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

International Nuclear Information System (INIS)

Lederer, H

2008-01-01

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

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

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

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

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

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

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.  

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.

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

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)

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-03-01

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

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.

High-performance scientific computing in the cloud

Science.gov (United States)

Jorissen, Kevin; Vila, Fernando; Rehr, John

2011-03-01

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

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.

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

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

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.

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...

GRID computing for experimental high energy physics

International Nuclear Information System (INIS)

Moloney, G.R.; Martin, L.; Seviour, E.; Taylor, G.N.; Moorhead, G.F.

2002-01-01

Full text: The Large Hadron Collider (LHC), to be completed at the CERN laboratory in 2006, will generate 11 petabytes of data per year. The processing of this large data stream requires a large, distributed computing infrastructure. A recent innovation in high performance distributed computing, the GRID, has been identified as an important tool in data analysis for the LHC. GRID computing has actual and potential application in many fields which require computationally intensive analysis of large, shared data sets. The Australian experimental High Energy Physics community has formed partnerships with the High Performance Computing community to establish a GRID node at the University of Melbourne. Through Australian membership of the ATLAS experiment at the LHC, Australian researchers have an opportunity to be involved in the European DataGRID project. This presentation will include an introduction to the GRID, and it's application to experimental High Energy Physics. We will present the results of our studies, including participation in the first LHC data challenge

GPU-based high-performance computing for radiation therapy

International Nuclear Information System (INIS)

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

2014-01-01

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

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.

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...

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.

High performance computing on vector systems

CERN Document Server

Roller, Sabine

2008-01-01

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

High Performance Computing Modernization Program Kerberos Throughput Test Report

Science.gov (United States)

2017-10-26

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

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...

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.

Micromagnetics on high-performance workstation and mobile computational platforms

Science.gov (United States)

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

2015-05-01

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

Monitoring SLAC High Performance UNIX Computing Systems

International Nuclear Information System (INIS)

Lettsome, Annette K.

2005-01-01

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

High Performance Computing Software Applications for Space Situational Awareness

Science.gov (United States)

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

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

Power/energy use cases for high performance computing

Energy Technology Data Exchange (ETDEWEB)

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

2013-12-01

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

DURIP: High Performance Computing in Biomathematics Applications

Science.gov (United States)

2017-05-10

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

AHPCRC - Army High Performance Computing Research Center

Science.gov (United States)

2010-01-01

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

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.

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

Enabling High-Performance Computing as a Service

KAUST Repository

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

2012-01-01

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

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.

High-performance computing in accelerating structure design and analysis

International Nuclear Information System (INIS)

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

2006-01-01

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

Enabling High-Performance Computing as a Service

KAUST Repository

AbdelBaky, Moustafa

2012-10-01

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

High Performance Networks From Supercomputing to Cloud Computing

CERN Document Server

Abts, Dennis

2011-01-01

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

Evaluation of high-performance computing software

Energy Technology Data Exchange (ETDEWEB)

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

1996-12-31

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

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

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.

High Performance Computing Operations Review Report

Energy Technology Data Exchange (ETDEWEB)

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

2013-12-19

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

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

CERN Document Server

Kröner, Dietmar; Resch, Michael

2009-01-01

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

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

National Research Council Canada - National Science Library

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

2010-01-01

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

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

CSIR Research Space (South Africa)

Sithole, Happy

2017-10-01

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

The path toward HEP High Performance Computing

International Nuclear Information System (INIS)

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

2014-01-01

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

High performance computing and communications: FY 1997 implementation plan

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-12-01

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

High performance computing and communications: FY 1996 implementation plan

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-05-16

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

Benchmarking high performance computing architectures with CMS’ skeleton framework

Science.gov (United States)

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

2017-10-01

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

Contemporary high performance computing from petascale toward exascale

CERN Document Server

Vetter, Jeffrey S

2015-01-01

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

Resilient and Robust High Performance Computing Platforms for Scientific Computing Integrity

Energy Technology Data Exchange (ETDEWEB)

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

2017-07-14

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

A high performance scientific cloud computing environment for materials simulations

Science.gov (United States)

Jorissen, K.; Vila, F. D.; Rehr, J. J.

2012-09-01

We describe the development of a scientific cloud computing (SCC) platform that offers high performance computation capability. The platform consists of a scientific virtual machine prototype containing a UNIX operating system and several materials science codes, together with essential interface tools (an SCC toolset) that offers functionality comparable to local compute clusters. In particular, our SCC toolset provides automatic creation of virtual clusters for parallel computing, including tools for execution and monitoring performance, as well as efficient I/O utilities that enable seamless connections to and from the cloud. Our SCC platform is optimized for the Amazon Elastic Compute Cloud (EC2). We present benchmarks for prototypical scientific applications and demonstrate performance comparable to local compute clusters. To facilitate code execution and provide user-friendly access, we have also integrated cloud computing capability in a JAVA-based GUI. Our SCC platform may be an alternative to traditional HPC resources for materials science or quantum chemistry applications.

Inclusive vision for high performance computing at the CSIR

CSIR Research Space (South Africa)

Gazendam, A

2006-02-01

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

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

A high performance scientific cloud computing environment for materials simulations

OpenAIRE

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

2011-01-01

We describe the development of a scientific cloud computing (SCC) platform that offers high performance computation capability. The platform consists of a scientific virtual machine prototype containing a UNIX operating system and several materials science codes, together with essential interface tools (an SCC toolset) that offers functionality comparable to local compute clusters. In particular, our SCC toolset provides automatic creation of virtual clusters for parallel computing, including...

The path toward HEP High Performance Computing

CERN Document Server

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

2014-01-01

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

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

CERN Document Server

Hori, Muneo; Ohsaki, Makoto

2016-01-01

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

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

CERN Document Server

Belyaev, Nikita; The ATLAS collaboration

2017-01-01

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

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

International Nuclear Information System (INIS)

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

1988-08-01

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

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

International Nuclear Information System (INIS)

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

2014-11-01

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

A High Performance VLSI Computer Architecture For Computer Graphics

Science.gov (United States)

Chin, Chi-Yuan; Lin, Wen-Tai

1988-10-01

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

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

Science.gov (United States)

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

2015-01-01

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

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

International Nuclear Information System (INIS)

Pop, Florin

2014-01-01

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

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 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.

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...

Component-based software for high-performance scientific computing

Energy Technology Data Exchange (ETDEWEB)

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

2005-01-01

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

Component-based software for high-performance scientific computing

International Nuclear Information System (INIS)

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

2005-01-01

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

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

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

KAUST Repository

Zheng, Shuai

2011-06-01

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

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

Science.gov (United States)

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

2017-12-01

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

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

Science.gov (United States)

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

2017-10-01

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

High performance computing and communications: FY 1995 implementation plan

Energy Technology Data Exchange (ETDEWEB)

NONE

1994-04-01

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

Unravelling the structure of matter on high-performance computers

International Nuclear Information System (INIS)

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

1992-11-01

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

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

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

Science.gov (United States)

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

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Anwar S. Shatil

2015-01-01

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

Performance of particle in cell methods on highly concurrent computational architectures

International Nuclear Information System (INIS)

Adams, M.F.; Ethier, S.; Wichmann, N.

2009-01-01

Particle in cell (PIC) methods are effective in computing Vlasov-Poisson system of equations used in simulations of magnetic fusion plasmas. PIC methods use grid based computations, for solving Poisson's equation or more generally Maxwell's equations, as well as Monte-Carlo type methods to sample the Vlasov equation. The presence of two types of discretizations, deterministic field solves and Monte-Carlo methods for the Vlasov equation, pose challenges in understanding and optimizing performance on today large scale computers which require high levels of concurrency. These challenges arises from the need to optimize two very different types of processes and the interactions between them. Modern cache based high-end computers have very deep memory hierarchies and high degrees of concurrency which must be utilized effectively to achieve good performance. The effective use of these machines requires maximizing concurrency by eliminating serial or redundant work and minimizing global communication. A related issue is minimizing the memory traffic between levels of the memory hierarchy because performance is often limited by the bandwidths and latencies of the memory system. This paper discusses some of the performance issues, particularly in regard to parallelism, of PIC methods. The gyrokinetic toroidal code (GTC) is used for these studies and a new radial grid decomposition is presented and evaluated. Scaling of the code is demonstrated on ITER sized plasmas with up to 16K Cray XT3/4 cores.

Performance of particle in cell methods on highly concurrent computational architectures

International Nuclear Information System (INIS)

Adams, M F; Ethier, S; Wichmann, N

2007-01-01

Particle in cell (PIC) methods are effective in computing Vlasov-Poisson system of equations used in simulations of magnetic fusion plasmas. PIC methods use grid based computations, for solving Poisson's equation or more generally Maxwell's equations, as well as Monte-Carlo type methods to sample the Vlasov equation. The presence of two types of discretizations, deterministic field solves and Monte-Carlo methods for the Vlasov equation, pose challenges in understanding and optimizing performance on today large scale computers which require high levels of concurrency. These challenges arises from the need to optimize two very different types of processes and the interactions between them. Modern cache based high-end computers have very deep memory hierarchies and high degrees of concurrency which must be utilized effectively to achieve good performance. The effective use of these machines requires maximizing concurrency by eliminating serial or redundant work and minimizing global communication. A related issue is minimizing the memory traffic between levels of the memory hierarchy because performance is often limited by the bandwidths and latencies of the memory system. This paper discusses some of the performance issues, particularly in regard to parallelism, of PIC methods. The gyrokinetic toroidal code (GTC) is used for these studies and a new radial grid decomposition is presented and evaluated. Scaling of the code is demonstrated on ITER sized plasmas with up to 16K Cray XT3/4 cores

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.

5th International Conference on High Performance Scientific Computing

CERN Document Server

Hoang, Xuan; Rannacher, Rolf; Schlöder, Johannes

2014-01-01

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

3rd International Conference on High Performance Scientific Computing

CERN Document Server

Kostina, Ekaterina; Phu, Hoang; Rannacher, Rolf

2008-01-01

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

6th International Conference on High Performance Scientific Computing

CERN Document Server

Phu, Hoang; Rannacher, Rolf; Schlöder, Johannes

2017-01-01

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

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

CERN Document Server

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

2017-01-01

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

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-02-06

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

A High Performance COTS Based Computer Architecture

Science.gov (United States)

Patte, Mathieu; Grimoldi, Raoul; Trautner, Roland

2014-08-01

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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

Science.gov (United States)

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

2016-07-01

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

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.

Community Cloud Computing

Science.gov (United States)

Marinos, Alexandros; Briscoe, Gerard

Cloud Computing is rising fast, with its data centres growing at an unprecedented rate. However, this has come with concerns over privacy, efficiency at the expense of resilience, and environmental sustainability, because of the dependence on Cloud vendors such as Google, Amazon and Microsoft. Our response is an alternative model for the Cloud conceptualisation, providing a paradigm for Clouds in the community, utilising networked personal computers for liberation from the centralised vendor model. Community Cloud Computing (C3) offers an alternative architecture, created by combing the Cloud with paradigms from Grid Computing, principles from Digital Ecosystems, and sustainability from Green Computing, while remaining true to the original vision of the Internet. It is more technically challenging than Cloud Computing, having to deal with distributed computing issues, including heterogeneous nodes, varying quality of service, and additional security constraints. However, these are not insurmountable challenges, and with the need to retain control over our digital lives and the potential environmental consequences, it is a challenge we must pursue.

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 ...

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...

High-Performance Computing Paradigm and Infrastructure

CERN Document Server

Yang, Laurence T

2006-01-01

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

High Performance Computing - Power Application Programming Interface Specification.

Energy Technology Data Exchange (ETDEWEB)

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

2014-08-01

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

NINJA: Java for High Performance Numerical Computing

Directory of Open Access Journals (Sweden)

José E. Moreira

2002-01-01

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

Toward an ultra-high resolution community climate system model for the BlueGene platform

International Nuclear Information System (INIS)

Dennis, John M; Jacob, Robert; Vertenstein, Mariana; Craig, Tony; Loy, Raymond

2007-01-01

Global climate models need to simulate several small, regional-scale processes which affect the global circulation in order to accurately simulate the climate. This is particularly important in the ocean where small scale features such as oceanic eddies are currently represented with adhoc parameterizations. There is also a need for higher resolution to provide climate predictions at small, regional scales. New high-performance computing platforms such as the IBM BlueGene can provide the necessary computational power to perform ultra-high resolution climate model integrations. We have begun to investigate the scaling of the individual components of the Community Climate System Model to prepare it for integrations on BlueGene and similar platforms. Our investigations show that it is possible to successfully utilize O(32K) processors. We describe the scalability of five models: the Parallel Ocean Program (POP), the Community Ice CodE (CICE), the Community Land Model (CLM), and the new CCSM sequential coupler (CPL7) which are components of the next generation Community Climate System Model (CCSM); as well as the High-Order Method Modeling Environment (HOMME) which is a dynamical core currently being evaluated within the Community Atmospheric Model. For our studies we concentrate on 1/10 0 resolution for CICE, POP, and CLM models and 1/4 0 resolution for HOMME. The ability to simulate high resolutions on the massively parallel petascale systems that will dominate high-performance computing for the foreseeable future is essential to the advancement of climate science

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

International Nuclear Information System (INIS)

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

2009-01-01

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

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

Science.gov (United States)

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

2013-01-28

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

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

Data.gov (United States)

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

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...

