Computational Biology and High Performance Computing 2000

Energy Technology Data Exchange (ETDEWEB)

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

2000-10-19

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

Computational 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

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 — an overview

Science.gov (United States)

Marksteiner, Peter

1996-08-01

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

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 in Windows Azure cloud

OpenAIRE

Ambruš, Dejan

2013-01-01

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

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.

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

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.

Quantum Accelerators for High-performance Computing Systems

Energy Technology Data Exchange (ETDEWEB)

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

2017-11-01

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

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.

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)

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 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.

High performance computing in science and engineering Garching/Munich 2016

Energy Technology Data Exchange (ETDEWEB)

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

2016-11-01

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

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

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

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...

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.

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…

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.

Optical interconnection networks for high-performance computing systems

International Nuclear Information System (INIS)

Biberman, Aleksandr; Bergman, Keren

2012-01-01

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

Debugging a high performance computing program

Science.gov (United States)

Gooding, Thomas M.

2013-08-20

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

10th International Workshop on Parallel Tools for High Performance Computing

CERN Document Server

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

2017-01-01

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

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.

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.

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

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

Energy Technology Data Exchange (ETDEWEB)

Drewmark Communications; Sartor, Dale; Wilson, Mark

2010-07-01

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

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 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...

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

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.

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 ...

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.

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

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.

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).

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.

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.

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

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

Science.gov (United States)

2011-01-01

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

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.

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

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.

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

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

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2013-05-01

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

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.

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.

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

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

CERN Multimedia

2002-01-01

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

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.

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...

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.

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...

Transportation Research & Analysis Computing Center

Data.gov (United States)

Federal Laboratory Consortium — The technical objectives of the TRACC project included the establishment of a high performance computing center for use by USDOT research teams, including those from...

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 - 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.

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...

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.

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, 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

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.

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.

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.

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

Science.gov (United States)

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

2018-05-01

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

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

Science.gov (United States)

2018-01-01

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

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.

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

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 ...

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 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

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...

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

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

International Nuclear Information System (INIS)

Khaleel, Mohammad A.

2009-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Khaleel, Mohammad A.

2009-10-01

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

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.

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 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.

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...

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.

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

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.

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.

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.

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.

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

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.

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

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...

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.

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

Energy Technology Data Exchange (ETDEWEB)

Hules, J. [ed.

1996-11-01

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

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.

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.

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 ...

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

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...

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 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

Nuclear forces and high-performance computing: The perfect match

International Nuclear Information System (INIS)

Luu, T; Walker-Loud, A

2009-01-01

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

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

[Activities of Research Institute for Advanced Computer Science

Science.gov (United States)

Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

2001-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administrations missions. RIACS is located at the NASA Ames Research Center, Moffett Field, California. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1. Automated Reasoning for Autonomous Systems Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. 2. Human-Centered Computing Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities. 3. High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to analysis of large scientific datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

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.

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.

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.

Research Institute for Advanced Computer Science

Science.gov (United States)

Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

2000-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth; (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking. Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a

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.

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.

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...

Parallel computing in genomic research: advances and applications

Directory of Open Access Journals (Sweden)

Ocaña K

2015-11-01

Full Text Available Kary Ocaña,1 Daniel de Oliveira2 1National Laboratory of Scientific Computing, Petrópolis, Rio de Janeiro, 2Institute of Computing, Fluminense Federal University, Niterói, Brazil Abstract: Today's genomic experiments have to process the so-called "biological big data" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities. Keywords: high-performance computing, genomic research, cloud computing, grid computing, cluster computing, parallel computing

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

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 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)

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

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.

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.

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.

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.

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

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

Directory of Open Access Journals (Sweden)

Eduard AyguadÉ

1997-01-01

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

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

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.

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

Economic Model For a Return on Investment Analysis of United States Government High Performance Computing (HPC) Research and Development (R & D) Investment

Energy Technology Data Exchange (ETDEWEB)

Joseph, Earl C. [IDC Research Inc., Framingham, MA (United States); Conway, Steve [IDC Research Inc., Framingham, MA (United States); Dekate, Chirag [IDC Research Inc., Framingham, MA (United States)

2013-09-30

This study investigated how high-performance computing (HPC) investments can improve economic success and increase scientific innovation. This research focused on the common good and provided uses for DOE, other government agencies, industry, and academia. The study created two unique economic models and an innovation index: 1 A macroeconomic model that depicts the way HPC investments result in economic advancements in the form of ROI in revenue (GDP), profits (and cost savings), and jobs. 2 A macroeconomic model that depicts the way HPC investments result in basic and applied innovations, looking at variations by sector, industry, country, and organization size. A new innovation index that provides a means of measuring and comparing innovation levels. Key findings of the pilot study include: IDC collected the required data across a broad set of organizations, with enough detail to create these models and the innovation index. The research also developed an expansive list of HPC success stories.

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.

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

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 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.

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.

Activities of the Research Institute for Advanced Computer Science

Science.gov (United States)

Oliger, Joseph

1994-01-01

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

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...

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)

Activity report of Computing Research Center

Energy Technology Data Exchange (ETDEWEB)

1997-07-01

On April 1997, National Laboratory for High Energy Physics (KEK), Institute of Nuclear Study, University of Tokyo (INS), and Meson Science Laboratory, Faculty of Science, University of Tokyo began to work newly as High Energy Accelerator Research Organization after reconstructing and converting their systems, under aiming at further development of a wide field of accelerator science using a high energy accelerator. In this Research Organization, Applied Research Laboratory is composed of four Centers to execute assistance of research actions common to one of the Research Organization and their relating research and development (R and D) by integrating the present four centers and their relating sections in Tanashi. What is expected for the assistance of research actions is not only its general assistance but also its preparation and R and D of a system required for promotion and future plan of the research. Computer technology is essential to development of the research and can communize for various researches in the Research Organization. On response to such expectation, new Computing Research Center is required for promoting its duty by coworking and cooperating with every researchers at a range from R and D on data analysis of various experiments to computation physics acting under driving powerful computer capacity such as supercomputer and so forth. Here were described on report of works and present state of Data Processing Center of KEK at the first chapter and of the computer room of INS at the second chapter and on future problems for the Computing Research Center. (G.K.)

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.

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

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

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.

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.

Applied Computational Fluid Dynamics at NASA Ames Research Center

Science.gov (United States)

Holst, Terry L.; Kwak, Dochan (Technical Monitor)

1994-01-01

The field of Computational Fluid Dynamics (CFD) has advanced to the point where it can now be used for many applications in fluid mechanics research and aerospace vehicle design. A few applications being explored at NASA Ames Research Center will be presented and discussed. The examples presented will range in speed from hypersonic to low speed incompressible flow applications. Most of the results will be from numerical solutions of the Navier-Stokes or Euler equations in three space dimensions for general geometry applications. Computational results will be used to highlight the presentation as appropriate. Advances in computational facilities including those associated with NASA's CAS (Computational Aerosciences) Project of the Federal HPCC (High Performance Computing and Communications) Program will be discussed. Finally, opportunities for future research will be presented and discussed. All material will be taken from non-sensitive, previously-published and widely-disseminated work.

