to validate our performance model of the hybrid application on these multicore supercomputers. The validation results for our performance modeling method show less than 7.77% error rate in predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore supercomputers. © 2013 Elsevier Inc.

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.

Scientific Performance of a Nano-satellite MeV Telescope

Energy Technology Data Exchange (ETDEWEB)

Lucchetta, Giulio; Berlato, Francesco; Rando, Riccardo; Bastieri, Denis; Urso, Giorgio, E-mail: giulio.lucchetta@desy.de, E-mail: fberlato@mpe.mpg.de [Dipartimento di Fisica and Astronomia “G. Galilei,” Università di Padova, I-35131 Padova (Italy)

2017-05-01

Over the past two decades, both X-ray and gamma-ray astronomy have experienced great progress. However, the region of the electromagnetic spectrum around ∼1 MeV is not so thoroughly explored. Future medium-sized gamma-ray telescopes will fill this gap in observations. As the timescale for the development and launch of a medium-class mission is ∼10 years, with substantial costs, we propose a different approach for the immediate future. In this paper, we evaluate the viability of a much smaller and cheaper detector: a nano-satellite Compton telescope, based on the CubeSat architecture. The scientific performance of this telescope would be well below that of the instrument expected for the future larger missions; however, via simulations, we estimate that such a compact telescope will achieve a performance similar to that of COMPTEL.

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...

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).

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

Science.gov (United States)

Thackston, Russell; Fortenberry, Ryan C

2015-05-05

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

Scientific work environments in the next decade

Science.gov (United States)

Gomez, Julian E.

1989-01-01

The applications of contemporary computer graphics to scientific visualization is described, with emphasis on the nonintuitive problems. A radically different approach is proposed which centers on the idea of the scientist being in the simulation display space rather than observing it on a screen. Interaction is performed with nonstandard input devices to preserve the feeling of being immersed in the three-dimensional display space. Construction of such a system could begin now with currently available technology.

FY01 Supplemental Science and Performance Analysis: Volume 1, Scientific Bases and Analyses

International Nuclear Information System (INIS)

Bodvarsson, G.S.; Dobson, David

2001-01-01

The U.S. Department of Energy (DOE) is considering the possible recommendation of a site at Yucca Mountain, Nevada, for development as a geologic repository for the disposal of high-level radioactive waste and spent nuclear fuel. To facilitate public review and comment, in May 2001 the DOE released the Yucca Mountain Science and Engineering Report (S and ER) (DOE 2001 [DIRS 153849]), which presents technical information supporting the consideration of the possible site recommendation. The report summarizes the results of more than 20 years of scientific and engineering studies. A decision to recommend the site has not been made: the DOE has provided the S and ER and its supporting documents as an aid to the public in formulating comments on the possible recommendation. When the S and ER (DOE 2001 [DIRS 153849]) was released, the DOE acknowledged that technical and scientific analyses of the site were ongoing. Therefore, the DOE noted in the Federal Register Notice accompanying the report (66 FR 23013 [DIRS 155009], p. 2) that additional technical information would be released before the dates, locations, and times for public hearings on the possible recommendation were announced. This information includes: (1) the results of additional technical studies of a potential repository at Yucca Mountain, contained in this FY01 Supplemental Science and Performance Analyses: Vol. 1, Scientific Bases and Analyses; and FY01 Supplemental Science and Performance Analyses: Vol. 2, Performance Analyses (McNeish 2001 [DIRS 155023]) (collectively referred to as the SSPA) and (2) a preliminary evaluation of the Yucca Mountain site's preclosure and postclosure performance against the DOE's proposed site suitability guidelines (10 CFR Part 963 [64 FR 67054 [DIRS 124754

FY01 Supplemental Science and Performance Analysis: Volume 1,Scientific Bases and Analyses

Energy Technology Data Exchange (ETDEWEB)

Bodvarsson, G.S.; Dobson, David

2001-05-30

The U.S. Department of Energy (DOE) is considering the possible recommendation of a site at Yucca Mountain, Nevada, for development as a geologic repository for the disposal of high-level radioactive waste and spent nuclear fuel. To facilitate public review and comment, in May 2001 the DOE released the Yucca Mountain Science and Engineering Report (S&ER) (DOE 2001 [DIRS 153849]), which presents technical information supporting the consideration of the possible site recommendation. The report summarizes the results of more than 20 years of scientific and engineering studies. A decision to recommend the site has not been made: the DOE has provided the S&ER and its supporting documents as an aid to the public in formulating comments on the possible recommendation. When the S&ER (DOE 2001 [DIRS 153849]) was released, the DOE acknowledged that technical and scientific analyses of the site were ongoing. Therefore, the DOE noted in the Federal Register Notice accompanying the report (66 FR 23013 [DIRS 155009], p. 2) that additional technical information would be released before the dates, locations, and times for public hearings on the possible recommendation were announced. This information includes: (1) the results of additional technical studies of a potential repository at Yucca Mountain, contained in this FY01 Supplemental Science and Performance Analyses: Vol. 1, Scientific Bases and Analyses; and FY01 Supplemental Science and Performance Analyses: Vol. 2, Performance Analyses (McNeish 2001 [DIRS 155023]) (collectively referred to as the SSPA) and (2) a preliminary evaluation of the Yucca Mountain site's preclosure and postclosure performance against the DOE's proposed site suitability guidelines (10 CFR Part 963 [64 FR 67054 [DIRS 124754

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...