The high performance cluster computing system for BES offline data analysis

International Nuclear Information System (INIS)

Sun Yongzhao; Xu Dong; Zhang Shaoqiang; Yang Ting

2004-01-01

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

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

International Nuclear Information System (INIS)

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

2001-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2001-10-12

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

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

Directory of Open Access Journals (Sweden)

Marietjie Havenga

2011-07-01

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

High energy physics and grid computing

International Nuclear Information System (INIS)

Yu Chuansong

2004-01-01

The status of the new generation computing environment of the high energy physics experiments is introduced briefly in this paper. The development of the high energy physics experiments and the new computing requirements by the experiments are presented. The blueprint of the new generation computing environment of the LHC experiments, the history of the Grid computing, the R and D status of the high energy physics grid computing technology, the network bandwidth needed by the high energy physics grid and its development are described. The grid computing research in Chinese high energy physics community is introduced at last. (authors)

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

National Research Council Canada - National Science Library

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

2007-01-01

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

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.

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.

Toward an ultra-high resolution community climate system model for the BlueGene platform

Energy Technology Data Exchange (ETDEWEB)

Dennis, John M [Computer Science Section, National Center for Atmospheric Research, Boulder, CO (United States); Jacob, Robert [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL (United States); Vertenstein, Mariana [Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO (United States); Craig, Tony [Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO (United States); Loy, Raymond [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL (United States)

2007-07-15

Global climate models need to simulate several small, regional-scale processes which affect the global circulation in order to accurately simulate the climate. This is particularly important in the ocean where small scale features such as oceanic eddies are currently represented with adhoc parameterizations. There is also a need for higher resolution to provide climate predictions at small, regional scales. New high-performance computing platforms such as the IBM BlueGene can provide the necessary computational power to perform ultra-high resolution climate model integrations. We have begun to investigate the scaling of the individual components of the Community Climate System Model to prepare it for integrations on BlueGene and similar platforms. Our investigations show that it is possible to successfully utilize O(32K) processors. We describe the scalability of five models: the Parallel Ocean Program (POP), the Community Ice CodE (CICE), the Community Land Model (CLM), and the new CCSM sequential coupler (CPL7) which are components of the next generation Community Climate System Model (CCSM); as well as the High-Order Method Modeling Environment (HOMME) which is a dynamical core currently being evaluated within the Community Atmospheric Model. For our studies we concentrate on 1/10{sup 0} resolution for CICE, POP, and CLM models and 1/4{sup 0} resolution for HOMME. The ability to simulate high resolutions on the massively parallel petascale systems that will dominate high-performance computing for the foreseeable future is essential to the advancement of climate science.

High performance simulation for the Silva project using the tera computer

International Nuclear Information System (INIS)

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

2003-01-01

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

High performance simulation for the Silva project using the tera computer

Energy Technology Data Exchange (ETDEWEB)

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

2003-07-01

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

Scalability of DL_POLY on High Performance Computing Platform

Directory of Open Access Journals (Sweden)

Mabule Samuel Mabakane

2017-12-01

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

Internet end-to-end performance monitoring for the High Energy Nuclear and Particle Physics community

International Nuclear Information System (INIS)

Matthews, W.

2000-01-01

Modern High Energy Nuclear and Particle Physics (HENP) experiments at Laboratories around the world present a significant challenge to wide area networks. Petabytes (1015) or exabytes (1018) of data will be generated during the lifetime of the experiment. Much of this data will be distributed via the Internet to the experiment's collaborators at Universities and Institutes throughout the world for analysis. In order to assess the feasibility of the computing goals of these and future experiments, the HENP networking community is actively monitoring performance across a large part of the Internet used by its collaborators. Since 1995, the pingER project has been collecting data on ping packet loss and round trip times. In January 2000, there are 28 monitoring sites in 15 countries gathering data on over 2,000 end-to-end pairs. HENP labs such as SLAC, Fermi Lab and CERN are using Advanced Network's Surveyor project and monitoring performance from one-way delay of UDP packets. More recently several HENP sites have become involved with NLANR's active measurement program (AMP). In addition SLAC and CERN are part of the RIPE test-traffic project and SLAC is home for a NIMI machine. The large End-to-end performance monitoring infrastructure allows the HENP networking community to chart long term trends and closely examine short term glitches across a wide range of networks and connections. The different methodologies provide opportunities to compare results based on different protocols and statistical samples. Understanding agreement and discrepancies between results provides particular insight into the nature of the network. This paper will highlight the practical side of monitoring by reviewing the special needs of High Energy Nuclear and Particle Physics experiments and provide an overview of the experience of measuring performance across a large number of interconnected networks throughout the world with various methodologies. In particular, results from each project

Internet end-to-end performance monitoring for the High Energy Nuclear and Particle Physics community

Energy Technology Data Exchange (ETDEWEB)

Matthews, W.

2000-02-22

Modern High Energy Nuclear and Particle Physics (HENP) experiments at Laboratories around the world present a significant challenge to wide area networks. Petabytes (1015) or exabytes (1018) of data will be generated during the lifetime of the experiment. Much of this data will be distributed via the Internet to the experiment's collaborators at Universities and Institutes throughout the world for analysis. In order to assess the feasibility of the computing goals of these and future experiments, the HENP networking community is actively monitoring performance across a large part of the Internet used by its collaborators. Since 1995, the pingER project has been collecting data on ping packet loss and round trip times. In January 2000, there are 28 monitoring sites in 15 countries gathering data on over 2,000 end-to-end pairs. HENP labs such as SLAC, Fermi Lab and CERN are using Advanced Network's Surveyor project and monitoring performance from one-way delay of UDP packets. More recently several HENP sites have become involved with NLANR's active measurement program (AMP). In addition SLAC and CERN are part of the RIPE test-traffic project and SLAC is home for a NIMI machine. The large End-to-end performance monitoring infrastructure allows the HENP networking community to chart long term trends and closely examine short term glitches across a wide range of networks and connections. The different methodologies provide opportunities to compare results based on different protocols and statistical samples. Understanding agreement and discrepancies between results provides particular insight into the nature of the network. This paper will highlight the practical side of monitoring by reviewing the special needs of High Energy Nuclear and Particle Physics experiments and provide an overview of the experience of measuring performance across a large number of interconnected networks throughout the world with various methodologies. In particular, results

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

KAUST Repository

Rojas, Jhonathan Prieto

2013-09-10

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

CSDMS2.0: Computational Infrastructure for Community Surface Dynamics Modeling

Science.gov (United States)

Syvitski, J. P.; Hutton, E.; Peckham, S. D.; Overeem, I.; Kettner, A.

2012-12-01

The Community Surface Dynamic Modeling System (CSDMS) is an NSF-supported, international and community-driven program that seeks to transform the science and practice of earth-surface dynamics modeling. CSDMS integrates a diverse community of more than 850 geoscientists representing 360 international institutions (academic, government, industry) from 60 countries and is supported by a CSDMS Interagency Committee (22 Federal agencies), and a CSDMS Industrial Consortia (18 companies). CSDMS presently distributes more 200 Open Source models and modeling tools, access to high performance computing clusters in support of developing and running models, and a suite of products for education and knowledge transfer. CSDMS software architecture employs frameworks and services that convert stand-alone models into flexible "plug-and-play" components to be assembled into larger applications. CSDMS2.0 will support model applications within a web browser, on a wider variety of computational platforms, and on other high performance computing clusters to ensure robustness and sustainability of the framework. Conversion of stand-alone models into "plug-and-play" components will employ automated wrapping tools. Methods for quantifying model uncertainty are being adapted as part of the modeling framework. Benchmarking data is being incorporated into the CSDMS modeling framework to support model inter-comparison. Finally, a robust mechanism for ingesting and utilizing semantic mediation databases is being developed within the Modeling Framework. Six new community initiatives are being pursued: 1) an earth - ecosystem modeling initiative to capture ecosystem dynamics and ensuing interactions with landscapes, 2) a geodynamics initiative to investigate the interplay among climate, geomorphology, and tectonic processes, 3) an Anthropocene modeling initiative, to incorporate mechanistic models of human influences, 4) a coastal vulnerability modeling initiative, with emphasis on deltas and

Performance engineering in the community atmosphere model

International Nuclear Information System (INIS)

Worley, P; Mirin, A; Drake, J; Sawyer, W

2006-01-01

The Community Atmosphere Model (CAM) is the atmospheric component of the Community Climate System Model (CCSM) and is the primary consumer of computer resources in typical CCSM simulations. Performance engineering has been an important aspect of CAM development throughout its existence. This paper briefly summarizes these efforts and their impacts over the past five years

Analysis and modeling of social influence in high performance computing workloads

KAUST Repository

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

2011-01-01

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

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.

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

KAUST Repository

Downes, Turlough P.

2013-01-01

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

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

International Nuclear Information System (INIS)

Oehmen, C S; Cannon, W R

2008-01-01

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

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

KAUST Repository

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

2016-01-01

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

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

Science.gov (United States)

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

1990-07-01

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

Overview of Parallel Platforms for Common High Performance Computing

Directory of Open Access Journals (Sweden)

T. Fryza

2012-04-01

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

HIGH PERFORMANCE PHOTOGRAMMETRIC PROCESSING ON COMPUTER CLUSTERS

Directory of Open Access Journals (Sweden)

V. N. Adrov

2012-07-01

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

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2013-09-01

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

High Performance Data Distribution for Scientific Community

Science.gov (United States)

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

2010-05-01

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

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

National Research Council Canada - National Science Library

1999-01-01

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

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.

Computer science of the high performance; Informatica del alto rendimiento

Energy Technology Data Exchange (ETDEWEB)

Moraleda, A.

2008-07-01

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

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

Science.gov (United States)

Eurich, Markus; Calleja, Paul; Boutellier, Roman

2013-01-01

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

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

Science.gov (United States)

2015-06-01

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

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

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

International Nuclear Information System (INIS)

Ernst, M.

1994-01-01

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

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.

High performance computing environment for multidimensional image analysis.

Science.gov (United States)

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

2007-07-10

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

A checkpoint compression study for high-performance computing systems

Energy Technology Data Exchange (ETDEWEB)

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

2015-02-17

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

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

CERN Document Server

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

2012-01-01

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

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

Science.gov (United States)

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

2010-06-21

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

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.

What Physicists Should Know About High Performance Computing - Circa 2002

Science.gov (United States)

Frederick, Donald

2002-08-01

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

RISC Processors and High Performance Computing

Science.gov (United States)

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

1995-01-01

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

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

Data.gov (United States)

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

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

CERN Document Server

Reinefeld, A

2001-01-01

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

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

International Nuclear Information System (INIS)

Bouchard, Kristofer E.

2016-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-03-01

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

Clusters of PCS for high-speed computation for modelling of the climate

International Nuclear Information System (INIS)

Pabon C, Jose Daniel; Eslava R, Jesus Antonio; Montoya G, Gerardo de Jesus

2001-01-01

In order to create high speed computing capability, the Program of Post grade in Meteorology of the Department of Geosciences, National University of Colombia installed a cluster of 8 PCs for parallel processing. This high-speed processing machine was tested with the Climate Community Model (CCM3). In this paper, the results related to the performance of this machine are presented

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

Science.gov (United States)

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

2012-01-01

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

Building a High Performance Computing Infrastructure for Novosibirsk Scientific Center

International Nuclear Information System (INIS)

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

2011-01-01

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

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-12-31

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

Trends in high-performance computing for engineering calculations.

Science.gov (United States)

Giles, M B; Reguly, I

2014-08-13

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

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

Science.gov (United States)

Ivanovic, Pavle; Richter, Harald

2018-01-01

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

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

International Nuclear Information System (INIS)

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

1994-06-01

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

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

Directory of Open Access Journals (Sweden)

Alberto Cocaña-Fernández

2016-03-01

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

7th International Workshop on Parallel Tools for High Performance Computing

CERN Document Server

Gracia, José; Nagel, Wolfgang; Resch, Michael

2014-01-01

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

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

Science.gov (United States)

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

2014-05-01

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

Astronomy and Computing: A New Journal for the Astronomical Computing Community

Science.gov (United States)

Mann, R. G.; Accomazzi, A.; Budavári, T.; Fluke, C.; Gray, N.; O'Mullane, W.; Wicenec, A.; Wise, M.

2013-10-01

We introduce Astronomy and Computing (A&C), a new, peer-reviewed journal for the expanding community of people whose work focuses on the application of computer science and information technology within astronomy, rather than on astronomical research per se. A&C arose from a BoF discussion at the ADASS XX conference in Boston, and from the ADASS community will come many of the people who will write, referee and read the papers published in A&C. In this paper, we outline the aims and scope of A&C, together with a summary of the types of paper we envisage it publishing and the criteria that will be used to referee them, and we invite the ADASS community to help us develop these in more detail and to shape a journal that serves the astronomical computing community well.

Real-time Tsunami Inundation Prediction Using High Performance Computers

Science.gov (United States)

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

2014-12-01

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

High performance systems

Energy Technology Data Exchange (ETDEWEB)

Vigil, M.B. [comp.

1995-03-01

This document provides a written compilation of the presentations and viewgraphs from the 1994 Conference on High Speed Computing given at the High Speed Computing Conference, {open_quotes}High Performance Systems,{close_quotes} held at Gleneden Beach, Oregon, on April 18 through 21, 1994.

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

KAUST Repository

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

2013-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-11-01

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

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

KAUST Repository

Ibeid, Huda

2016-03-04

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

Lightweight Provenance Service for High-Performance Computing

Energy Technology Data Exchange (ETDEWEB)

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

2017-09-09

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

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

Science.gov (United States)

Hessenbruch, John M.; Guilfoyle, Peter S.

1997-01-01

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

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

Science.gov (United States)

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

2017-12-01

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

9th International Workshop on Parallel Tools for High Performance Computing

CERN Document Server

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

2016-01-01

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

High Performance Computing - Power Application Programming Interface Specification Version 1.4

Energy Technology Data Exchange (ETDEWEB)

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

2016-10-01

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

[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.

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

International Nuclear Information System (INIS)

Adolphsen, Chris

2003-01-01

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

Enabling the ATLAS Experiment at the LHC for High Performance Computing

CERN Document Server

AUTHOR|(CDS)2091107; Ereditato, Antonio

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

Whole School Improvement and Restructuring as Prevention and Promotion: Lessons from STEP and the Project on High Performance Learning Communities.