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.

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.

Examination of China's performance and thematic evolution in quantum cryptography research using quantitative and computational techniques.

Science.gov (United States)

Olijnyk, Nicholas V

2018-01-01

This study performed two phases of analysis to shed light on the performance and thematic evolution of China's quantum cryptography (QC) research. First, large-scale research publication metadata derived from QC research published from 2001-2017 was used to examine the research performance of China relative to that of global peers using established quantitative and qualitative measures. Second, this study identified the thematic evolution of China's QC research using co-word cluster network analysis, a computational science mapping technique. The results from the first phase indicate that over the past 17 years, China's performance has evolved dramatically, placing it in a leading position. Among the most significant findings is the exponential rate at which all of China's performance indicators (i.e., Publication Frequency, citation score, H-index) are growing. China's H-index (a normalized indicator) has surpassed all other countries' over the last several years. The second phase of analysis shows how China's main research focus has shifted among several QC themes, including quantum-key-distribution, photon-optical communication, network protocols, and quantum entanglement with an emphasis on applied research. Several themes were observed across time periods (e.g., photons, quantum-key-distribution, secret-messages, quantum-optics, quantum-signatures); some themes disappeared over time (e.g., computer-networks, attack-strategies, bell-state, polarization-state), while others emerged more recently (e.g., quantum-entanglement, decoy-state, unitary-operation). Findings from the first phase of analysis provide empirical evidence that China has emerged as the global driving force in QC. Considering China is the premier driving force in global QC research, findings from the second phase of analysis provide an understanding of China's QC research themes, which can provide clarity into how QC technologies might take shape. QC and science and technology policy researchers

Examination of China's performance and thematic evolution in quantum cryptography research using quantitative and computational techniques.

Directory of Open Access Journals (Sweden)

Nicholas V Olijnyk

Full Text Available This study performed two phases of analysis to shed light on the performance and thematic evolution of China's quantum cryptography (QC research. First, large-scale research publication metadata derived from QC research published from 2001-2017 was used to examine the research performance of China relative to that of global peers using established quantitative and qualitative measures. Second, this study identified the thematic evolution of China's QC research using co-word cluster network analysis, a computational science mapping technique. The results from the first phase indicate that over the past 17 years, China's performance has evolved dramatically, placing it in a leading position. Among the most significant findings is the exponential rate at which all of China's performance indicators (i.e., Publication Frequency, citation score, H-index are growing. China's H-index (a normalized indicator has surpassed all other countries' over the last several years. The second phase of analysis shows how China's main research focus has shifted among several QC themes, including quantum-key-distribution, photon-optical communication, network protocols, and quantum entanglement with an emphasis on applied research. Several themes were observed across time periods (e.g., photons, quantum-key-distribution, secret-messages, quantum-optics, quantum-signatures; some themes disappeared over time (e.g., computer-networks, attack-strategies, bell-state, polarization-state, while others emerged more recently (e.g., quantum-entanglement, decoy-state, unitary-operation. Findings from the first phase of analysis provide empirical evidence that China has emerged as the global driving force in QC. Considering China is the premier driving force in global QC research, findings from the second phase of analysis provide an understanding of China's QC research themes, which can provide clarity into how QC technologies might take shape. QC and science and technology

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.

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.

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 Assets for Ocean Acoustics Research

Science.gov (United States)

2016-11-18

processors, effectively), and 512GB memory . The second has 24 CPU cores, dual -thread, (48 processors, effectively), and 512GB memory . The third has...28 CPU cores, dual -thread, (56 processors, effectively), and 256GB memory . Mr. Arthur Newhall ofWHOI worked with the vendors to secure the best...Headrick Office ofNaval Research, Code 322 One Liberty Center 875 North Randolph Street, Suite 4125 Arlington, VA 22203 Dear Dr. Headrick

Young Researchers Advancing Computational Science: Perspectives of the Young Scientists Conference 2015

NARCIS (Netherlands)

Boukhanovsky, A.V.; Ilyin, V.A; Krzhizhanovskaya, V.V.; Athanassoulis, G.A.; Klimentov, A.A.; Sloot, P.M.A.

2015-01-01

We present an annual international Young Scientists Conference (YSC) on computational science http://ysc.escience.ifmo.ru/, which brings together renowned experts and young researchers working in high-performance computing, data-driven modeling, and simulation of large-scale complex systems. The

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.

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

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.

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

Science.gov (United States)

Khosronejad, A.

2016-12-01

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

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

Science.gov (United States)

Thackston, Russell; Fortenberry, Ryan C

2015-05-05

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

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.

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

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

Science.gov (United States)

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

2009-08-01

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

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.  

Large scale computing in the Energy Research Programs

International Nuclear Information System (INIS)

1991-05-01

The Energy Research Supercomputer Users Group (ERSUG) comprises all investigators using resources of the Department of Energy Office of Energy Research supercomputers. At the December 1989 meeting held at Florida State University (FSU), the ERSUG executive committee determined that the continuing rapid advances in computational sciences and computer technology demanded a reassessment of the role computational science should play in meeting DOE's commitments. Initial studies were to be performed for four subdivisions: (1) Basic Energy Sciences (BES) and Applied Mathematical Sciences (AMS), (2) Fusion Energy, (3) High Energy and Nuclear Physics, and (4) Health and Environmental Research. The first two subgroups produced formal subreports that provided a basis for several sections of this report. Additional information provided in the AMS/BES is included as Appendix C in an abridged form that eliminates most duplication. Additionally, each member of the executive committee was asked to contribute area-specific assessments; these assessments are included in the next section. In the following sections, brief assessments are given for specific areas, a conceptual model is proposed that the entire computational effort for energy research is best viewed as one giant nation-wide computer, and then specific recommendations are made for the appropriate evolution of the system

Final Report: Performance Engineering Research Institute

Energy Technology Data Exchange (ETDEWEB)

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

2014-10-27

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

Large Scale Computing and Storage Requirements for Basic Energy Sciences Research

Energy Technology Data Exchange (ETDEWEB)

Gerber, Richard; Wasserman, Harvey

2011-03-31

The National Energy Research Scientific Computing Center (NERSC) is the leading scientific computing facility supporting research within the Department of Energy's Office of Science. NERSC provides high-performance computing (HPC) resources to approximately 4,000 researchers working on about 400 projects. In addition to hosting large-scale computing facilities, NERSC provides the support and expertise scientists need to effectively and efficiently use HPC systems. In February 2010, NERSC, DOE's Office of Advanced Scientific Computing Research (ASCR) and DOE's Office of Basic Energy Sciences (BES) held a workshop to characterize HPC requirements for BES research through 2013. The workshop was part of NERSC's legacy of anticipating users future needs and deploying the necessary resources to meet these demands. Workshop participants reached a consensus on several key findings, in addition to achieving the workshop's goal of collecting and characterizing computing requirements. The key requirements for scientists conducting research in BES are: (1) Larger allocations of computational resources; (2) Continued support for standard application software packages; (3) Adequate job turnaround time and throughput; and (4) Guidance and support for using future computer architectures. This report expands upon these key points and presents others. Several 'case studies' are included as significant representative samples of the needs of science teams within BES. Research teams scientific goals, computational methods of solution, current and 2013 computing requirements, and special software and support needs are summarized in these case studies. Also included are researchers strategies for computing in the highly parallel, 'multi-core' environment that is expected to dominate HPC architectures over the next few years. NERSC has strategic plans and initiatives already underway that address key workshop findings. This report includes a

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

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...