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

Science.gov (United States)

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

2009-07-01

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

Exploiting graphics processing units for computational biology and bioinformatics.

Science.gov (United States)

Payne, Joshua L; Sinnott-Armstrong, Nicholas A; Moore, Jason H

2010-09-01

Advances in the video gaming industry have led to the production of low-cost, high-performance graphics processing units (GPUs) that possess more memory bandwidth and computational capability than central processing units (CPUs), the standard workhorses of scientific computing. With the recent release of generalpurpose GPUs and NVIDIA's GPU programming language, CUDA, graphics engines are being adopted widely in scientific computing applications, particularly in the fields of computational biology and bioinformatics. The goal of this article is to concisely present an introduction to GPU hardware and programming, aimed at the computational biologist or bioinformaticist. To this end, we discuss the primary differences between GPU and CPU architecture, introduce the basics of the CUDA programming language, and discuss important CUDA programming practices, such as the proper use of coalesced reads, data types, and memory hierarchies. We highlight each of these topics in the context of computing the all-pairs distance between instances in a dataset, a common procedure in numerous disciplines of scientific computing. We conclude with a runtime analysis of the GPU and CPU implementations of the all-pairs distance calculation. We show our final GPU implementation to outperform the CPU implementation by a factor of 1700.

Function Follows Performance in Evolutionary Computational Processing

DEFF Research Database (Denmark)

Pasold, Anke; Foged, Isak Worre

2011-01-01

As the title ‘Function Follows Performance in Evolutionary Computational Processing’ suggests, this paper explores the potentials of employing multiple design and evaluation criteria within one processing model in order to account for a number of performative parameters desired within varied...

Computer Self-Efficacy, Computer Anxiety, Performance and Personal Outcomes of Turkish Physical Education Teachers

Science.gov (United States)

Aktag, Isil

2015-01-01

The purpose of this study is to determine the computer self-efficacy, performance outcome, personal outcome, and affect and anxiety level of physical education teachers. Influence of teaching experience, computer usage and participation of seminars or in-service programs on computer self-efficacy level were determined. The subjects of this study…

Big data computing: Building a vision for ARS information management

Science.gov (United States)

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

Airborne Cloud Computing Environment (ACCE)

Science.gov (United States)

Hardman, Sean; Freeborn, Dana; Crichton, Dan; Law, Emily; Kay-Im, Liz

2011-01-01

Airborne Cloud Computing Environment (ACCE) is JPL's internal investment to improve the return on airborne missions. Improve development performance of the data system. Improve return on the captured science data. The investment is to develop a common science data system capability for airborne instruments that encompasses the end-to-end lifecycle covering planning, provisioning of data system capabilities, and support for scientific analysis in order to improve the quality, cost effectiveness, and capabilities to enable new scientific discovery and research in earth observation.

Nurturing a growing field: Computers & Geosciences

Science.gov (United States)

Mariethoz, Gregoire; Pebesma, Edzer

2017-10-01

Computational issues are becoming increasingly critical for virtually all fields of geoscience. This includes the development of improved algorithms and models, strategies for implementing high-performance computing, or the management and visualization of the large datasets provided by an ever-growing number of environmental sensors. Such issues are central to scientific fields as diverse as geological modeling, Earth observation, geophysics or climatology, to name just a few. Related computational advances, across a range of geoscience disciplines, are the core focus of Computers & Geosciences, which is thus a truly multidisciplinary journal.

Templet Web: the use of volunteer computing approach in PaaS-style cloud

Science.gov (United States)

Vostokin, Sergei; Artamonov, Yuriy; Tsarev, Daniil

2018-03-01

This article presents the Templet Web cloud service. The service is designed for high-performance scientific computing automation. The use of high-performance technology is specifically required by new fields of computational science such as data mining, artificial intelligence, machine learning, and others. Cloud technologies provide a significant cost reduction for high-performance scientific applications. The main objectives to achieve this cost reduction in the Templet Web service design are: (a) the implementation of "on-demand" access; (b) source code deployment management; (c) high-performance computing programs development automation. The distinctive feature of the service is the approach mainly used in the field of volunteer computing, when a person who has access to a computer system delegates his access rights to the requesting user. We developed an access procedure, algorithms, and software for utilization of free computational resources of the academic cluster system in line with the methods of volunteer computing. The Templet Web service has been in operation for five years. It has been successfully used for conducting laboratory workshops and solving research problems, some of which are considered in this article. The article also provides an overview of research directions related to service development.