Science.gov (United States)

Felner, Robert D.; Favazza, Antoinette; Shim, Minsuk; Brand, Stephen; Gu, Kenneth; Noonan, Nancy

2001-01-01

Describes the School Transitional Environment Project and its successor, the Project on High Performance Learning Communities, that have contributed to building a model for school improvement called the High Performance Learning Communities. The model seeks to build the principles of prevention into whole school change. Presents findings from…

HiGIS: An Open Framework for High Performance Geographic Information System

Directory of Open Access Journals (Sweden)

XIONG, W.

2015-08-01

Full Text Available Big data era expose many challenges to geospatial data management, geocomputation and cartography. There is no exception in geographic information systems (GIS community. Technologies and facilities of high performance computing (HPC become more and more feasible to researchers, while mobile computing, ubiquitous computing, and cloud computing are emerging. But traditional GIS need to be improved to take advantages of all these evolutions. We proposed and implemented a GIS married with high performance computing, which is called HiGIS. The goal of HiGIS is to promote the performance of geocomputation by leveraging the power of HPC, and to build an open framework for geospatial data storing, processing, displaying and sharing. In this paper the architecture, data model and modules of the HiGIS system are introduced. A geocomputation scheduling engine based on communicating sequential process was designed to exploit spatial analysis and processing. Parallel I/O strategy using file view was proposed to improve the performance of geospatial raster data access. In order to support web-based online mapping, an interactive cartographic script was provided to represent a map. A demostration of locating house was used to manifest the characteristics of HiGIS. Parallel and concurrency performance experiments show the feasibility of this system.

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

International Nuclear Information System (INIS)

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

2009-01-01

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

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

Development and Performance of the Modularized, High-performance Computing and Hybrid-architecture Capable GEOS-Chem Chemical Transport Model

Science.gov (United States)

Long, M. S.; Yantosca, R.; Nielsen, J.; Linford, J. C.; Keller, C. A.; Payer Sulprizio, M.; Jacob, D. J.

2014-12-01

The GEOS-Chem global chemical transport model (CTM), used by a large atmospheric chemistry research community, has been reengineered to serve as a platform for a range of computational atmospheric chemistry science foci and applications. Development included modularization for coupling to general circulation and Earth system models (ESMs) and the adoption of co-processor capable atmospheric chemistry solvers. This was done using an Earth System Modeling Framework (ESMF) interface that operates independently of GEOS-Chem scientific code to permit seamless transition from the GEOS-Chem stand-alone serial CTM to deployment as a coupled ESM module. In this manner, the continual stream of updates contributed by the CTM user community is automatically available for broader applications, which remain state-of-science and directly referenceable to the latest version of the standard GEOS-Chem CTM. These developments are now available as part of the standard version of the GEOS-Chem CTM. The system has been implemented as an atmospheric chemistry module within the NASA GEOS-5 ESM. The coupled GEOS-5/GEOS-Chem system was tested for weak and strong scalability and performance with a tropospheric oxidant-aerosol simulation. Results confirm that the GEOS-Chem chemical operator scales efficiently for any number of processes. Although inclusion of atmospheric chemistry in ESMs is computationally expensive, the excellent scalability of the chemical operator means that the relative cost goes down with increasing number of processes, making fine-scale resolution simulations possible.

Computer-aided engineering in High Energy Physics

International Nuclear Information System (INIS)

Bachy, G.; Hauviller, C.; Messerli, R.; Mottier, M.

1988-01-01

Computing, standard tool for a long time in the High Energy Physics community, is being slowly introduced at CERN in the mechanical engineering field. The first major application was structural analysis followed by Computer-Aided Design (CAD). Development work is now progressing towards Computer-Aided Engineering around a powerful data base. This paper gives examples of the power of this approach applied to engineering for accelerators and detectors

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

Science.gov (United States)

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

2016-04-19

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

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

Science.gov (United States)

Baxter, C.; Matott, L.

2012-12-01

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

High performance computing in power and energy systems

Energy Technology Data Exchange (ETDEWEB)

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

2013-07-01

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

High performance computer code for molecular dynamics simulations

International Nuclear Information System (INIS)

Levay, I.; Toekesi, K.

2007-01-01

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

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

Science.gov (United States)

Mills, Kim; Fox, Geoffrey

1994-01-01

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

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

Science.gov (United States)

Aragón, Alejandro M.

2014-11-01

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

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

Science.gov (United States)

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

2013-01-01

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

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

International Nuclear Information System (INIS)

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

2017-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-06-15

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

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

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

Science.gov (United States)

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

2018-05-03

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

Innovative Partnerships Assist Community College Computing Programs.

Science.gov (United States)

O'Banion, Terry

1987-01-01

Relates efforts of major corporations in providing assistance to community college computing programs. Explains the goals of the League for Innovation in the Community College, a consortium of 19 community colleges, and cites examples of collaborative projects. (ML)

High Performance Spaceflight Computing (HPSC)

Data.gov (United States)

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

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

International Nuclear Information System (INIS)

Diakhate, F.

2010-12-01

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

Lessons from High-Performing Hispanic Schools: Creating Learning Communities. Critical Issues in Educational Leadership Series.

Science.gov (United States)

Reyes, Pedro, Ed.; Scribner, Jay D., Ed.; Scribner, Alicia Paredes, Ed.

The current poor condition of education for Hispanic students need not exist. This book reports on high-performing schools along the Texas-Mexico border that have achieved schoolwide success by creating communities of learners. Three elementary, three middle, and two high schools in the border region were selected for study based on the following…

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

CERN Document Server

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

2016-01-01

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

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...

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.

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

Science.gov (United States)

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

2015-02-23

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-11-15

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

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

Directory of Open Access Journals (Sweden)

Ernestina Martel

2018-06-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-04-30

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

Analysis and modeling of social influence in high performance computing workloads

KAUST Repository

Zheng, Shuai

2011-01-01

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

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

International Nuclear Information System (INIS)

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

2001-01-01

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

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

International Nuclear Information System (INIS)

2002-01-01

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

Scalability of DL_POLY on High Performance Computing Platform

CSIR Research Space (South Africa)

Mabakane, Mabule S

2017-12-01

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

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

Science.gov (United States)

2015-09-01

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

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

Directory of Open Access Journals (Sweden)

Yurii Rogozhin

2014-03-01

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

MUMAX: A new high-performance micromagnetic simulation tool

International Nuclear Information System (INIS)

Vansteenkiste, A.; Van de Wiele, B.

2011-01-01

We present MUMAX, a general-purpose micromagnetic simulation tool running on graphical processing units (GPUs). MUMAX is designed for high-performance computations and specifically targets large simulations. In that case speedups of over a factor 100 x can be obtained compared to the CPU-based OOMMF program developed at NIST. MUMAX aims to be general and broadly applicable. It solves the classical Landau-Lifshitz equation taking into account the magnetostatic, exchange and anisotropy interactions, thermal effects and spin-transfer torque. Periodic boundary conditions can optionally be imposed. A spatial discretization using finite differences in two or three dimensions can be employed. MUMAX is publicly available as open-source software. It can thus be freely used and extended by community. Due to its high computational performance, MUMAX should open up the possibility of running extensive simulations that would be nearly inaccessible with typical CPU-based simulators. - Highlights: → Novel, open-source micromagnetic simulator on GPU hardware. → Speedup of ∝100x compared to other widely used tools. → Extensively validated against standard problems. → Makes previously infeasible simulations accessible.

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

Data.gov (United States)

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

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

Data.gov (United States)

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-08-15

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

International Nuclear Information System (INIS)

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

2017-01-01

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

High performance computations using dynamical nucleation theory

International Nuclear Information System (INIS)

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

2008-01-01

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

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

Directory of Open Access Journals (Sweden)

Muneo Hori

2018-02-01

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

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

KAUST Repository

Danani, Bob K.

2012-07-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-10-01

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

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

Science.gov (United States)

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

2015-06-30

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

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

Science.gov (United States)

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

2013-11-05

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

High performance computing, supercomputing, náročné počítání

Czech Academy of Sciences Publication Activity Database

Okrouhlík, Miloslav

2003-01-01

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

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.)

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

CERN Document Server

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

2014-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-06-01

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

High performance stream computing for particle beam transport simulations

International Nuclear Information System (INIS)

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

2008-01-01

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

Astronomy and Computing: A new journal for the astronomical computing community

NARCIS (Netherlands)

Accomazzi, A.; Budavári, T.; Fluke, C.; Gray, N.; Mann, R.G.; O'Mullane, W.; Wicenec, A.; Wise, M.

2013-01-01

We introduce Astronomy and Computing, a new journal for the growing population of people working in the domain where astronomy overlaps with computer science and information technology. The journal aims to provide a new communication channel within that community, which is not well served by current

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

Data.gov (United States)

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

Astronomy and Computing: A New Journal for the Astronomical Computing Community

NARCIS (Netherlands)

Mann, R.G.; Accomazzi, A.; Budavári, T.; Fluke, C.; Gray, N.; O'Mullane, W.; Wicenec, A.; Wise, M.

2013-01-01

We introduce Astronomy and Computing (A&C), a new, peer-reviewed journal for the expanding community of people whose work focuses on the application of computer science and information technology within astronomy, rather than on astronomical research per se. A&C arose from a BoF discussion at the

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

Science.gov (United States)

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

2016-02-27

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

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

Science.gov (United States)

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

2016-03-01

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

Enabling Diverse Software Stacks on Supercomputers using High Performance Virtual Clusters.

Energy Technology Data Exchange (ETDEWEB)

Younge, Andrew J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Pedretti, Kevin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Grant, Ryan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brightwell, Ron [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-05-01

While large-scale simulations have been the hallmark of the High Performance Computing (HPC) community for decades, Large Scale Data Analytics (LSDA) workloads are gaining attention within the scientific community not only as a processing component to large HPC simulations, but also as standalone scientific tools for knowledge discovery. With the path towards Exascale, new HPC runtime systems are also emerging in a way that differs from classical distributed com- puting models. However, system software for such capabilities on the latest extreme-scale DOE supercomputing needs to be enhanced to more appropriately support these types of emerging soft- ware ecosystems. In this paper, we propose the use of Virtual Clusters on advanced supercomputing resources to enable systems to support not only HPC workloads, but also emerging big data stacks. Specifi- cally, we have deployed the KVM hypervisor within Cray's Compute Node Linux on a XC-series supercomputer testbed. We also use libvirt and QEMU to manage and provision VMs directly on compute nodes, leveraging Ethernet-over-Aries network emulation. To our knowledge, this is the first known use of KVM on a true MPP supercomputer. We investigate the overhead our solution using HPC benchmarks, both evaluating single-node performance as well as weak scaling of a 32-node virtual cluster. Overall, we find single node performance of our solution using KVM on a Cray is very efficient with near-native performance. However overhead increases by up to 20% as virtual cluster size increases, due to limitations of the Ethernet-over-Aries bridged network. Furthermore, we deploy Apache Spark with large data analysis workloads in a Virtual Cluster, ef- fectively demonstrating how diverse software ecosystems can be supported by High Performance Virtual Clusters.

THE IMPROVEMENT OF COMPUTER NETWORK PERFORMANCE WITH BANDWIDTH MANAGEMENT IN KEMURNIAN II SENIOR HIGH SCHOOL

Directory of Open Access Journals (Sweden)

Bayu Kanigoro

2012-05-01

Full Text Available This research describes the improvement of computer network performance with bandwidth management in Kemurnian II Senior High School. The main issue of this research is the absence of bandwidth division on computer, which makes user who is downloading data, the provided bandwidth will be absorbed by the user. It leads other users do not get the bandwidth. Besides that, it has been done IP address division on each room, such as computer, teacher and administration room for supporting learning process in Kemurnian II Senior High School, so wireless network is needed. The method is location observation and interview with related parties in Kemurnian II Senior High School, the network analysis has run and designed a new topology network including the wireless network along with its configuration and separation bandwidth on microtic router and its limitation. The result is network traffic on Kemurnian II Senior High School can be shared evenly to each user; IX and IIX traffic are separated, which improve the speed on network access at school and the implementation of wireless network.Keywords: Bandwidth Management; Wireless Network

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)

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-05-15

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-09-01

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

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

Science.gov (United States)

Bielski, Conrad; Lemoine, Guido; Syryczynski, Jacek

2009-09-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-11-11

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

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

Science.gov (United States)

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

2017-10-01

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

High performance in software development

CERN Multimedia

CERN. Geneva; Haapio, Petri; Liukkonen, Juha-Matti

2015-01-01

What are the ingredients of high-performing software? Software development, especially for large high-performance systems, is one the most complex tasks mankind has ever tried. Technological change leads to huge opportunities but challenges our old ways of working. Processing large data sets, possibly in real time or with other tight computational constraints, requires an efficient solution architecture. Efficiency requirements span from the distributed storage and large-scale organization of computation and data onto the lowest level of processor and data bus behavior. Integrating performance behavior over these levels is especially important when the computation is resource-bounded, as it is in numerics: physical simulation, machine learning, estimation of statistical models, etc. For example, memory locality and utilization of vector processing are essential for harnessing the computing power of modern processor architectures due to the deep memory hierarchies of modern general-purpose computers. As a r...