Current state and future direction of computer systems at NASA Langley Research Center

Science.gov (United States)

Rogers, James L. (Editor); Tucker, Jerry H. (Editor)

1992-01-01

Computer systems have advanced at a rate unmatched by any other area of technology. As performance has dramatically increased there has been an equally dramatic reduction in cost. This constant cost performance improvement has precipitated the pervasiveness of computer systems into virtually all areas of technology. This improvement is due primarily to advances in microelectronics. Most people are now convinced that the new generation of supercomputers will be built using a large number (possibly thousands) of high performance microprocessors. Although the spectacular improvements in computer systems have come about because of these hardware advances, there has also been a steady improvement in software techniques. In an effort to understand how these hardware and software advances will effect research at NASA LaRC, the Computer Systems Technical Committee drafted this white paper to examine the current state and possible future directions of computer systems at the Center. This paper discusses selected important areas of computer systems including real-time systems, embedded systems, high performance computing, distributed computing networks, data acquisition systems, artificial intelligence, and visualization.

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.

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.

The impact of computer science in molecular medicine: enabling high-throughput research.

Science.gov (United States)

de la Iglesia, Diana; García-Remesal, Miguel; de la Calle, Guillermo; Kulikowski, Casimir; Sanz, Ferran; Maojo, Víctor

2013-01-01

The Human Genome Project and the explosion of high-throughput data have transformed the areas of molecular and personalized medicine, which are producing a wide range of studies and experimental results and providing new insights for developing medical applications. Research in many interdisciplinary fields is resulting in data repositories and computational tools that support a wide diversity of tasks: genome sequencing, genome-wide association studies, analysis of genotype-phenotype interactions, drug toxicity and side effects assessment, prediction of protein interactions and diseases, development of computational models, biomarker discovery, and many others. The authors of the present paper have developed several inventories covering tools, initiatives and studies in different computational fields related to molecular medicine: medical informatics, bioinformatics, clinical informatics and nanoinformatics. With these inventories, created by mining the scientific literature, we have carried out several reviews of these fields, providing researchers with a useful framework to locate, discover, search and integrate resources. In this paper we present an analysis of the state-of-the-art as it relates to computational resources for molecular medicine, based on results compiled in our inventories, as well as results extracted from a systematic review of the literature and other scientific media. The present review is based on the impact of their related publications and the available data and software resources for molecular medicine. It aims to provide information that can be useful to support ongoing research and work to improve diagnostics and therapeutics based on molecular-level insights.

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...

Computing at the leading edge: Research in the energy sciences

Energy Technology Data Exchange (ETDEWEB)

Mirin, A.A.; Van Dyke, P.T. [eds.

1994-02-01

The purpose of this publication is to highlight selected scientific challenges that have been undertaken by the DOE Energy Research community. The high quality of the research reflected in these contributions underscores the growing importance both to the Grand Challenge scientific efforts sponsored by DOE and of the related supporting technologies that the National Energy Research Supercomputer Center (NERSC) and other facilities are able to provide. The continued improvement of the computing resources available to DOE scientists is prerequisite to ensuring their future progress in solving the Grand Challenges. Titles of articles included in this publication include: the numerical tokamak project; static and animated molecular views of a tumorigenic chemical bound to DNA; toward a high-performance climate systems model; modeling molecular processes in the environment; lattice Boltzmann models for flow in porous media; parallel algorithms for modeling superconductors; parallel computing at the Superconducting Super Collider Laboratory; the advanced combustion modeling environment; adaptive methodologies for computational fluid dynamics; lattice simulations of quantum chromodynamics; simulating high-intensity charged-particle beams for the design of high-power accelerators; electronic structure and phase stability of random alloys.

Computing at the leading edge: Research in the energy sciences

International Nuclear Information System (INIS)

Mirin, A.A.; Van Dyke, P.T.

1994-01-01

The purpose of this publication is to highlight selected scientific challenges that have been undertaken by the DOE Energy Research community. The high quality of the research reflected in these contributions underscores the growing importance both to the Grand Challenge scientific efforts sponsored by DOE and of the related supporting technologies that the National Energy Research Supercomputer Center (NERSC) and other facilities are able to provide. The continued improvement of the computing resources available to DOE scientists is prerequisite to ensuring their future progress in solving the Grand Challenges. Titles of articles included in this publication include: the numerical tokamak project; static and animated molecular views of a tumorigenic chemical bound to DNA; toward a high-performance climate systems model; modeling molecular processes in the environment; lattice Boltzmann models for flow in porous media; parallel algorithms for modeling superconductors; parallel computing at the Superconducting Super Collider Laboratory; the advanced combustion modeling environment; adaptive methodologies for computational fluid dynamics; lattice simulations of quantum chromodynamics; simulating high-intensity charged-particle beams for the design of high-power accelerators; electronic structure and phase stability of random alloys

The Preliminary Research for Implementation of Improved DTC Scheme of High Performance PMSM Drives

Directory of Open Access Journals (Sweden)

Tole Sutikno

2008-12-01

Full Text Available The direct torque control (DTC is one of control approache that is used commonly in PMSM control system. This method supports a very quick and precise torque response. However, the DTC method is not perfect and has some disadvantages. Many researchers have been proposed to modify the basic DTC scheme for PMSM drive. All this contributions allow performance to be improved, but at the same time they lead to more complex schemes. Furthermore, the PMSM drive control systems are usually based on microcontroller and DSP. Some researchers also have been used DSP and FPGA together to develop DTC for AC drives. These allow improving the performance, but they will increase cost. For the reason above, this paper proposed a new DTC scheme to apply only based on FPGA. The preliminary research showed that the proposed DTC sheme can reduce torque and flux ripples significantly. Therefore, this paper also recomend to realize proposed DTC scheme based on FPGA in order to support to execute very fast computation.The implementation is hoped that it will very potential to replace not only the induction motor but also the DC servo motor in a number of industrial process, commercial, domestic and modern military applications of high-performance drive.

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

International Nuclear Information System (INIS)

Suzuki, Yoshio

2007-01-01

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

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.