Vision systems for scientific and engineering applications

International Nuclear Information System (INIS)

Chadda, V.K.

2009-01-01

Human performance can get degraded due to boredom, distraction and fatigue in vision-related tasks such as measurement, counting etc. Vision based techniques are increasingly being employed in many scientific and engineering applications. Notable advances in this field are emerging from continuing improvements in the fields of sensors and related technologies, and advances in computer hardware and software. Automation utilizing vision-based systems can perform repetitive tasks faster and more accurately, with greater consistency over time than humans. Electronics and Instrumentation Services Division has developed vision-based systems for several applications to perform tasks such as precision alignment, biometric access control, measurement, counting etc. This paper describes in brief four such applications. (author)

Activities of the Research Institute for Advanced Computer Science

Science.gov (United States)

Oliger, Joseph

1994-01-01

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. Research at RIACS is currently being done in the following areas: (1) parallel computing; (2) advanced methods for scientific computing; (3) high performance networks; and (4) learning systems. RIACS technical reports are usually preprints of manuscripts that have been submitted to research journals or conference proceedings. A list of these reports for the period January 1, 1994 through December 31, 1994 is in the Reports and Abstracts section of this report.

Status, performance and scientific highlights from the MAGIC telescope system

Energy Technology Data Exchange (ETDEWEB)

Doert, Marlene [Technische Universitaet Dortmund (Germany); Ruhr-Universitaet Bochum (Germany); Collaboration: MAGIC-Collaboration

2015-07-01

The MAGIC telescopes are a system of two 17 m Imaging Air Cherenkov Telescopes, which are located at 2200 m above sea level at the Roque de Los Muchachos Observatory on the Canary Island of La Palma. In this presentation, we report on recent scientific highlights gained from MAGIC observations in the galactic and the extragalactic regime. We also present the current status and performance of the MAGIC system after major hardware upgrades in the years 2011 to 2014 and give an overview of future plans.

Cross-language Babel structs—making scientific interfaces more efficient

International Nuclear Information System (INIS)

Prantl, Adrian; Epperly, Thomas G W; Ebner, Dietmar

2013-01-01

Babel is an open-source language interoperability framework tailored to the needs of high-performance scientific computing. As an integral element of the Common Component Architecture, it is employed in a wide range of scientific applications where it is used to connect components written in different programming languages. In this paper we describe how we extended Babel to support interoperable tuple data types (structs). Structs are a common idiom in (mono-lingual) scientific application programming interfaces (APIs); they are an efficient way to pass tuples of nonuniform data between functions, and are supported natively by most programming languages. Using our extended version of Babel, developers of scientific codes can now pass structs as arguments between functions implemented in any of the supported languages. In C, C++, Fortran 2003/2008 and Chapel, structs can be passed without the overhead of data marshaling or copying, providing language interoperability at minimal cost. Other supported languages are Fortran 77, Fortran 90/95, Java and Python. We will show how we designed a struct implementation that is interoperable with all of the supported languages and present benchmark data to compare the performance of all language bindings, highlighting the differences between languages that offer native struct support and an object-oriented interface with getter/setter methods. A case study shows how structs can help simplify the interfaces of scientific codes significantly. (paper)

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

Evaluation of medical research performance--position paper of the Association of the Scientific Medical Societies in Germany (AWMF).

Science.gov (United States)

Herrmann-Lingen, Christoph; Brunner, Edgar; Hildenbrand, Sibylle; Loew, Thomas H; Raupach, Tobias; Spies, Claudia; Treede, Rolf-Detlef; Vahl, Christian-Friedrich; Wenz, Hans-Jürgen

2014-01-01

The evaluation of medical research performance is a key prerequisite for the systematic advancement of medical faculties, research foci, academic departments, and individual scientists' careers. However, it is often based on vaguely defined aims and questionable methods and can thereby lead to unwanted regulatory effects. The current paper aims at defining the position of German academic medicine toward the aims, methods, and consequences of its evaluation. During the Berlin Forum of the Association of the Scientific Medical Societies in Germany (AWMF) held on 18 October 2013, international experts presented data on methods for evaluating medical research performance. Subsequent discussions among representatives of relevant scientific organizations and within three ad-hoc writing groups led to a first draft of this article. Further discussions within the AWMF Committee for Evaluation of Performance in Research and Teaching and the AWMF Executive Board resulted in the final consented version presented here. The AWMF recommends modifications to the current system of evaluating medical research performance. Evaluations should follow clearly defined and communicated aims and consist of both summative and formative components. Informed peer reviews are valuable but feasible in longer time intervals only. They can be complemented by objective indicators. However, the Journal Impact Factor is not an appropriate measure for evaluating individual publications or their authors. The scientific "impact" rather requires multidimensional evaluation. Indicators of potential relevance in this context may include, e.g., normalized citation rates of scientific publications, other forms of reception by the scientific community and the public, and activities in scientific organizations, research synthesis and science communication. In addition, differentiated recommendations are made for evaluating the acquisition of third-party funds and the promotion of junior scientists. With the