Leveraging the Power of High Performance Computing for Next Generation Sequencing Data Analysis: Tricks and Twists from a High Throughput Exome Workflow

Science.gov (United States)

Wonczak, Stephan; Thiele, Holger; Nieroda, Lech; Jabbari, Kamel; Borowski, Stefan; Sinha, Vishal; Gunia, Wilfried; Lang, Ulrich; Achter, Viktor; Nürnberg, Peter

2015-01-01

Next generation sequencing (NGS) has been a great success and is now a standard method of research in the life sciences. With this technology, dozens of whole genomes or hundreds of exomes can be sequenced in rather short time, producing huge amounts of data. Complex bioinformatics analyses are required to turn these data into scientific findings. In order to run these analyses fast, automated workflows implemented on high performance computers are state of the art. While providing sufficient compute power and storage to meet the NGS data challenge, high performance computing (HPC) systems require special care when utilized for high throughput processing. This is especially true if the HPC system is shared by different users. Here, stability, robustness and maintainability are as important for automated workflows as speed and throughput. To achieve all of these aims, dedicated solutions have to be developed. In this paper, we present the tricks and twists that we utilized in the implementation of our exome data processing workflow. It may serve as a guideline for other high throughput data analysis projects using a similar infrastructure. The code implementing our solutions is provided in the supporting information files. PMID:25942438

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

Science.gov (United States)

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2010-11-01

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

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

International Nuclear Information System (INIS)

Qin, J; Bauer, M A

2010-01-01

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

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

DEFF Research Database (Denmark)

Bogdanov, Dan; Niitsoo, Margus; Toft, Tomas

2012-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2011-07-28

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

It takes a village: supporting inquiry- and equity-oriented computer science pedagogy through a professional learning community

Science.gov (United States)

Ryoo, Jean; Goode, Joanna; Margolis, Jane

2015-10-01

This article describes the importance that high school computer science teachers place on a teachers' professional learning community designed around an inquiry- and equity-oriented approach for broadening participation in computing. Using grounded theory to analyze four years of teacher surveys and interviews from the Exploring Computer Science (ECS) program in the Los Angeles Unified School District, this article describes how participating in professional development activities purposefully aimed at fostering a teachers' professional learning community helps ECS teachers make the transition to an inquiry-based classroom culture and break professional isolation. This professional learning community also provides experiences that challenge prevalent deficit notions and stereotypes about which students can or cannot excel in computer science.

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

International Nuclear Information System (INIS)

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

1997-04-01

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

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

Science.gov (United States)

Goodwin, Bruce

2015-03-01

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

Software Applications on the Peregrine System | High-Performance Computing

Science.gov (United States)

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

Blaze-DEMGPU: Modular high performance DEM framework for the GPU architecture

Directory of Open Access Journals (Sweden)

Nicolin Govender

2016-01-01

Full Text Available Blaze-DEMGPU is a modular GPU based discrete element method (DEM framework that supports polyhedral shaped particles. The high level performance is attributed to the light weight and Single Instruction Multiple Data (SIMD that the GPU architecture offers. Blaze-DEMGPU offers suitable algorithms to conduct DEM simulations on the GPU and these algorithms can be extended and modified. Since a large number of scientific simulations are particle based, many of the algorithms and strategies for GPU implementation present in Blaze-DEMGPU can be applied to other fields. Blaze-DEMGPU will make it easier for new researchers to use high performance GPU computing as well as stimulate wider GPU research efforts by the DEM community.

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-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....

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

Energy Technology Data Exchange (ETDEWEB)

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

2013-10-01

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

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

KAUST Repository

Perovic, Nevena

2014-09-01

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

Computational Performance of a Parallelized Three-Dimensional High-Order Spectral Element Toolbox

Science.gov (United States)

Bosshard, Christoph; Bouffanais, Roland; Clémençon, Christian; Deville, Michel O.; Fiétier, Nicolas; Gruber, Ralf; Kehtari, Sohrab; Keller, Vincent; Latt, Jonas

In this paper, a comprehensive performance review of an MPI-based high-order three-dimensional spectral element method C++ toolbox is presented. The focus is put on the performance evaluation of several aspects with a particular emphasis on the parallel efficiency. The performance evaluation is analyzed with help of a time prediction model based on a parameterization of the application and the hardware resources. A tailor-made CFD computation benchmark case is introduced and used to carry out this review, stressing the particular interest for clusters with up to 8192 cores. Some problems in the parallel implementation have been detected and corrected. The theoretical complexities with respect to the number of elements, to the polynomial degree, and to communication needs are correctly reproduced. It is concluded that this type of code has a nearly perfect speed up on machines with thousands of cores, and is ready to make the step to next-generation petaflop machines.

Creating Small Learning Communities: Lessons from the Project on High-Performing Learning Communities about "What Works" in Creating Productive, Developmentally Enhancing, Learning Contexts

Science.gov (United States)

Felner, Robert D.; Seitsinger, Anne M.; Brand, Stephen; Burns, Amy; Bolton, Natalie

2007-01-01

Personalizing the school environment is a central goal of efforts to transform America's schools. Three decades of work by the Project on High Performance Learning Communities are considered that demonstrate the potential impact and importance of the creation of "small learning environments" on student motivation, adjustment, and well-being.…

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

Energy Technology Data Exchange (ETDEWEB)

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

2018-04-01

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

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.

High-Performance Networking

CERN Multimedia

CERN. Geneva

2003-01-01

The series will start with an historical introduction about what people saw as high performance message communication in their time and how that developed to the now to day known "standard computer network communication". It will be followed by a far more technical part that uses the High Performance Computer Network standards of the 90's, with 1 Gbit/sec systems as introduction for an in depth explanation of the three new 10 Gbit/s network and interconnect technology standards that exist already or emerge. If necessary for a good understanding some sidesteps will be included to explain important protocols as well as some necessary details of concerned Wide Area Network (WAN) standards details including some basics of wavelength multiplexing (DWDM). Some remarks will be made concerning the rapid expanding applications of networked storage.

A community computational challenge to predict the activity of pairs of compounds.

Science.gov (United States)

Bansal, Mukesh; Yang, Jichen; Karan, Charles; Menden, Michael P; Costello, James C; Tang, Hao; Xiao, Guanghua; Li, Yajuan; Allen, Jeffrey; Zhong, Rui; Chen, Beibei; Kim, Minsoo; Wang, Tao; Heiser, Laura M; Realubit, Ronald; Mattioli, Michela; Alvarez, Mariano J; Shen, Yao; Gallahan, Daniel; Singer, Dinah; Saez-Rodriguez, Julio; Xie, Yang; Stolovitzky, Gustavo; Califano, Andrea

2014-12-01

Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

The ongoing investigation of high performance parallel computing in HEP

CERN Document Server

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

1993-01-01

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

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

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

Energy Technology Data Exchange (ETDEWEB)

Karthik, Rajasekar [ORNL

2014-01-01

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

It Takes a Village: Supporting Inquiry- and Equity-Oriented Computer Science Pedagogy through a Professional Learning Community

Science.gov (United States)

Ryoo, Jean; Goode, Joanna; Margolis, Jane

2015-01-01

This article describes the importance that high school computer science teachers place on a teachers' professional learning community designed around an inquiry- and equity-oriented approach for broadening participation in computing. Using grounded theory to analyze four years of teacher surveys and interviews from the Exploring Computer Science…

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.

Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce.

Science.gov (United States)

Aji, Ablimit; Wang, Fusheng; Vo, Hoang; Lee, Rubao; Liu, Qiaoling; Zhang, Xiaodong; Saltz, Joel

2013-08-01

Support of high performance queries on large volumes of spatial data becomes increasingly important in many application domains, including geospatial problems in numerous fields, location based services, and emerging scientific applications that are increasingly data- and compute-intensive. The emergence of massive scale spatial data is due to the proliferation of cost effective and ubiquitous positioning technologies, development of high resolution imaging technologies, and contribution from a large number of community users. There are two major challenges for managing and querying massive spatial data to support spatial queries: the explosion of spatial data, and the high computational complexity of spatial queries. In this paper, we present Hadoop-GIS - a scalable and high performance spatial data warehousing system for running large scale spatial queries on Hadoop. Hadoop-GIS supports multiple types of spatial queries on MapReduce through spatial partitioning, customizable spatial query engine RESQUE, implicit parallel spatial query execution on MapReduce, and effective methods for amending query results through handling boundary objects. Hadoop-GIS utilizes global partition indexing and customizable on demand local spatial indexing to achieve efficient query processing. Hadoop-GIS is integrated into Hive to support declarative spatial queries with an integrated architecture. Our experiments have demonstrated the high efficiency of Hadoop-GIS on query response and high scalability to run on commodity clusters. Our comparative experiments have showed that performance of Hadoop-GIS is on par with parallel SDBMS and outperforms SDBMS for compute-intensive queries. Hadoop-GIS is available as a set of library for processing spatial queries, and as an integrated software package in Hive.

Community petascale project for accelerator science and simulation: Advancing computational science for future accelerators and accelerator technologies

International Nuclear Information System (INIS)

Spentzouris, P.; Cary, J.; McInnes, L.C.; Mori, W.; Ng, C.; Ng, E.; Ryne, R.

2008-01-01

The design and performance optimization of particle accelerators are essential for the success of the DOE scientific program in the next decade. Particle accelerators are very complex systems whose accurate description involves a large number of degrees of freedom and requires the inclusion of many physics processes. Building on the success of the SciDAC-1 Accelerator Science and Technology project, the SciDAC-2 Community Petascale Project for Accelerator Science and Simulation (ComPASS) is developing a comprehensive set of interoperable components for beam dynamics, electromagnetics, electron cooling, and laser/plasma acceleration modelling. ComPASS is providing accelerator scientists the tools required to enable the necessary accelerator simulation paradigm shift from high-fidelity single physics process modeling (covered under SciDAC1) to high-fidelity multiphysics modeling. Our computational frameworks have been used to model the behavior of a large number of accelerators and accelerator R and D experiments, assisting both their design and performance optimization. As parallel computational applications, the ComPASS codes have been shown to make effective use of thousands of processors.

New Challenges for Computing in High Energy Physics

International Nuclear Information System (INIS)

Santoro, Alberto

2003-01-01

In view of the new scientific programs established for the LHC (Large Hadron Collider) era, the way to face the technological challenges in computing was develop a new concept of GRID computing. We show some examples and, in particular, a proposal for high energy physicists in countries like Brazil. Due to the big amount of data and the need of close collaboration it will be impossible to work in research centers and universities very far from Fermilab or CERN unless a GRID architecture is built. An important effort is being made by the international community to up to date their computing infrastructure and networks

Twenty-First Century Learning: Communities, Interaction and Ubiquitous Computing

Science.gov (United States)

Leh, Amy S.C.; Kouba, Barbara; Davis, Dirk

2005-01-01

Advanced technology makes 21st century learning, communities and interactions unique and leads people to an era of ubiquitous computing. The purpose of this article is to contribute to the discussion of learning in the 21st century. The paper will review literature on learning community, community learning, interaction, 21st century learning and…

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).

Computational fluid dynamics (CFD) assisted performance evaluation of the Twincer (TM) disposable high-dose dry powder inhaler

NARCIS (Netherlands)

de Boer, Anne H.; Hagedoorn, Paul; Woolhouse, Robert; Wynn, Ed

Objectives To use computational fluid dynamics (CFD) for evaluating and understanding the performance of the high-dose disposable Twincer (TM) dry powder inhaler, as well as to learn the effect of design modifications on dose entrainment, powder dispersion and retention behaviour. Methods Comparison

Big Data and High-Performance Computing in Global Seismology

Science.gov (United States)

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

2014-05-01

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

Community Design Parameters and the Performance of Residential Cogeneration Systems

Directory of Open Access Journals (Sweden)

Hazem Rashed-Ali

2012-11-01

Full Text Available The integration of cogeneration systems in residential and mixed-use communities has the potential of reducing their energy demand and harmful emissions and can thus play asignificant role in increasing their environmental sustainability. This study investigated the impact of selected planning and architectural design parameters on the environmental and economic performances of centralized cogeneration systems integrated into residential communities in U.S.cold climates. Parameters investigated include: 1 density, 2 use mix, 3 street configuration, 4 housing typology, 5 envelope and building systems’ efficiencies, and 6 passive solar energyutilization. The study integrated several simulation tools into a procedure to assess the impact of each design parameter on the cogeneration system performance. This assessment procedure included: developing a base-line model representing typical design characteristics of U.S. residential communities; assessing the cogeneration system’s performance within this model using three performance indicators: percentage of reduction in primary energy use, percentage of reduction in CO2 emissions; and internal rate of return; assessing the impact of each parameter on the system performance through developing 46 design variations of the base-line model representing potential changes in each parameter and calculating the three indicators for each variation; and finally, using a multi-attribute decision analysis methodology to evaluate the relative impact of each parameter on the cogeneration system performance. The study results show that planning parameters had a higher impact on the cogeneration system performance than architectural ones. Also, a significant correlation was found between design characteristics identified as favorable for the cogeneration system performance and those of sustainable residential communities. These include high densities, high use mix, interconnected street networks, and mixing of

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...

High-Performance Operating Systems

DEFF Research Database (Denmark)

Sharp, Robin

1999-01-01

Notes prepared for the DTU course 49421 "High Performance Operating Systems". The notes deal with quantitative and qualitative techniques for use in the design and evaluation of operating systems in computer systems for which performance is an important parameter, such as real-time applications......, communication systems and multimedia systems....

Detecting highly overlapping community structure by greedy clique expansion

OpenAIRE

Lee, Conrad; Reid, Fergal; McDaid, Aaron; Hurley, Neil

2010-01-01

In complex networks it is common for each node to belong to several communities, implying a highly overlapping community structure. Recent advances in benchmarking indicate that existing community assignment algorithms that are capable of detecting overlapping communities perform well only when the extent of community overlap is kept to modest levels. To overcome this limitation, we introduce a new community assignment algorithm called Greedy Clique Expansion (GCE). The algorithm identifies d...