Usage of super high speed computer for clarification of complex phenomena

International Nuclear Information System (INIS)

Sekiguchi, Tomotsugu; Sato, Mitsuhisa; Nakata, Hideki; Tatebe, Osami; Takagi, Hiromitsu

1999-01-01

This study aims at construction of an efficient super high speed computer system application environment in response to parallel distributed system with easy transplantation to different computer system and different number by conducting research and development on super high speed computer application technology required for elucidation of complicated phenomenon in elucidation of complicated phenomenon of nuclear power field due to computed scientific method. In order to realize such environment, the Electrotechnical Laboratory has conducted development on Ninf, a network numerical information library. This Ninf system can supply a global network infrastructure for worldwide computing with high performance on further wide range distributed network (G.K.)

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

Leveraging High Performance Computing for Managing Large and Evolving Data Collections

Directory of Open Access Journals (Sweden)

Ritu Arora

2014-10-01

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

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.

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

Examination of China’s performance and thematic evolution in quantum cryptography research using quantitative and computational techniques

Science.gov (United States)

2018-01-01

This study performed two phases of analysis to shed light on the performance and thematic evolution of China’s quantum cryptography (QC) research. First, large-scale research publication metadata derived from QC research published from 2001–2017 was used to examine the research performance of China relative to that of global peers using established quantitative and qualitative measures. Second, this study identified the thematic evolution of China’s QC research using co-word cluster network analysis, a computational science mapping technique. The results from the first phase indicate that over the past 17 years, China’s performance has evolved dramatically, placing it in a leading position. Among the most significant findings is the exponential rate at which all of China’s performance indicators (i.e., Publication Frequency, citation score, H-index) are growing. China’s H-index (a normalized indicator) has surpassed all other countries’ over the last several years. The second phase of analysis shows how China’s main research focus has shifted among several QC themes, including quantum-key-distribution, photon-optical communication, network protocols, and quantum entanglement with an emphasis on applied research. Several themes were observed across time periods (e.g., photons, quantum-key-distribution, secret-messages, quantum-optics, quantum-signatures); some themes disappeared over time (e.g., computer-networks, attack-strategies, bell-state, polarization-state), while others emerged more recently (e.g., quantum-entanglement, decoy-state, unitary-operation). Findings from the first phase of analysis provide empirical evidence that China has emerged as the global driving force in QC. Considering China is the premier driving force in global QC research, findings from the second phase of analysis provide an understanding of China’s QC research themes, which can provide clarity into how QC technologies might take shape. QC and science and technology

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.

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)

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.

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)

Large Scale Computing and Storage Requirements for High Energy Physics

International Nuclear Information System (INIS)

Gerber, Richard A.; Wasserman, Harvey

2010-01-01

The National Energy Research Scientific Computing Center (NERSC) is the leading scientific computing facility for the Department of Energy's Office of Science, providing high-performance computing (HPC) resources to more than 3,000 researchers working on about 400 projects. NERSC provides large-scale computing resources and, crucially, the support and expertise needed for scientists to make effective use of them. In November 2009, NERSC, DOE's Office of Advanced Scientific Computing Research (ASCR), and DOE's Office of High Energy Physics (HEP) held a workshop to characterize the HPC resources needed at NERSC to support HEP research through the next three to five years. The effort is part of NERSC's legacy of anticipating users needs and deploying resources to meet those demands. The workshop revealed several key points, in addition to achieving its goal of collecting and characterizing computing requirements. The chief findings: (1) Science teams need access to a significant increase in computational resources to meet their research goals; (2) Research teams need to be able to read, write, transfer, store online, archive, analyze, and share huge volumes of data; (3) Science teams need guidance and support to implement their codes on future architectures; and (4) Projects need predictable, rapid turnaround of their computational jobs to meet mission-critical time constraints. This report expands upon these key points and includes others. It also presents a number of case studies as representative of the research conducted within HEP. Workshop participants were asked to codify their requirements in this case study format, summarizing their science goals, methods of solution, current and three-to-five year computing requirements, and software and support needs. Participants were also asked to describe their strategy for computing in the highly parallel, multi-core environment that is expected to dominate HPC architectures over the next few years. The report includes

Graphics supercomputer for computational fluid dynamics research

Science.gov (United States)

Liaw, Goang S.

1994-11-01

The objective of this project is to purchase a state-of-the-art graphics supercomputer to improve the Computational Fluid Dynamics (CFD) research capability at Alabama A & M University (AAMU) and to support the Air Force research projects. A cutting-edge graphics supercomputer system, Onyx VTX, from Silicon Graphics Computer Systems (SGI), was purchased and installed. Other equipment including a desktop personal computer, PC-486 DX2 with a built-in 10-BaseT Ethernet card, a 10-BaseT hub, an Apple Laser Printer Select 360, and a notebook computer from Zenith were also purchased. A reading room has been converted to a research computer lab by adding some furniture and an air conditioning unit in order to provide an appropriate working environments for researchers and the purchase equipment. All the purchased equipment were successfully installed and are fully functional. Several research projects, including two existing Air Force projects, are being performed using these facilities.

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

Directory of Open Access Journals (Sweden)

Wojtek James eGoscinski

2014-03-01

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

High energy physics and cloud computing

International Nuclear Information System (INIS)

Cheng Yaodong; Liu Baoxu; Sun Gongxing; Chen Gang

2011-01-01

High Energy Physics (HEP) has been a strong promoter of computing technology, for example WWW (World Wide Web) and the grid computing. In the new era of cloud computing, HEP has still a strong demand, and major international high energy physics laboratories have launched a number of projects to research on cloud computing technologies and applications. It describes the current developments in cloud computing and its applications in high energy physics. Some ongoing projects in the institutes of high energy physics, Chinese Academy of Sciences, including cloud storage, virtual computing clusters, and BESⅢ elastic cloud, are also described briefly in the paper. (authors)

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.

TORCH Computational Reference Kernels - A Testbed for Computer Science Research

Energy Technology Data Exchange (ETDEWEB)

Kaiser, Alex; Williams, Samuel Webb; Madduri, Kamesh; Ibrahim, Khaled; Bailey, David H.; Demmel, James W.; Strohmaier, Erich

2010-12-02

For decades, computer scientists have sought guidance on how to evolve architectures, languages, and programming models in order to improve application performance, efficiency, and productivity. Unfortunately, without overarching advice about future directions in these areas, individual guidance is inferred from the existing software/hardware ecosystem, and each discipline often conducts their research independently assuming all other technologies remain fixed. In today's rapidly evolving world of on-chip parallelism, isolated and iterative improvements to performance may miss superior solutions in the same way gradient descent optimization techniques may get stuck in local minima. To combat this, we present TORCH: A Testbed for Optimization ResearCH. These computational reference kernels define the core problems of interest in scientific computing without mandating a specific language, algorithm, programming model, or implementation. To compliment the kernel (problem) definitions, we provide a set of algorithmically-expressed verification tests that can be used to verify a hardware/software co-designed solution produces an acceptable answer. Finally, to provide some illumination as to how researchers have implemented solutions to these problems in the past, we provide a set of reference implementations in C and MATLAB.

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.