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

The role of anxiety symptoms in school performance in a community sample of children and adolescents

Directory of Open Access Journals (Sweden)

D'Arrigo Valentina

2007-12-01

Full Text Available Abstract Background Anxiety symptoms are relatively common among children and adolescents and can interfere with functioning. The prevalence of anxiety and the relationship between anxiety and school performance were examined among elementary, middle, and high school students. Methods Samples of elementary (N = 131, age 8–10 years, middle (N = 267, age 11–13 years, and high school (N = 80, age 14–16 years children were recruited from four public schools in a predominantly middle-class community in Catania, Italy. Children completed the Multidimensional Anxiety Scale for Children (MASC. T-scores were computed for the MASC total scores, and considered to be in the anxious range if 65 or above. Current academic grades were obtained from school records. Results Of the 478 children, 35 (7.3% had a MASC T-score in the anxious range. The rate of children in the anxious range was 2.3% in elementary, 7.9% in middle, and 15.9% in high school (χ2 = 7.8, df = 2, p 2 = 11.68, df = 2, p Conclusion In this community sample of children and adolescents attending elementary through high school, the prevalence of abnormally high self-reported levels of anxiety increased in frequency with age and was negatively associated with school performance.

HPC-NMF: A High-Performance Parallel Algorithm for Nonnegative Matrix Factorization

Energy Technology Data Exchange (ETDEWEB)

2016-08-22

NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient distributed algorithms to solve the problem for big data sets. We propose a high-performance distributed-memory parallel algorithm that computes the factorization by iteratively solving alternating non-negative least squares (NLS) subproblems for $\\WW$ and $\\HH$. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). As opposed to previous implementation, our algorithm is also flexible: It performs well for both dense and sparse matrices, and allows the user to choose any one of the multiple algorithms for solving the updates to low rank factors $\\WW$ and $\\HH$ within the alternating iterations.

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

International Nuclear Information System (INIS)

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

2005-11-01

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

Imprinting Community College Computer Science Education with Software Engineering Principles

Science.gov (United States)

Hundley, Jacqueline Holliday

Although the two-year curriculum guide includes coverage of all eight software engineering core topics, the computer science courses taught in Alabama community colleges limit student exposure to the programming, or coding, phase of the software development lifecycle and offer little experience in requirements analysis, design, testing, and maintenance. We proposed that some software engineering principles can be incorporated into the introductory-level of the computer science curriculum. Our vision is to give community college students a broader exposure to the software development lifecycle. For those students who plan to transfer to a baccalaureate program subsequent to their community college education, our vision is to prepare them sufficiently to move seamlessly into mainstream computer science and software engineering degrees. For those students who plan to move from the community college to a programming career, our vision is to equip them with the foundational knowledge and skills required by the software industry. To accomplish our goals, we developed curriculum modules for teaching seven of the software engineering knowledge areas within current computer science introductory-level courses. Each module was designed to be self-supported with suggested learning objectives, teaching outline, software tool support, teaching activities, and other material to assist the instructor in using it.

Running climate model on a commercial cloud computing environment: A case study using Community Earth System Model (CESM) on Amazon AWS

Science.gov (United States)

Chen, Xiuhong; Huang, Xianglei; Jiao, Chaoyi; Flanner, Mark G.; Raeker, Todd; Palen, Brock

2017-01-01

The suites of numerical models used for simulating climate of our planet are usually run on dedicated high-performance computing (HPC) resources. This study investigates an alternative to the usual approach, i.e. carrying out climate model simulations on commercially available cloud computing environment. We test the performance and reliability of running the CESM (Community Earth System Model), a flagship climate model in the United States developed by the National Center for Atmospheric Research (NCAR), on Amazon Web Service (AWS) EC2, the cloud computing environment by Amazon.com, Inc. StarCluster is used to create virtual computing cluster on the AWS EC2 for the CESM simulations. The wall-clock time for one year of CESM simulation on the AWS EC2 virtual cluster is comparable to the time spent for the same simulation on a local dedicated high-performance computing cluster with InfiniBand connections. The CESM simulation can be efficiently scaled with the number of CPU cores on the AWS EC2 virtual cluster environment up to 64 cores. For the standard configuration of the CESM at a spatial resolution of 1.9° latitude by 2.5° longitude, increasing the number of cores from 16 to 64 reduces the wall-clock running time by more than 50% and the scaling is nearly linear. Beyond 64 cores, the communication latency starts to outweigh the benefit of distributed computing and the parallel speedup becomes nearly unchanged.

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

Energy Technology Data Exchange (ETDEWEB)

Wang, Jun

2011-06-22

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

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

Energy Technology Data Exchange (ETDEWEB)

Hamlet, Jason R.; Keliiaa, Curtis M.

2010-09-01

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

Preparing for Further Introduction of Computing Technology in Vancouver Community College Instruction. Report of the Instructional Computing Committee.

Science.gov (United States)

Vancouver Community Coll., British Columbia.

After examining the impact of changing technology on postsecondary instruction and on the tools needed for instruction, this report analyzes the status and offers recommendations concerning the future of instructional computing at Vancouver Community College (VCC) in British Columbia. Section I focuses on the use of computers in community college…

A Computer Simulation of Community Pharmacy Practice for Educational Use.

Science.gov (United States)

Bindoff, Ivan; Ling, Tristan; Bereznicki, Luke; Westbury, Juanita; Chalmers, Leanne; Peterson, Gregory; Ollington, Robert

2014-11-15

To provide a computer-based learning method for pharmacy practice that is as effective as paper-based scenarios, but more engaging and less labor-intensive. We developed a flexible and customizable computer simulation of community pharmacy. Using it, the students would be able to work through scenarios which encapsulate the entirety of a patient presentation. We compared the traditional paper-based teaching method to our computer-based approach using equivalent scenarios. The paper-based group had 2 tutors while the computer group had none. Both groups were given a prescenario and postscenario clinical knowledge quiz and survey. Students in the computer-based group had generally greater improvements in their clinical knowledge score, and third-year students using the computer-based method also showed more improvements in history taking and counseling competencies. Third-year students also found the simulation fun and engaging. Our simulation of community pharmacy provided an educational experience as effective as the paper-based alternative, despite the lack of a human tutor.

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

Science.gov (United States)

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

2018-01-01

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

High performance GPU processing for inversion using uniform grid searches

Science.gov (United States)

Venetis, Ioannis E.; Saltogianni, Vasso; Stiros, Stathis; Gallopoulos, Efstratios

2017-04-01

Many geophysical problems are described by systems of redundant, highly non-linear systems of ordinary equations with constant terms deriving from measurements and hence representing stochastic variables. Solution (inversion) of such problems is based on numerical, optimization methods, based on Monte Carlo sampling or on exhaustive searches in cases of two or even three "free" unknown variables. Recently the TOPological INVersion (TOPINV) algorithm, a grid search-based technique in the Rn space, has been proposed. TOPINV is not based on the minimization of a certain cost function and involves only forward computations, hence avoiding computational errors. The basic concept is to transform observation equations into inequalities on the basis of an optimization parameter k and of their standard errors, and through repeated "scans" of n-dimensional search grids for decreasing values of k to identify the optimal clusters of gridpoints which satisfy observation inequalities and by definition contain the "true" solution. Stochastic optimal solutions and their variance-covariance matrices are then computed as first and second statistical moments. Such exhaustive uniform searches produce an excessive computational load and are extremely time consuming for common computers based on a CPU. An alternative is to use a computing platform based on a GPU, which nowadays is affordable to the research community, which provides a much higher computing performance. Using the CUDA programming language to implement TOPINV allows the investigation of the attained speedup in execution time on such a high performance platform. Based on synthetic data we compared the execution time required for two typical geophysical problems, modeling magma sources and seismic faults, described with up to 18 unknown variables, on both CPU/FORTRAN and GPU/CUDA platforms. The same problems for several different sizes of search grids (up to 1012 gridpoints) and numbers of unknown variables were solved on

HPTA: High-Performance Text Analytics

OpenAIRE

Vandierendonck, Hans; Murphy, Karen; Arif, Mahwish; Nikolopoulos, Dimitrios S.

2017-01-01

One of the main targets of data analytics is unstructured data, which primarily involves textual data. High-performance processing of textual data is non-trivial. We present the HPTA library for high-performance text analytics. The library helps programmers to map textual data to a dense numeric representation, which can be handled more efficiently. HPTA encapsulates three performance optimizations: (i) efficient memory management for textual data, (ii) parallel computation on associative dat...

Performance comparison between Java and JNI for optimal implementation of computational micro-kernels

OpenAIRE

Halli , Nassim; Charles , Henri-Pierre; Méhaut , Jean-François

2015-01-01

International audience; General purpose CPUs used in high performance computing (HPC) support a vector instruction set and an out-of-order engine dedicated to increase the instruction level parallelism. Hence, related optimizations are currently critical to improve the performance of applications requiring numerical computation. Moreover, the use of a Java run-time environment such as the HotSpot Java Virtual Machine (JVM) in high performance computing is a promising alternative. It benefits ...

Validation of the solar heating and cooling high speed performance (HISPER) computer code

Science.gov (United States)

Wallace, D. B.

1980-01-01

Developed to give a quick and accurate predictions HISPER, a simplification of the TRNSYS program, achieves its computational speed by not simulating detailed system operations or performing detailed load computations. In order to validate the HISPER computer for air systems the simulation was compared to the actual performance of an operational test site. Solar insolation, ambient temperature, water usage rate, and water main temperatures from the data tapes for an office building in Huntsville, Alabama were used as input. The HISPER program was found to predict the heating loads and solar fraction of the loads with errors of less than ten percent. Good correlation was found on both a seasonal basis and a monthly basis. Several parameters (such as infiltration rate and the outside ambient temperature above which heating is not required) were found to require careful selection for accurate simulation.

Advanced Certification Program for Computer Graphic Specialists. Final Performance Report.

Science.gov (United States)

Parkland Coll., Champaign, IL.

A pioneer program in computer graphics was implemented at Parkland College (Illinois) to meet the demand for specialized technicians to visualize data generated on high performance computers. In summer 1989, 23 students were accepted into the pilot program. Courses included C programming, calculus and analytic geometry, computer graphics, and…

Peregrine System | High-Performance Computing | NREL

Science.gov (United States)

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

High-Performance Computer Modeling of the Cosmos-Iridium Collision

Energy Technology Data Exchange (ETDEWEB)

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

2009-08-28

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

The Future of Software Engineering for High Performance Computing

Energy Technology Data Exchange (ETDEWEB)

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

2015-07-16

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

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

Science.gov (United States)

Torrent, Marc

2014-03-01

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

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.

Modification in the FUDA computer code to predict fuel performance at high burnup

Energy Technology Data Exchange (ETDEWEB)

Das, M; Arunakumar, B V; Prasad, P N [Nuclear Power Corp., Mumbai (India)

1997-08-01

The computer code FUDA (FUel Design Analysis) participated in the blind exercises organized by the IAEA CRP (Co-ordinated Research Programme) on FUMEX (Fuel Modelling at Extended Burnup). While the code prediction compared well with the experiments at Halden under various parametric and operating conditions, the fission gas release and fission gas pressure were found to be slightly over-predicted, particularly at high burnups. In view of the results of 6 FUMEX cases, the main models and submodels of the code were reviewed and necessary improvements were made. The new version of the code FUDA MOD 2 is now able to predict fuel performance parameter for burn-ups up to 50000 MWD/TeU. The validation field of the code has been extended to prediction of thorium oxide fuel performance. An analysis of local deformations at pellet interfaces and near the end caps is carried out considering the hourglassing of the pellet by finite element technique. (author). 15 refs, 1 fig.

Modification in the FUDA computer code to predict fuel performance at high burnup

International Nuclear Information System (INIS)

Das, M.; Arunakumar, B.V.; Prasad, P.N.

1997-01-01

The computer code FUDA (FUel Design Analysis) participated in the blind exercises organized by the IAEA CRP (Co-ordinated Research Programme) on FUMEX (Fuel Modelling at Extended Burnup). While the code prediction compared well with the experiments at Halden under various parametric and operating conditions, the fission gas release and fission gas pressure were found to be slightly over-predicted, particularly at high burnups. In view of the results of 6 FUMEX cases, the main models and submodels of the code were reviewed and necessary improvements were made. The new version of the code FUDA MOD 2 is now able to predict fuel performance parameter for burn-ups up to 50000 MWD/TeU. The validation field of the code has been extended to prediction of thorium oxide fuel performance. An analysis of local deformations at pellet interfaces and near the end caps is carried out considering the hourglassing of the pellet by finite element technique. (author). 15 refs, 1 fig

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

Science.gov (United States)

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

2017-01-01

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

Trends in life science grid: from computing grid to knowledge grid

Directory of Open Access Journals (Sweden)

Konagaya Akihiko

2006-12-01

Full Text Available Abstract Background Grid computing has great potential to become a standard cyberinfrastructure for life sciences which often require high-performance computing and large data handling which exceeds the computing capacity of a single institution. Results This survey reviews the latest grid technologies from the viewpoints of computing grid, data grid and knowledge grid. Computing grid technologies have been matured enough to solve high-throughput real-world life scientific problems. Data grid technologies are strong candidates for realizing "resourceome" for bioinformatics. Knowledge grids should be designed not only from sharing explicit knowledge on computers but also from community formulation for sharing tacit knowledge among a community. Conclusion Extending the concept of grid from computing grid to knowledge grid, it is possible to make use of a grid as not only sharable computing resources, but also as time and place in which people work together, create knowledge, and share knowledge and experiences in a community.

Design and Implementation of High-Performance GIS Dynamic Objects Rendering Engine

Science.gov (United States)

Zhong, Y.; Wang, S.; Li, R.; Yun, W.; Song, G.

2017-12-01

Spatio-temporal dynamic visualization is more vivid than static visualization. It important to use dynamic visualization techniques to reveal the variation process and trend vividly and comprehensively for the geographical phenomenon. To deal with challenges caused by dynamic visualization of both 2D and 3D spatial dynamic targets, especially for different spatial data types require high-performance GIS dynamic objects rendering engine. The main approach for improving the rendering engine with vast dynamic targets relies on key technologies of high-performance GIS, including memory computing, parallel computing, GPU computing and high-performance algorisms. In this study, high-performance GIS dynamic objects rendering engine is designed and implemented for solving the problem based on hybrid accelerative techniques. The high-performance GIS rendering engine contains GPU computing, OpenGL technology, and high-performance algorism with the advantage of 64-bit memory computing. It processes 2D, 3D dynamic target data efficiently and runs smoothly with vast dynamic target data. The prototype system of high-performance GIS dynamic objects rendering engine is developed based SuperMap GIS iObjects. The experiments are designed for large-scale spatial data visualization, the results showed that the high-performance GIS dynamic objects rendering engine have the advantage of high performance. Rendering two-dimensional and three-dimensional dynamic objects achieve 20 times faster on GPU than on CPU.

International Conference: Computer-Aided Design of High-Temperature Materials

National Research Council Canada - National Science Library

Kalia, Rajiv

1998-01-01

.... The conference was attended by experimental and computational materials scientists, and experts in high performance computing and communications from universities, government laboratories, and industries in the U.S., Europe, and Japan...

High performance data transfer

Science.gov (United States)

Cottrell, R.; Fang, C.; Hanushevsky, A.; Kreuger, W.; Yang, W.

2017-10-01

The exponentially increasing need for high speed data transfer is driven by big data, and cloud computing together with the needs of data intensive science, High Performance Computing (HPC), defense, the oil and gas industry etc. We report on the Zettar ZX software. This has been developed since 2013 to meet these growing needs by providing high performance data transfer and encryption in a scalable, balanced, easy to deploy and use way while minimizing power and space utilization. In collaboration with several commercial vendors, Proofs of Concept (PoC) consisting of clusters have been put together using off-the- shelf components to test the ZX scalability and ability to balance services using multiple cores, and links. The PoCs are based on SSD flash storage that is managed by a parallel file system. Each cluster occupies 4 rack units. Using the PoCs, between clusters we have achieved almost 200Gbps memory to memory over two 100Gbps links, and 70Gbps parallel file to parallel file with encryption over a 5000 mile 100Gbps link.

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

Science.gov (United States)

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

2017-12-01

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

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

Science.gov (United States)

Trudgian, David C; Mirzaei, Hamid

2012-12-07

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

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

Directory of Open Access Journals (Sweden)

Ruijian Zhang

2017-12-01

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

The performance of a new Geant4 Bertini intra-nuclear cascade model in high throughput computing (HTC) cluster architecture

Energy Technology Data Exchange (ETDEWEB)

Aatos, Heikkinen; Andi, Hektor; Veikko, Karimaki; Tomas, Linden [Helsinki Univ., Institute of Physics (Finland)

2003-07-01

We study the performance of a new Bertini intra-nuclear cascade model implemented in the general detector simulation tool-kit Geant4 with a High Throughput Computing (HTC) cluster architecture. A 60 node Pentium III open-Mosix cluster is used with the Mosix kernel performing automatic process load-balancing across several CPUs. The Mosix cluster consists of several computer classes equipped with Windows NT workstations that automatically boot, daily and become nodes of the Mosix cluster. The models included in our study are a Bertini intra-nuclear cascade model with excitons, consisting of a pre-equilibrium model, a nucleus explosion model, a fission model and an evaporation model. The speed and accuracy obtained for these models is presented. (authors)

High-resolution phylogenetic microbial community profiling

Energy Technology Data Exchange (ETDEWEB)

Singer, Esther; Coleman-Derr, Devin; Bowman, Brett; Schwientek, Patrick; Clum, Alicia; Copeland, Alex; Ciobanu, Doina; Cheng, Jan-Fang; Gies, Esther; Hallam, Steve; Tringe, Susannah; Woyke, Tanja

2014-03-17

The representation of bacterial and archaeal genome sequences is strongly biased towards cultivated organisms, which belong to merely four phylogenetic groups. Functional information and inter-phylum level relationships are still largely underexplored for candidate phyla, which are often referred to as microbial dark matter. Furthermore, a large portion of the 16S rRNA gene records in the GenBank database are labeled as environmental samples and unclassified, which is in part due to low read accuracy, potential chimeric sequences produced during PCR amplifications and the low resolution of short amplicons. In order to improve the phylogenetic classification of novel species and advance our knowledge of the ecosystem function of uncultivated microorganisms, high-throughput full length 16S rRNA gene sequencing methodologies with reduced biases are needed. We evaluated the performance of PacBio single-molecule real-time (SMRT) sequencing in high-resolution phylogenetic microbial community profiling. For this purpose, we compared PacBio and Illumina metagenomic shotgun and 16S rRNA gene sequencing of a mock community as well as of an environmental sample from Sakinaw Lake, British Columbia. Sakinaw Lake is known to contain a large age of microbial species from candidate phyla. Sequencing results show that community structure based on PacBio shotgun and 16S rRNA gene sequences is highly similar in both the mock and the environmental communities. Resolution power and community representation accuracy from SMRT sequencing data appeared to be independent of GC content of microbial genomes and was higher when compared to Illumina-based metagenome shotgun and 16S rRNA gene (iTag) sequences, e.g. full-length sequencing resolved all 23 OTUs in the mock community, while iTags did not resolve closely related species. SMRT sequencing hence offers various potential benefits when characterizing uncharted microbial communities.

Computational fluid dynamics (CFD) assisted performance evaluation of the Twincer™ disposable high-dose dry powder inhaler.

Science.gov (United States)

de Boer, Anne H; Hagedoorn, Paul; Woolhouse, Robert; Wynn, Ed

2012-09-01

To use computational fluid dynamics (CFD) for evaluating and understanding the performance of the high-dose disposable Twincer™ dry powder inhaler, as well as to learn the effect of design modifications on dose entrainment, powder dispersion and retention behaviour. Comparison of predicted flow and particle behaviour from CFD computations with experimental data obtained with cascade impactor and laser diffraction analysis. Inhaler resistance, flow split, particle trajectories and particle residence times can well be predicted with CFD for a multiple classifier based inhaler like the Twincer™. CFD computations showed that the flow split of the Twincer™ is independent of the pressure drop across the inhaler and that the total flow rate can be decreased without affecting the dispersion efficacy or retention behaviour. They also showed that classifier symmetry can be improved by reducing the resistance of one of the classifier bypass channels, which for the current concept does not contribute to the swirl in the classifier chamber. CFD is a highly valuable tool for development and optimisation of dry powder inhalers. CFD can assist adapting the inhaler design to specific physico-chemical properties of the drug formulation with respect to dispersion and retention behaviour. © 2012 The Authors. JPP © 2012 Royal Pharmaceutical Society.

Introduction to massively-parallel computing in high-energy physics

CERN Document Server

AUTHOR|(CDS)2083520

1993-01-01

Ever since computers were first used for scientific and numerical work, there has existed an "arms race" between the technical development of faster computing hardware, and the desires of scientists to solve larger problems in shorter time-scales. However, the vast leaps in processor performance achieved through advances in semi-conductor science have reached a hiatus as the technology comes up against the physical limits of the speed of light and quantum effects. This has lead all high performance computer manufacturers to turn towards a parallel architecture for their new machines. In these lectures we will introduce the history and concepts behind parallel computing, and review the various parallel architectures and software environments currently available. We will then introduce programming methodologies that allow efficient exploitation of parallel machines, and present case studies of the parallelization of typical High Energy Physics codes for the two main classes of parallel computing architecture (S...

Distributed metadata in a high performance computing environment

Science.gov (United States)

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

2017-07-11

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

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)

High performance computing network for cloud environment using simulators

OpenAIRE

Singh, N. Ajith; Hemalatha, M.

2012-01-01

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

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)

The Convergence of High Performance Computing and Large Scale Data Analytics

Science.gov (United States)

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

2015-12-01

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

Case Study of Leadership Practices and School-Community Interrelationships in High-Performing, High-Poverty, Rural California High Schools

Science.gov (United States)

Masumoto, Marcia; Brown-Welty, Sharon

2009-01-01

Many rural California high schools are impacted by the disadvantages of poverty, non-English speaking students, limited resources, changing demographics, and challenges of the rural context. Focusing on contemporary leadership theories and school-community interrelationships, this qualitative study examines the practices of educational leaders in…

Computer Simulation Performed for Columbia Project Cooling System

Science.gov (United States)

Ahmad, Jasim

2005-01-01

This demo shows a high-fidelity simulation of the air flow in the main computer room housing the Columbia (10,024 intel titanium processors) system. The simulation asseses the performance of the cooling system and identified deficiencies, and recommended modifications to eliminate them. It used two in house software packages on NAS supercomputers: Chimera Grid tools to generate a geometric model of the computer room, OVERFLOW-2 code for fluid and thermal simulation. This state-of-the-art technology can be easily extended to provide a general capability for air flow analyses on any modern computer room. Columbia_CFD_black.tiff

Metaproteomics: Harnessing the power of high performance mass spectrometry to identify the suite of proteins that control metabolic activities in microbial communities

Science.gov (United States)

Hettich, Robert L.; Pan, Chongle; Chourey, Karuna; Giannone, Richard J.

2013-01-01

Summary The availability of extensive genome information for many different microbes, including unculturable species in mixed communities from environmental samples, has enabled systems-biology interrogation by providing a means to access genomic, transcriptomic, and proteomic information. To this end, metaproteomics exploits the power of high performance mass spectrometry for extensive characterization of the complete suite of proteins expressed by a microbial community in an environmental sample. PMID:23469896

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-01-05

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

Federal High End Computing (HEC) Information Portal

Data.gov (United States)

Networking and Information Technology Research and Development, Executive Office of the President — This portal provides information about opportunities to engage in U.S. Federal government high performance computing activities, including supercomputer use,...

High-Performance Schools: Affordable Green Design for K-12 Schools; Preprint

Energy Technology Data Exchange (ETDEWEB)

Plympton, P.; Brown, J.; Stevens, K.

2004-08-01

Schools in the United States spend $7.8 billion on energy each year-more than the cost of computers and textbooks combined, according to a 2003 report from the National Center for Education Statistics. The U.S. Department of Energy (DOE) estimates that these high utility bills could be reduced as much as 25% if schools adopt readily available high performance design principles and technologies. Accordingly, hundreds of K-12 schools across the country have made a commitment to improve the learning and teaching environment of schools while saving money and energy and protecting the environment. DOE and its public- and private-sector partners have developed Energy Design Guidelines for High Performance Schools, customized for nine climate zones in U.S. states and territories. These design guidelines provide information for school decision makers and design professionals on the advantages of energy efficiency and renewable energy designs and technologies. With such features as natural day lighting, efficient electric lights, water conservation, and renewable energy, schools in all types of climates are proving that school buildings, and the students and teachers who occupy them, are indeed high performers. This paper describes high performance schools from each of the nine climate zones associated with the Energy Design Guidelines. The nine case studies focus on the high performance design strategies implemented in each school, as well as the cost savings and benefits realized by students, faculty, the community, and the environment.

High performance cloud auditing and applications

CERN Document Server

Choi, Baek-Young; Song, Sejun

2014-01-01

This book mainly focuses on cloud security and high performance computing for cloud auditing. The book discusses emerging challenges and techniques developed for high performance semantic cloud auditing, and presents the state of the art in cloud auditing, computing and security techniques with focus on technical aspects and feasibility of auditing issues in federated cloud computing environments.   In summer 2011, the United States Air Force Research Laboratory (AFRL) CyberBAT Cloud Security and Auditing Team initiated the exploration of the cloud security challenges and future cloud auditing research directions that are covered in this book. This work was supported by the United States government funds from the Air Force Office of Scientific Research (AFOSR), the AFOSR Summer Faculty Fellowship Program (SFFP), the Air Force Research Laboratory (AFRL) Visiting Faculty Research Program (VFRP), the National Science Foundation (NSF) and the National Institute of Health (NIH). All chapters were partially suppor...

Long-term high-solids anaerobic digestion of food waste: Effects of ammonia on process performance and microbial community.

Science.gov (United States)

Peng, Xuya; Zhang, ShangYi; Li, Lei; Zhao, Xiaofei; Ma, Yao; Shi, Dezhi

2018-04-22

A long-term high solids anaerobic digestion of food waste was conducted to identify microbial mechanisms of ammonia inhibition during digestion and to clarify correlations between ammonia accumulation, microbial community dynamics (diversity, composition, and interactions), and process stability. Results show that the effects of ammonia on process performance and microbial community were indirectly caused by volatile fatty acid accumulation. Excess free ammonia blocked acetate metabolism, leading to process instability. Accumulated acetate caused feedback inhibition at the acetogenesis stage, which resulted in considerable accumulation of propionate, valerate, and other long-chain fatty acids. This high concentration of volatile fatty acids reduced the abundance of syntrophic acetogenic bacteria and allowed hydrolytic fermentative bacteria to dominate. The normally interactive and orderly metabolic network was broken, which further exacerbated the process instability. These results improve the understanding of microbial mechanisms which contribute to process instability and provide guidance for the microbial management of anaerobic digesters. Copyright © 2018 Elsevier Ltd. All rights reserved.

Performance Evaluation of a Hot-Humid Climate Community

Energy Technology Data Exchange (ETDEWEB)

Osser, R. [Building Science Corporation, Somerville, MA (United States); Kerrigan, P. [Building Science Corporation, Somerville, MA (United States)

2012-02-01

This report describes the Project Home Again community in New Orleans, a new development for high-performance, affordable homes for residents who lost their homes to Hurricane Katrina. Building Science Corporation acted as a consultant for the project, advocating design strategies for durability, flood resistance, occupant comfort, and low energy use while maintaining cost effectiveness.

Reduction of community alcohol problems: computer simulation experiments in three counties.