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 Descriptive Semantic Analysis of Semantic Graph Databases

Energy Technology Data Exchange (ETDEWEB)

Joslyn, Cliff A.; Adolf, Robert D.; al-Saffar, Sinan; Feo, John T.; Haglin, David J.; Mackey, Greg E.; Mizell, David W.

2011-06-02

As semantic graph database technology grows to address components ranging from extant large triple stores to SPARQL endpoints over SQL-structured relational databases, it will become increasingly important to be able to understand their inherent semantic structure, whether codified in explicit ontologies or not. Our group is researching novel methods for what we call descriptive semantic analysis of RDF triplestores, to serve purposes of analysis, interpretation, visualization, and optimization. But data size and computational complexity makes it increasingly necessary to bring high performance computational resources to bear on this task. Our research group built a novel high performance hybrid system comprising computational capability for semantic graph database processing utilizing the large multi-threaded architecture of the Cray XMT platform, conventional servers, and large data stores. In this paper we describe that architecture and our methods, and present the results of our analyses of basic properties, connected components, namespace interaction, and typed paths such for the Billion Triple Challenge 2010 dataset.

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

INSPIRED High School Computing Academies

Science.gov (United States)

Doerschuk, Peggy; Liu, Jiangjiang; Mann, Judith

2011-01-01

If we are to attract more women and minorities to computing we must engage students at an early age. As part of its mission to increase participation of women and underrepresented minorities in computing, the Increasing Student Participation in Research Development Program (INSPIRED) conducts computing academies for high school students. The…

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

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

Science.gov (United States)

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

2016-01-01

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

Performative Computation-aided Design Optimization

Directory of Open Access Journals (Sweden)

Ming Tang

2012-12-01

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

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.

Biological and Environmental Research Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Biological and Environmental Research, March 28-31, 2016, Rockville, Maryland

Energy Technology Data Exchange (ETDEWEB)

Arkin, Adam [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bader, David C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Coffey, Richard [Argonne National Lab. (ANL), Argonne, IL (United States); Antypas, Katie [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bard, Deborah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Dart, Eli [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Esnet; Dosanjh, Sudip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Gerber, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hack, James [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Monga, Inder [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Esnet; Papka, Michael E. [Argonne National Lab. (ANL), Argonne, IL (United States); Riley, Katherine [Argonne National Lab. (ANL), Argonne, IL (United States); Rotman, Lauren [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Esnet; Straatsma, Tjerk [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wells, Jack [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Aluru, Srinivas [Georgia Inst. of Technology, Atlanta, GA (United States); Andersen, Amity [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Aprá, Edoardo [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). EMSL; Azad, Ariful [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bates, Susan [National Center for Atmospheric Research, Boulder, CO (United States); Blaby, Ian [Brookhaven National Lab. (BNL), Upton, NY (United States); Blaby-Haas, Crysten [Brookhaven National Lab. (BNL), Upton, NY (United States); Bonneau, Rich [New York Univ. (NYU), NY (United States); Bowen, Ben [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bradford, Mark A. [Yale Univ., New Haven, CT (United States); Brodie, Eoin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Brown, James (Ben) [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Buluc, Aydin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bernholdt, David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bylaska, Eric [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Calvin, Kate [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Cannon, Bill [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Chen, Xingyuan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Cheng, Xiaolin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cheung, Margaret [Univ. of Houston, Houston, TX (United States); Chowdhary, Kenny [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Colella, Phillip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Collins, Bill [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Compo, Gil [National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States); Crowley, Mike [National Renewable Energy Lab. (NREL), Golden, CO (United States); Debusschere, Bert [Sandia National Lab. (SNL-CA), Livermore, CA (United States); D’Imperio, Nicholas [Brookhaven National Lab. (BNL), Upton, NY (United States); Dror, Ron [Stanford Univ., Stanford, CA (United States); Egan, Rob [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Evans, Katherine [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Friedberg, Iddo [Iowa State Univ., Ames, IA (United States); Fyke, Jeremy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Gao, Zheng [Stony Brook Univ., Stony Brook, NY (United States); Georganas, Evangelos [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Giraldo, Frank [Naval Postgraduate School, Monterey, CA (United States); Gnanakaran, Gnana [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Govind, Niri [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). EMSL; Grandy, Stuart [Univ. of New Hampshire, Durham, NH (United States); Gustafson, Bill [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hammond, Glenn [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hargrove, William [USDA Forest Service, Washington, D.C. (United States); Heroux, Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hoffman, Forrest [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hofmeyr, Steven [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hunke, Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Jackson, Charles [Univ. of Texas-Austin, Austin, TX (United States); Jacob, Rob [Argonne National Lab. (ANL), Argonne, IL (United States); Jacobson, Dan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Jacobson, Matt [Univ. of California, San Francisco, CA (United States); Jain, Chirag [Georgia Inst. of Technology, Atlanta, GA (United States); Johansen, Hans [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Johnson, Jeff [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jones, Andy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jones, Phil [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Kalyanaraman, Ananth [Washington State Univ., Pullman, WA (United States); Kang, Senghwa [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); King, Eric [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Koanantakool, Penporn [Univ. of California, Berkeley, CA (United States); Kollias, Pavlos [Stony Brook Univ., Stony Brook, NY (United States); Kopera, Michal [Univ. of California, Santa Cruz, CA (United States); Kotamarthi, Rao [Argonne National Lab. (ANL), Argonne, IL (United States); Kowalski, Karol [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). EMSL; Kumar, Jitendra [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kyrpides, Nikos [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Leung, Ruby [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Li, Xiaolin [Stony Brook Univ., Stony Brook, NY (United States); Lin, Wuyin [Brookhaven National Lab. (BNL), Upton, NY (United States); Link, Robert [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Liu, Yangang [Brookhaven National Lab. (BNL), Upton, NY (United States); Loew, Leslie [Univ. of Connecticut, Storrs, CT (United States); Luke, Edward [Brookhaven National Lab. (BNL), Upton, NY (United States); Ma, Hsi -Yen [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Mahadevan, Radhakrishnan [Univ. of Toronto, Toronto, ON (Canada); Maranas, Costas [Pennsylvania State Univ., University Park, PA (United States); Martin, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Maslowski, Wieslaw [Naval Postgraduate School, Monterey, CA (United States); McCue, Lee Ann [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); McInnes, Lois Curfman [Argonne National Lab. (ANL), Argonne, IL (United States); Mills, Richard [Intel Corp., Santa Clara, CA (United States); Molins Rafa, Sergi [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Morozov, Dmitriy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Mostafavi, Sara [Center for Molecular Medicine and Therapeutics, Vancouver, BC (Canada); Moulton, David J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Mourao, Zenaida [Univ. of Cambridge (United Kingdom); Najm, Habib [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ng, Bernard [Center for Molecular Medicine and Therapeutics, Vancouver, BC (Canada); Ng, Esmond [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Norman, Matt [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Oh, Sang -Yun [Univ. of California, Santa Barbara, CA (United States); Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Pan, Chongle [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Pass, Rebecca [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Pau, George S. H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Petridis, Loukas [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Prakash, Giri [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Price, Stephen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Randall, David [Colorado State Univ., Fort Collins, CO (United States); Renslow, Ryan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Riihimaki, Laura [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Ringler, Todd [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Roberts, Andrew [Naval Postgraduate School, Monterey, CA (United States); Rokhsar, Dan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ruebel, Oliver [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Salinger, Andrew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Scheibe, Tim [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Schulz, Roland [Intel, Mountain View, CA (United States); Sivaraman, Chitra [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Smith, Jeremy [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Sreepathi, Sarat [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Steefel, Carl [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Talbot, Jenifer [Boston Univ., Boston, MA (United States); Tantillo, D. J. [Univ. of California, Davis, CA (United States); Tartakovsky, Alex [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Taylor, Mark [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Taylor, Ronald [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Trebotich, David [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Urban, Nathan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Valiev, Marat [Pacific Northwest National Lab. (PNNL), Richland, WA (United States). EMSL; Wagner, Allon [Univ. of California, Berkeley, CA (United States); Wainwright, Haruko [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wieder, Will [NCAR/Univ. of Colorado, Boulder, CO (United States); Wiley, Steven [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Williams, Dean [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Worley, Pat [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Xie, Shaocheng [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Yelick, Kathy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Yoo, Shinjae [Brookhaven National Lab. (BNL), Upton, NY (United States); Yosef, Niri [Univ. of California, Berkeley, CA (United States); Zhang, Minghua [Stony Brook Univ., Stony Brook, NY (United States)