Science.gov (United States)

Holder, H D; Blose, J O

1987-03-01

A series of alcohol abuse prevention strategies was evaluated using computer simulation for three counties in the United States: Wake County, North Carolina, Washington County, Vermont and Alameda County, California. A system dynamics model composed of a network of interacting variables was developed for the pattern of alcoholic beverage consumption in a community. The relationship of community drinking patterns to various stimulus factors was specified in the model based on available empirical research. Stimulus factors included disposable income, alcoholic beverage prices, advertising exposure, minimum drinking age and changes in cultural norms. After a generic model was developed and validated on the national level, a computer-based system dynamics model was developed for each county, and a series of experiments was conducted to project the potential impact of specific prevention strategies. The project concluded that prevention efforts can both lower current levels of alcohol abuse and reduce projected increases in alcohol-related problems. Without such efforts, already high levels of alcohol-related family disruptions in the three counties could be expected to rise an additional 6% and drinking-related work problems 1-5%, over the next 10 years after controlling for population growth. Of the strategies tested, indexing the price of alcoholic beverages to the consumer price index in conjunction with the implementation of a community educational program with well-defined target audiences has the best potential for significant problem reduction in all three counties.

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.

New Mexico High School Supercomputing Challenge, 1990--1995: Five years of making a difference to students, teachers, schools, and communities. Progress report

Energy Technology Data Exchange (ETDEWEB)

Foster, M.; Kratzer, D.

1996-02-01

The New Mexico High School Supercomputing Challenge is an academic program dedicated to increasing interest in science and math among high school students by introducing them to high performance computing. This report provides a summary and evaluation of the first five years of the program, describes the program and shows the impact that it has had on high school students, their teachers, and their communities. Goals and objectives are reviewed and evaluated, growth and development of the program are analyzed, and future directions are discussed.

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

Science.gov (United States)

2009-09-23

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

The HEPCloud Facility: elastic computing for High Energy Physics - The NOvA Use Case

Science.gov (United States)

Fuess, S.; Garzoglio, G.; Holzman, B.; Kennedy, R.; Norman, A.; Timm, S.; Tiradani, A.

2017-10-01

The need for computing in the HEP community follows cycles of peaks and valleys mainly driven by conference dates, accelerator shutdown, holiday schedules, and other factors. Because of this, the classical method of provisioning these resources at providing facilities has drawbacks such as potential overprovisioning. As the appetite for computing increases, however, so does the need to maximize cost efficiency by developing a model for dynamically provisioning resources only when needed. To address this issue, the HEPCloud project was launched by the Fermilab Scientific Computing Division in June 2015. Its goal is to develop a facility that provides a common interface to a variety of resources, including local clusters, grids, high performance computers, and community and commercial Clouds. Initially targeted experiments include CMS and NOvA, as well as other Fermilab stakeholders. In its first phase, the project has demonstrated the use of the “elastic” provisioning model offered by commercial clouds, such as Amazon Web Services. In this model, resources are rented and provisioned automatically over the Internet upon request. In January 2016, the project demonstrated the ability to increase the total amount of global CMS resources by 58,000 cores from 150,000 cores - a 38 percent increase - in preparation for the Recontres de Moriond. In March 2016, the NOvA experiment has also demonstrated resource burst capabilities with an additional 7,300 cores, achieving a scale almost four times as large as the local allocated resources and utilizing the local AWS s3 storage to optimize data handling operations and costs. NOvA was using the same familiar services used for local computations, such as data handling and job submission, in preparation for the Neutrino 2016 conference. In both cases, the cost was contained by the use of the Amazon Spot Instance Market and the Decision Engine, a HEPCloud component that aims at minimizing cost and job interruption. This paper

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

Energy Technology Data Exchange (ETDEWEB)

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

1997-08-20

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

Class modality, student characteristics, and performance in a community college introductory STEM course

Science.gov (United States)

Fogle, Thomas Ty

Research on introductory STEM course performance has indicated that student characteristics (age, ethnicity and gender) and Grade Point Average (G.P.A.) can be predictive of student performance, and by implication, a correlation among these factors can help determine course design interventions to help certain types of students perform well in introductory STEM courses. The basis of this study was a community college Visual Basic programming course taught in both online and hybrid format. Beginning students in this course represented a diverse population residing in a large, mid-western, city and surrounding communities. Many of these students were defined as "at-Risk" or "non-traditional, which generally means any combination of socio-economic, cultural, family and employment factors that indicate a student is non-traditional. Research has shown these students struggle academically in technologically dense STEM courses, and may require student services and support to achieve their individual performance goals. The overall number in the study range was 392 distance students and 287 blended course students. The main question of this research was to determine to what extent student characteristics in a community college context, and previous success, as measured in overall G.P.A., were related to course performance in an introductory Visual Basic programming (STEM) course; and, whether or not a combination of these factors and course modality was predictive of success. The study employed a quantitative, quasi-experimental design to assess whether students' course performance was linked to course modality, student characteristics and overall G.P.A. The results indicated that the only predictor of student performance was overall G.P.A. Despite the research analyzed in Chapter 2, there was no statistically significant relationship to modality, age, ethnicity, or gender to performance in the course. Cognitive load is significant in a computer programming course and it

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

Science.gov (United States)

da Silveira, Pedro Rodrigo Castro

2014-01-01

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

Gender Differences in Introductory University Physics Performance: The Influence of High School Physics Preparation and Affect

Science.gov (United States)

Hazari, Zahra

2006-12-01

The attrition of females studying physics after high school has been a continuing concern for the physics education community. If females are well prepared, feel confident, and do well in introductory college physics, they may be inclined to study physics further. This quantitative study uses HLM to identify factors from high school physics preparation (content, pedagogy, and assessment) and the affective domain that predict female and male performance in introductory college physics. The study includes controls for student demographic and academic background characteristics, and the final dataset consists of 1973 surveys from 54 introductory college physics classes. The results highlight high school physics and affective experiences that differentially predict female and male performance. These experiences include: learning requirements, computer graphing/analysis, long written problems, everyday world examples, community projects cumulative tests/quizzes, father's encouragement, family's belief that science leads to a better career, and the length of time students believe that high school physics would help in university physics. There were also experiences that similarly predict female and male performance. The results paint a dynamic picture of the factors from high school physics and the affective domain that influence the future physics performance of females and males. The implication is that there are many aspects to the teaching of physics in high school that, although widely used and thought to be effective, need reform in their implementation in order to be fully beneficial to females and/or males in college.

Play for Performance: Using Computer Games to Improve Motivation and Test-Taking Performance

Science.gov (United States)

Dennis, Alan R.; Bhagwatwar, Akshay; Minas, Randall K.

2013-01-01

The importance of testing, especially certification and high-stakes testing, has increased substantially over the past decade. Building on the "serious gaming" literature and the psychology "priming" literature, we developed a computer game designed to improve test-taking performance using psychological priming. The game primed…

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-01-01

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

Assessing control of postural stability in community-living older adults using performance-based limits of stability

Directory of Open Access Journals (Sweden)

Boissy Patrick

2008-03-01

Full Text Available Abstract Background Balance disability measurements routinely used to identify fall risks in frail populations have limited value in the early detection of postural stability deficits in community-living older adults. The objectives of the study were to 1 measure performance-based limits of stability (LOS in community-living older adults and compare them to theoretical LOS computed from data proposed by the Balance Master® system, 2 explore the feasibility of a new measurement approach based on the assessment of postural stability during weight-shifting tasks at performance-based LOS, 3 quantify intra-session performance variability during multiple trials using the performance-based LOS paradigm. Methods Twenty-four healthy community-living older adults (10 men, 14 women aged between 62 to 85 (mean age ± sd, 71.5 ± 6 yrs participated in the study. Subjects' performance-based LOS were established by asking them to transfer their body weight as far as possible in three directions (forward, right and left without changing their base of support. LOS were computed as the maximal excursion of the COP in each direction among three trials. Participants then performed two experimental tasks that consisted in controlling, with the assistance of visual feedback, their centre of pressure (COP within two predefined targets set at 100% of their performance-based LOS. For each tasks 8 trials were performed. Ground reaction forces and torques during performance-based LOS evaluation and experimental tasks were recorded with a force plate. Sway area and medio-lateral mean COP displacement speed variables were extracted from force plate recordings. Results Significant differences between theoretical LOS computed from maximum leaning angles derived from anthropometric characteristics and performance-based LOS were observed. Results showed that a motor learning effect was present as the participants optimized their weight-shifting strategy through the first three

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

Sampling from complex networks with high community structures.

Science.gov (United States)

Salehi, Mostafa; Rabiee, Hamid R; Rajabi, Arezo

2012-06-01

In this paper, we propose a novel link-tracing sampling algorithm, based on the concepts from PageRank vectors, to sample from networks with high community structures. Our method has two phases; (1) Sampling the closest nodes to the initial nodes by approximating personalized PageRank vectors and (2) Jumping to a new community by using PageRank vectors and unknown neighbors. Empirical studies on several synthetic and real-world networks show that the proposed method improves the performance of network sampling compared to the popular link-based sampling methods in terms of accuracy and visited communities.

Tablet computers for recording tuberculosis data at a community ...

African Journals Online (AJOL)

Tablet computers for recording tuberculosis data at a community health centre in King Sabata Dalindyebo Local Municipality, ... South African Family Practice ... They expressed a desire to extend the use of tablets to other areas of their work.

Computing in high energy physics

Energy Technology Data Exchange (ETDEWEB)

Watase, Yoshiyuki

1991-09-15

The increasingly important role played by computing and computers in high energy physics is displayed in the 'Computing in High Energy Physics' series of conferences, bringing together experts in different aspects of computing - physicists, computer scientists, and vendors.

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-12-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Karonis, Nicholas T.

2000-05-01

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

Computing in high energy physics

International Nuclear Information System (INIS)

Watase, Yoshiyuki

1991-01-01

The increasingly important role played by computing and computers in high energy physics is displayed in the 'Computing in High Energy Physics' series of conferences, bringing together experts in different aspects of computing - physicists, computer scientists, and vendors

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

High performance computing applied to simulation of the flow in pipes; Computacao de alto desempenho aplicada a simulacao de escoamento em dutos

Energy Technology Data Exchange (ETDEWEB)

Cozin, Cristiane; Lueders, Ricardo; Morales, Rigoberto E.M. [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil). Dept. de Engenharia Mecanica

2008-07-01

In recent years, computer cluster has emerged as a real alternative to solution of problems which require high performance computing. Consequently, the development of new applications has been driven. Among them, flow simulation represents a real computational burden specially for large systems. This work presents a study of using parallel computing for numerical fluid flow simulation in pipelines. A mathematical flow model is numerically solved. In general, this procedure leads to a tridiagonal system of equations suitable to be solved by a parallel algorithm. In this work, this is accomplished by a parallel odd-oven reduction method found in the literature which is implemented on Fortran programming language. A computational platform composed by twelve processors was used. Many measures of CPU times for different tridiagonal system sizes and number of processors were obtained, highlighting the communication time between processors as an important issue to be considered when evaluating the performance of parallel applications. (author)

High performance parallel I/O

CERN Document Server

Prabhat

2014-01-01

Gain Critical Insight into the Parallel I/O EcosystemParallel I/O is an integral component of modern high performance computing (HPC), especially in storing and processing very large datasets to facilitate scientific discovery. Revealing the state of the art in this field, High Performance Parallel I/O draws on insights from leading practitioners, researchers, software architects, developers, and scientists who shed light on the parallel I/O ecosystem.The first part of the book explains how large-scale HPC facilities scope, configure, and operate systems, with an emphasis on choices of I/O har

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.

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

Science.gov (United States)

Beck, Jeffrey; Bos, Jeremy P.

2017-05-01

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

Dance Performance: Giving Voice to the Community

Science.gov (United States)

Ferro, Simone; Watts, Meredith W.

2012-01-01

This project used oral history contributed by community story-tellers as source material for choreographic work performed in the community. The oral histories focused on four major areas: arrival (migration), social life, spirituality, and segregation/civil rights. Public performances took place at the university, local schools, and the community…

Pathways to high and low performance: factors differentiating primary care facilities under performance-based financing in Nigeria

Science.gov (United States)

Mabuchi, Shunsuke; Sesan, Temilade; Bennett, Sara C

2018-01-01

Abstract The determinants of primary health facility performance in developing countries have not been well studied. One of the most under-researched areas is health facility management. This study investigated health facilities under the pilot performance-based financing (PBF) scheme in Nigeria, and aimed to understand which factors differentiated primary health care centres (PHCCs) which had performed well, vs those which had not, with a focus on health facility management practices. We used a multiple case study where we compared two high-performing PHCCs and two low-performing PHCCs for each of the two PBF target states. Two teams of two trained local researchers spent 1 week at each PHCC and collected semi-structured interview, observation and documentary data. Data from interviews were transcribed, translated and coded using a framework approach. The data for each PHCC were synthesized to understand dynamic interactions of different elements in each case. We then compared the characteristics of high and low performers. The areas in which critical differences between high and low-performers emerged were: community engagement and support; and performance and staff management. We also found that (i) contextual and health system factors particularly staffing, access and competition with other providers; (ii) health centre management including community engagement, performance management and staff management; and (iii) community leader support interacted and drove performance improvement among the PHCCs. Among them, we found that good health centre management can overcome some contextual and health system barriers and enhance community leader support. This study findings suggest a strong need to select capable and motivated health centre managers, provide long-term coaching in managerial skills, and motivate them to improve their practices. The study also highlights the need to position engagement with community leaders as a key management practice and a central

EGI-EUDAT integration activity - Pair data and high-throughput computing resources together

Science.gov (United States)

Scardaci, Diego; Viljoen, Matthew; Vitlacil, Dejan; Fiameni, Giuseppe; Chen, Yin; sipos, Gergely; Ferrari, Tiziana