2016-03-31

Understanding the fundamentals of genomic systems or the processes governing impactful weather patterns are examples of the types of simulation and modeling performed on the most advanced computing resources in America. High-performance computing and computational science together provide a necessary platform for the mission science conducted by the Biological and Environmental Research (BER) office at the U.S. Department of Energy (DOE). This report reviews BER’s computing needs and their importance for solving some of the toughest problems in BER’s portfolio. BER’s impact on science has been transformative. Mapping the human genome, including the U.S.-supported international Human Genome Project that DOE began in 1987, initiated the era of modern biotechnology and genomics-based systems biology. And since the 1950s, BER has been a core contributor to atmospheric, environmental, and climate science research, beginning with atmospheric circulation studies that were the forerunners of modern Earth system models (ESMs) and by pioneering the implementation of climate codes onto high-performance computers. See http://exascaleage.org/ber/ for more information.

Large Scale Computing and Storage Requirements for High Energy Physics

Energy Technology Data Exchange (ETDEWEB)

Gerber, Richard A.; Wasserman, Harvey

2010-11-24

The National Energy Research Scientific Computing Center (NERSC) is the leading scientific computing facility for the Department of Energy's Office of Science, providing high-performance computing (HPC) resources to more than 3,000 researchers working on about 400 projects. NERSC provides large-scale computing resources and, crucially, the support and expertise needed for scientists to make effective use of them. In November 2009, NERSC, DOE's Office of Advanced Scientific Computing Research (ASCR), and DOE's Office of High Energy Physics (HEP) held a workshop to characterize the HPC resources needed at NERSC to support HEP research through the next three to five years. The effort is part of NERSC's legacy of anticipating users needs and deploying resources to meet those demands. The workshop revealed several key points, in addition to achieving its goal of collecting and characterizing computing requirements. The chief findings: (1) Science teams need access to a significant increase in computational resources to meet their research goals; (2) Research teams need to be able to read, write, transfer, store online, archive, analyze, and share huge volumes of data; (3) Science teams need guidance and support to implement their codes on future architectures; and (4) Projects need predictable, rapid turnaround of their computational jobs to meet mission-critical time constraints. This report expands upon these key points and includes others. It also presents a number of case studies as representative of the research conducted within HEP. Workshop participants were asked to codify their requirements in this case study format, summarizing their science goals, methods of solution, current and three-to-five year computing requirements, and software and support needs. Participants were also asked to describe their strategy for computing in the highly parallel, multi-core environment that is expected to dominate HPC architectures over the next few years

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

OpenAIRE

Möller, Matthias; Vuik, Cornelis

2017-01-01

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

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

Research on high performance mirrors for free electron lasers

International Nuclear Information System (INIS)

Kitatani, Fumito

1996-01-01

For the stable functioning of free electron laser, high performance optical elements are required because of its characteristics. In particular in short wavelength free electron laser, since its gain is low, the optical elements having very high reflectivity are required. Also in free electron laser, since high energy noise light exists, the optical elements must have high optical breaking strength. At present in Power Reactor and Nuclear Fuel Development Corporation, the research for heightening the performance of dielectric multi-layer film elements for short wavelength is carried out. For manufacturing such high performance elements, it is necessary to develop the new materials for vapor deposition, new vapor deposition process, and the techniques of accurate substrate polishing and inspection. As the material that satisfies the requirements, there is diamond-like carbon (DLC) film, of which the properties are explained. As for the manufacture of the DLC films for short wavelength optics, the test equipment for forming the DLC films, the test of forming the DLC films, the change of the film quality due to gas conditions, discharge conditions and substrate materials, and the measurement of the optical breaking strength are reported. (K.I.)

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.

Performance Engineering Research Institute SciDAC-2 Enabling Technologies Institute Final Report

Energy Technology Data Exchange (ETDEWEB)

Hall, Mary [University of Utah

2014-09-19

Enhancing the performance of SciDAC applications on petascale systems has high priority within DOE SC. As we look to the future, achieving expected levels of performance on high-end com-puting (HEC) systems is growing ever more challenging due to enormous scale, increasing archi-tectural complexity, and increasing application complexity. To address these challenges, PERI has implemented a unified, tripartite research plan encompassing: (1) performance modeling and prediction; (2) automatic performance tuning; and (3) performance engineering of high profile applications. The PERI performance modeling and prediction activity is developing and refining performance models, significantly reducing the cost of collecting the data upon which the models are based, and increasing model fidelity, speed and generality. Our primary research activity is automatic tuning (autotuning) of scientific software. This activity is spurred by the strong user preference for automatic tools and is based on previous successful activities such as ATLAS, which has automatically tuned components of the LAPACK linear algebra library, and other re-cent work on autotuning domain-specific libraries. Our third major component is application en-gagement, to which we are devoting approximately 30% of our effort to work directly with Sci-DAC-2 applications. This last activity not only helps DOE scientists meet their near-term per-formance goals, but also helps keep PERI research focused on the real challenges facing DOE computational scientists as they enter the Petascale Era.

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-06-03

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

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.)

A research program in empirical computer science

Science.gov (United States)

Knight, J. C.