2016-04-01

EGI (www.egi.eu) is a publicly funded e-infrastructure put together to give scientists access to more than 530,000 logical CPUs, 200 PB of disk capacity and 300 PB of tape storage to drive research and innovation in Europe. The infrastructure provides both high throughput computing and cloud compute/storage capabilities. Resources are provided by about 350 resource centres which are distributed across 56 countries in Europe, the Asia-Pacific region, Canada and Latin America. EUDAT (www.eudat.eu) is a collaborative Pan-European infrastructure providing research data services, training and consultancy for researchers, research communities, research infrastructures and data centres. EUDAT's vision is to enable European researchers and practitioners from any research discipline to preserve, find, access, and process data in a trusted environment, as part of a Collaborative Data Infrastructure (CDI) conceived as a network of collaborating, cooperating centres, combining the richness of numerous community-specific data repositories with the permanence and persistence of some of Europe's largest scientific data centres. EGI and EUDAT, in the context of their flagship projects, EGI-Engage and EUDAT2020, started in March 2015 a collaboration to harmonise the two infrastructures, including technical interoperability, authentication, authorisation and identity management, policy and operations. The main objective of this work is to provide end-users with a seamless access to an integrated infrastructure offering both EGI and EUDAT services and, then, pairing data and high-throughput computing resources together. To define the roadmap of this collaboration, EGI and EUDAT selected a set of relevant user communities, already collaborating with both infrastructures, which could bring requirements and help to assign the right priorities to each of them. In this way, from the beginning, this activity has been really driven by the end users. The identified user communities are

High-Bandwidth Tactical-Network Data Analysis in a High-Performance-Computing (HPC) Environment: Transport Protocol (Transmission Control Protocol/User Datagram Protocol [TCP/UDP]) Analysis

Science.gov (United States)

2015-09-01

the network Mac8 Medium Access Control ( Mac ) (Ethernet) address observed as destination for outgoing packets subsessionid8 Zero-based index of...15. SUBJECT TERMS tactical networks, data reduction, high-performance computing, data analysis, big data 16. SECURITY CLASSIFICATION OF: 17...Integer index of row cts_deid Device (instrument) Identifier where observation took place cts_collpt Collection point or logical observation point on

Community unit performance: factors associated with childhood diarrhea and appropriate treatment in Nyanza Province, Kenya

Directory of Open Access Journals (Sweden)

Yoshito Kawakatsu

2017-02-01

Full Text Available Abstract Background The government of Kenya launched its community health strategy in 2006 to improve certain aspects of its community health program. Under the strategy, community units (CUs were established as level one of the Kenyan health system. A core member at this level is the community health worker (CHW. The objective of this study was to assess the relationship among the performance of the CUs, the prevalence of childhood diarrhea and appropriate treatment for it by controlling individual and community-level factors. Methods The main dataset used in this study was the 2011 Nyanza Province county-based Multiple Indicator Cluster Survey (MICS. In addition, based on the list of community units in Nyanza Province, Kenya, we identified the area’s CUs and their performance. MICS data and data on CUs were merged using sub-location names. There were 17 individual and two community-level independent variables in this study. Bivariate analysis and a multilevel logistic regression were performed. Results Factors significantly associated with a lower prevalence of diarrhea among children under five were the child’s increasing age, middle-aged household heads, children who received more attention, water treatment and rural versus urban area residence, while male children and highly performing CUs were significantly associated with a higher prevalence of diarrhea. In addition, middle wealth index, severity of diarrhea and middle- and high-CU performance were significantly associated with appropriate treatment for childhood diarrhea. Conclusions Although this study found that children living in areas of high CU performance were more likely to have diarrhea, these areas would have been identified as being more at risk for diarrhea prevalence and other health concerns, prioritized for the establishment of a CU and allocated more resources to improve the performance of CUs. A higher CU performance was significantly associated with the appropriate

Community unit performance: factors associated with childhood diarrhea and appropriate treatment in Nyanza Province, Kenya.

Science.gov (United States)

Kawakatsu, Yoshito; Tanaka, Junichi; Ogawa, Kazuya; Ogendo, Kenneth; Honda, Sumihisa

2017-02-16

The government of Kenya launched its community health strategy in 2006 to improve certain aspects of its community health program. Under the strategy, community units (CUs) were established as level one of the Kenyan health system. A core member at this level is the community health worker (CHW). The objective of this study was to assess the relationship among the performance of the CUs, the prevalence of childhood diarrhea and appropriate treatment for it by controlling individual and community-level factors. The main dataset used in this study was the 2011 Nyanza Province county-based Multiple Indicator Cluster Survey (MICS). In addition, based on the list of community units in Nyanza Province, Kenya, we identified the area's CUs and their performance. MICS data and data on CUs were merged using sub-location names. There were 17 individual and two community-level independent variables in this study. Bivariate analysis and a multilevel logistic regression were performed. Factors significantly associated with a lower prevalence of diarrhea among children under five were the child's increasing age, middle-aged household heads, children who received more attention, water treatment and rural versus urban area residence, while male children and highly performing CUs were significantly associated with a higher prevalence of diarrhea. In addition, middle wealth index, severity of diarrhea and middle- and high-CU performance were significantly associated with appropriate treatment for childhood diarrhea. Although this study found that children living in areas of high CU performance were more likely to have diarrhea, these areas would have been identified as being more at risk for diarrhea prevalence and other health concerns, prioritized for the establishment of a CU and allocated more resources to improve the performance of CUs. A higher CU performance was significantly associated with the appropriate treatment. It was suggested that CHWs could have a positive effect on

The role of anxiety symptoms in school performance in a community sample of children and adolescents.

Science.gov (United States)

Mazzone, Luigi; Ducci, Francesca; Scoto, Maria Cristina; Passaniti, Eleonora; D'Arrigo, Valentina Genitori; Vitiello, Benedetto

2007-12-05

Anxiety symptoms are relatively common among children and adolescents and can interfere with functioning. The prevalence of anxiety and the relationship between anxiety and school performance were examined among elementary, middle, and high school students. Samples of elementary (N = 131, age 8-10 years), middle (N = 267, age 11-13 years), and high school (N = 80, age 14-16 years) children were recruited from four public schools in a predominantly middle-class community in Catania, Italy. Children completed the Multidimensional Anxiety Scale for Children (MASC). T-scores were computed for the MASC total scores, and considered to be in the anxious range if 65 or above. Current academic grades were obtained from school records. Of the 478 children, 35 (7.3%) had a MASC T-score in the anxious range. The rate of children in the anxious range was 2.3% in elementary, 7.9% in middle, and 15.9% in high school (chi2 = 7.8, df = 2, p children and adolescents attending elementary through high school, the prevalence of abnormally high self-reported levels of anxiety increased in frequency with age and was negatively associated with school performance.

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

Science.gov (United States)

Rao, Nageswara S.

2015-09-01

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

High-Resolution Melt Analysis for Rapid Comparison of Bacterial Community Compositions

DEFF Research Database (Denmark)

Hjelmsø, Mathis Hjort; Hansen, Lars Hestbjerg; Bælum, Jacob

2014-01-01

In the study of bacterial community composition, 16S rRNA gene amplicon sequencing is today among the preferred methods of analysis. The cost of nucleotide sequence analysis, including requisite computational and bioinformatic steps, however, takes up a large part of many research budgets. High......-resolution melt (HRM) analysis is the study of the melt behavior of specific PCR products. Here we describe a novel high-throughput approach in which we used HRM analysis targeting the 16S rRNA gene to rapidly screen multiple complex samples for differences in bacterial community composition. We hypothesized...... that HRM analysis of amplified 16S rRNA genes from a soil ecosystem could be used as a screening tool to identify changes in bacterial community structure. This hypothesis was tested using a soil microcosm setup exposed to a total of six treatments representing different combinations of pesticide...

AstroCV: Astronomy computer vision library

Science.gov (United States)

González, Roberto E.; Muñoz, Roberto P.; Hernández, Cristian A.

2018-04-01

AstroCV processes and analyzes big astronomical datasets, and is intended to provide a community repository of high performance Python and C++ algorithms used for image processing and computer vision. The library offers methods for object recognition, segmentation and classification, with emphasis in the automatic detection and classification of galaxies.

The HEPCloud Facility: elastic computing for High Energy Physics – The NOvA Use Case

Energy Technology Data Exchange (ETDEWEB)

Fuess, S. [Fermilab; Garzoglio, G. [Fermilab; Holzman, B. [Fermilab; Kennedy, R. [Fermilab; Norman, A. [Fermilab; Timm, S. [Fermilab; Tiradani, A. [Fermilab

2017-03-15

The need for computing in the HEP community follows cycles of peaks and valleys mainly driven by conference dates, accelerator shutdown, holiday schedules, and other factors. Because of this, the classical method of provisioning these resources at providing facilities has drawbacks such as potential overprovisioning. As the appetite for computing increases, however, so does the need to maximize cost efficiency by developing a model for dynamically provisioning resources only when needed. To address this issue, the HEPCloud project was launched by the Fermilab Scientific Computing Division in June 2015. Its goal is to develop a facility that provides a common interface to a variety of resources, including local clusters, grids, high performance computers, and community and commercial Clouds. Initially targeted experiments include CMS and NOvA, as well as other Fermilab stakeholders. In its first phase, the project has demonstrated the use of the “elastic” provisioning model offered by commercial clouds, such as Amazon Web Services. In this model, resources are rented and provisioned automatically over the Internet upon request. In January 2016, the project demonstrated the ability to increase the total amount of global CMS resources by 58,000 cores from 150,000 cores - a 25 percent increase - in preparation for the Recontres de Moriond. In March 2016, the NOvA experiment has also demonstrated resource burst capabilities with an additional 7,300 cores, achieving a scale almost four times as large as the local allocated resources and utilizing the local AWS s3 storage to optimize data handling operations and costs. NOvA was using the same familiar services used for local computations, such as data handling and job submission, in preparation for the Neutrino 2016 conference. In both cases, the cost was contained by the use of the Amazon Spot Instance Market and the Decision Engine, a HEPCloud component that aims at minimizing cost and job interruption. This paper

SISYPHUS: A high performance seismic inversion factory

Science.gov (United States)

Gokhberg, Alexey; Simutė, Saulė; Boehm, Christian; Fichtner, Andreas

2016-04-01

In the recent years the massively parallel high performance computers became the standard instruments for solving the forward and inverse problems in seismology. The respective software packages dedicated to forward and inverse waveform modelling specially designed for such computers (SPECFEM3D, SES3D) became mature and widely available. These packages achieve significant computational performance and provide researchers with an opportunity to solve problems of bigger size at higher resolution within a shorter time. However, a typical seismic inversion process contains various activities that are beyond the common solver functionality. They include management of information on seismic events and stations, 3D models, observed and synthetic seismograms, pre-processing of the observed signals, computation of misfits and adjoint sources, minimization of misfits, and process workflow management. These activities are time consuming, seldom sufficiently automated, and therefore represent a bottleneck that can substantially offset performance benefits provided by even the most powerful modern supercomputers. Furthermore, a typical system architecture of modern supercomputing platforms is oriented towards the maximum computational performance and provides limited standard facilities for automation of the supporting activities. We present a prototype solution that automates all aspects of the seismic inversion process and is tuned for the modern massively parallel high performance computing systems. We address several major aspects of the solution architecture, which include (1) design of an inversion state database for tracing all relevant aspects of the entire solution process, (2) design of an extensible workflow management framework, (3) integration with wave propagation solvers, (4) integration with optimization packages, (5) computation of misfits and adjoint sources, and (6) process monitoring. The inversion state database represents a hierarchical structure with

Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing

Energy Technology Data Exchange (ETDEWEB)

Bremer, Peer-Timo [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Mohr, Bernd [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Schulz, Martin [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pasccci, Valerio [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Gamblin, Todd [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Brunst, Holger [Dresden Univ. of Technology (Germany)

2015-07-29

The characterization, modeling, analysis, and tuning of software performance has been a central topic in High Performance Computing (HPC) since its early beginnings. The overall goal is to make HPC software run faster on particular hardware, either through better scheduling, on-node resource utilization, or more efficient distributed communication.

Cognitive Correlates of Performance in Algorithms in a Computer Science Course for High School

Science.gov (United States)

Avancena, Aimee Theresa; Nishihara, Akinori

2014-01-01

Computer science for high school faces many challenging issues. One of these is whether the students possess the appropriate cognitive ability for learning the fundamentals of computer science. Online tests were created based on known cognitive factors and fundamental algorithms and were implemented among the second grade students in the…

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.

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

KAUST Repository

Jiang, Jiming; Claudel, Christian

2017-01-01

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

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

KAUST Repository

Jiang, Jiming

2017-02-02

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

Computer versus paper--does it make any difference in test performance?

Science.gov (United States)

Karay, Yassin; Schauber, Stefan K; Stosch, Christoph; Schüttpelz-Brauns, Katrin

2015-01-01

CONSTRUCT: In this study, we examine the differences in test performance between the paper-based and the computer-based version of the Berlin formative Progress Test. In this context it is the first study that allows controlling for students' prior performance. Computer-based tests make possible a more efficient examination procedure for test administration and review. Although university staff will benefit largely from computer-based tests, the question arises if computer-based tests influence students' test performance. A total of 266 German students from the 9th and 10th semester of medicine (comparable with the 4th-year North American medical school schedule) participated in the study (paper = 132, computer = 134). The allocation of the test format was conducted as a randomized matched-pair design in which students were first sorted according to their prior test results. The organizational procedure, the examination conditions, the room, and seating arrangements, as well as the order of questions and answers, were identical in both groups. The sociodemographic variables and pretest scores of both groups were comparable. The test results from the paper and computer versions did not differ. The groups remained within the allotted time, but students using the computer version (particularly the high performers) needed significantly less time to complete the test. In addition, we found significant differences in guessing behavior. Low performers using the computer version guess significantly more than low-performing students in the paper-pencil version. Participants in computer-based tests are not at a disadvantage in terms of their test results. The computer-based test required less processing time. The reason for the longer processing time when using the paper-pencil version might be due to the time needed to write the answer down, controlling for transferring the answer correctly. It is still not known why students using the computer version (particularly low-performing