1991-01-01

During the grant reporting period our primary activities have been to begin preparation for the establishment of a research program in experimental computer science. The focus of research in this program will be safety-critical systems. Many questions that arise in the effort to improve software dependability can only be addressed empirically. For example, there is no way to predict the performance of the various proposed approaches to building fault-tolerant software. Performance models, though valuable, are parameterized and cannot be used to make quantitative predictions without experimental determination of underlying distributions. In the past, experimentation has been able to shed some light on the practical benefits and limitations of software fault tolerance. It is common, also, for experimentation to reveal new questions or new aspects of problems that were previously unknown. A good example is the Consistent Comparison Problem that was revealed by experimentation and subsequently studied in depth. The result was a clear understanding of a previously unknown problem with software fault tolerance. The purpose of a research program in empirical computer science is to perform controlled experiments in the area of real-time, embedded control systems. The goal of the various experiments will be to determine better approaches to the construction of the software for computing systems that have to be relied upon. As such it will validate research concepts from other sources, provide new research results, and facilitate the transition of research results from concepts to practical procedures that can be applied with low risk to NASA flight projects. The target of experimentation will be the production software development activities undertaken by any organization prepared to contribute to the research program. Experimental goals, procedures, data analysis and result reporting will be performed for the most part by the University of Virginia.

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

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

Disentangling the Relationship Between the Adoption of In-Memory Computing and Firm Performance

DEFF Research Database (Denmark)

Fay, Marua; Müller, Oliver; vom Brocke, Jan

2016-01-01

Recent growth in data volume, variety, and velocity led to an increased demand for high-performance data processing and analytics solutions. In-memory computing (IMC) enables organizations to boost their information processing capacity, and is widely acknowledged to be one of the leading strategic...... at explaining the relationship between the adoption of IMC solutions and firm performance. In this research-in-progress paper we discuss the theoretical background of our work, describe the proposed research design, and develop five hypotheses for later testing. Our work aims at contributing to the research...

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)

Outcomes and challenges of global high-resolution non-hydrostatic atmospheric simulations using the K computer

Science.gov (United States)

Satoh, Masaki; Tomita, Hirofumi; Yashiro, Hisashi; Kajikawa, Yoshiyuki; Miyamoto, Yoshiaki; Yamaura, Tsuyoshi; Miyakawa, Tomoki; Nakano, Masuo; Kodama, Chihiro; Noda, Akira T.; Nasuno, Tomoe; Yamada, Yohei; Fukutomi, Yoshiki

2017-12-01

This article reviews the major outcomes of a 5-year (2011-2016) project using the K computer to perform global numerical atmospheric simulations based on the non-hydrostatic icosahedral atmospheric model (NICAM). The K computer was made available to the public in September 2012 and was used as a primary resource for Japan's Strategic Programs for Innovative Research (SPIRE), an initiative to investigate five strategic research areas; the NICAM project fell under the research area of climate and weather simulation sciences. Combining NICAM with high-performance computing has created new opportunities in three areas of research: (1) higher resolution global simulations that produce more realistic representations of convective systems, (2) multi-member ensemble simulations that are able to perform extended-range forecasts 10-30 days in advance, and (3) multi-decadal simulations for climatology and variability. Before the K computer era, NICAM was used to demonstrate realistic simulations of intra-seasonal oscillations including the Madden-Julian oscillation (MJO), merely as a case study approach. Thanks to the big leap in computational performance of the K computer, we could greatly increase the number of cases of MJO events for numerical simulations, in addition to integrating time and horizontal resolution. We conclude that the high-resolution global non-hydrostatic model, as used in this five-year project, improves the ability to forecast intra-seasonal oscillations and associated tropical cyclogenesis compared with that of the relatively coarser operational models currently in use. The impacts of the sub-kilometer resolution simulation and the multi-decadal simulations using NICAM are also reviewed.

Summary of researches being performed in the Institute of Mathematics and Computer Science on computer science and information technologies

Directory of Open Access Journals (Sweden)

Artiom Alhazov

2008-07-01

Full Text Available Evolution of the informatization notion (which assumes automation of majority of human activities applying computers, computer networks, information technologies towards the notion of {\\it Global Information Society} (GIS challenges the determination of new paradigms of society: automation and intellectualization of production, new level of education and teaching, formation of new styles of work, active participation in decision making, etc. To assure transition to GIS for any society, including that from Republic of Moldova, requires both special training and broad application of progressive technologies and information systems. Methodological aspects concerning impact of GIS creation over the citizen, economic unit, national economy in the aggregate demands a profound study. Without systematic approach to these aspects the GIS creation would have confront great difficulties. Collective of researchers from the Institute of Mathematics and Computer Science (IMCS of Academy of Sciences of Moldova, which work in the field of computer science, constitutes the center of advanced researches and activates in those directions of researches of computer science which facilitate technologies and applications without of which the development of GIS cannot be assured.

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.

Conference on High Performance Software for Nonlinear Optimization

CERN Document Server

Murli, Almerico; Pardalos, Panos; Toraldo, Gerardo

1998-01-01

This book contains a selection of papers presented at the conference on High Performance Software for Nonlinear Optimization (HPSN097) which was held in Ischia, Italy, in June 1997. The rapid progress of computer technologies, including new parallel architec­ tures, has stimulated a large amount of research devoted to building software environments and defining algorithms able to fully exploit this new computa­ tional power. In some sense, numerical analysis has to conform itself to the new tools. The impact of parallel computing in nonlinear optimization, which had a slow start at the beginning, seems now to increase at a fast rate, and it is reasonable to expect an even greater acceleration in the future. As with the first HPSNO conference, the goal of the HPSN097 conference was to supply a broad overview of the more recent developments and trends in nonlinear optimization, emphasizing the algorithmic and high performance software aspects. Bringing together new computational methodologies with theoretical...

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.

MAPLE research reactor beam-tube performance

International Nuclear Information System (INIS)

Lee, A.G.; Lidstone, R.F.; Gillespie, G.E.

1989-05-01

Atomic Energy of Canada Limited (AECL) has been developing the MAPLE (Multipurpose Applied Physics Lattice Experimental) reactor concept as a medium-flux neutron source to meet contemporary research reactor applications. This paper gives a brief description of the MAPLE reactor and presents some results of computer simulations used to analyze the neutronic performance. The computer simulations were performed to identify how the MAPLE reactor may be adapted to beam-tube applications such as neutron radiography

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...

Exploring Subpixel Learning Algorithms for Estimating Global Land Cover Fractions from Satellite Data Using High Performance Computing

Directory of Open Access Journals (Sweden)

Uttam Kumar

2017-10-01

Full Text Available Land cover (LC refers to the physical and biological cover present over the Earth’s surface in terms of the natural environment such as vegetation, water, bare soil, etc. Most LC features occur at finer spatial scales compared to the resolution of primary remote sensing satellites. Therefore, observed data are a mixture of spectral signatures of two or more LC features resulting in mixed pixels. One solution to the mixed pixel problem is the use of subpixel learning algorithms to disintegrate the pixel spectrum into its constituent spectra. Despite the popularity and existing research conducted on the topic, the most appropriate approach is still under debate. As an attempt to address this question, we compared the performance of several subpixel learning algorithms based on least squares, sparse regression, signal–subspace and geometrical methods. Analysis of the results obtained through computer-simulated and Landsat data indicated that fully constrained least squares (FCLS outperformed the other techniques. Further, FCLS was used to unmix global Web-Enabled Landsat Data to obtain abundances of substrate (S, vegetation (V and dark object (D classes. Due to the sheer nature of data and computational needs, we leveraged the NASA Earth Exchange (NEX high-performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into four classes, namely forest, farmland, water and urban areas (in conjunction with nighttime lights data over California, USA using a random forest classifier. Validation of these LC maps with the National Land Cover Database 2011 products and North American Forest Dynamics static forest map shows a 6% improvement in unmixing-based classification relative to per-pixel classification. As such, abundance maps continue to offer a useful alternative to high-spatial-resolution classified maps for forest inventory analysis, multi

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

HPCToolkit: performance tools for scientific computing

Energy Technology Data Exchange (ETDEWEB)

Tallent, N; Mellor-Crummey, J; Adhianto, L; Fagan, M; Krentel, M [Department of Computer Science, Rice University, Houston, TX 77005 (United States)

2008-07-15

As part of the U.S. Department of Energy's Scientific Discovery through Advanced Computing (SciDAC) program, science teams are tackling problems that require simulation and modeling on petascale computers. As part of activities associated with the SciDAC Center for Scalable Application Development Software (CScADS) and the Performance Engineering Research Institute (PERI), Rice University is building software tools for performance analysis of scientific applications on the leadership-class platforms. In this poster abstract, we briefly describe the HPCToolkit performance tools and how they can be used to pinpoint bottlenecks in SPMD and multi-threaded parallel codes. We demonstrate HPCToolkit's utility by applying it to two SciDAC applications: the S3D code for simulation of turbulent combustion and the MFDn code for ab initio calculations of microscopic structure of nuclei.

HPCToolkit: performance tools for scientific computing

International Nuclear Information System (INIS)

Tallent, N; Mellor-Crummey, J; Adhianto, L; Fagan, M; Krentel, M

2008-01-01

As part of the U.S. Department of Energy's Scientific Discovery through Advanced Computing (SciDAC) program, science teams are tackling problems that require simulation and modeling on petascale computers. As part of activities associated with the SciDAC Center for Scalable Application Development Software (CScADS) and the Performance Engineering Research Institute (PERI), Rice University is building software tools for performance analysis of scientific applications on the leadership-class platforms. In this poster abstract, we briefly describe the HPCToolkit performance tools and how they can be used to pinpoint bottlenecks in SPMD and multi-threaded parallel codes. We demonstrate HPCToolkit's utility by applying it to two SciDAC applications: the S3D code for simulation of turbulent combustion and the MFDn code for ab initio calculations of microscopic structure of nuclei

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

Computing in Research.

Science.gov (United States)

Ashenhurst, Robert L.

The introduction and diffusion of automatic computing facilities during the 1960's is reviewed; it is described as a time when research strategies in a broad variety of disciplines changed to take advantage of the newfound power provided by the computer. Several types of typical problems encountered by researchers who adopted the new technologies,…

Application of High-performance Visual Analysis Methods to Laser Wakefield Particle Acceleration Data

International Nuclear Information System (INIS)

Rubel, Oliver; Prabhat, Mr.; Wu, Kesheng; Childs, Hank; Meredith, Jeremy; Geddes, Cameron G.R.; Cormier-Michel, Estelle; Ahern, Sean; Weber, Gunther H.; Messmer, Peter; Hagen, Hans; Hamann, Bernd; Bethel, E. Wes

2008-01-01

Our work combines and extends techniques from high-performance scientific data management and visualization to enable scientific researchers to gain insight from extremely large, complex, time-varying laser wakefield particle accelerator simulation data. We extend histogram-based parallel coordinates for use in visual information display as well as an interface for guiding and performing data mining operations, which are based upon multi-dimensional and temporal thresholding and data subsetting operations. To achieve very high performance on parallel computing platforms, we leverage FastBit, a state-of-the-art index/query technology, to accelerate data mining and multi-dimensional histogram computation. We show how these techniques are used in practice by scientific researchers to identify, visualize and analyze a particle beam in a large, time-varying dataset

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...

Evaluation of External Memory Access Performance on a High-End FPGA Hybrid Computer

Directory of Open Access Journals (Sweden)

Konstantinos Kalaitzis

2016-10-01

Full Text Available The motivation of this research was to evaluate the main memory performance of a hybrid super computer such as the Convey HC-x, and ascertain how the controller performs in several access scenarios, vis-à-vis hand-coded memory prefetches. Such memory patterns are very useful in stencil computations. The theoretical bandwidth of the memory of the Convey is compared with the results of our measurements. The accurate study of the memory subsystem is particularly useful for users when they are developing their application-specific personality. Experiments were performed to measure the bandwidth between the coprocessor and the memory subsystem. The experiments aimed mainly at measuring the reading access speed of the memory from Application Engines (FPGAs. Different ways of accessing data were used in order to find the most efficient way to access memory. This way was proposed for future work in the Convey HC-x. When performing a series of accesses to memory, non-uniform latencies occur. The Memory Controller of the Convey HC-x in the coprocessor attempts to cover this latency. We measure memory efficiency as a ratio of the number of memory accesses and the number of execution cycles. The result of this measurement converges to one in most cases. In addition, we performed experiments with hand-coded memory accesses. The analysis of the experimental results shows how the memory subsystem and Memory Controllers work. From this work we conclude that the memory controllers do an excellent job, largely because (transparently to the user they seem to cache large amounts of data, and hence hand-coding is not needed in most situations.

System Software and Tools for High Performance Computing Environments: A report on the findings of the Pasadena Workshop, April 14--16, 1992

Energy Technology Data Exchange (ETDEWEB)

Sterling, T. [Universities Space Research Association, Washington, DC (United States); Messina, P. [Jet Propulsion Lab., Pasadena, CA (United States); Chen, M. [Yale Univ., New Haven, CT (United States)] [and others

1993-04-01

The Pasadena Workshop on System Software and Tools for High Performance Computing Environments was held at the Jet Propulsion Laboratory from April 14 through April 16, 1992. The workshop was sponsored by a number of Federal agencies committed to the advancement of high performance computing (HPC) both as a means to advance their respective missions and as a national resource to enhance American productivity and competitiveness. Over a hundred experts in related fields from industry, academia, and government were invited to participate in this effort to assess the current status of software technology in support of HPC systems. The overall objectives of the workshop were to understand the requirements and current limitations of HPC software technology and to contribute to a basis for establishing new directions in research and development for software technology in HPC environments. This report includes reports written by the participants of the workshop`s seven working groups. Materials presented at the workshop are reproduced in appendices. Additional chapters summarize the findings and analyze their implications for future directions in HPC software technology development.

NASA's computer science research program

Science.gov (United States)

Larsen, R. L.

1983-01-01

Following a major assessment of NASA's computing technology needs, a new program of computer science research has been initiated by the Agency. The program includes work in concurrent processing, management of large scale scientific databases, software engineering, reliable computing, and artificial intelligence. The program is driven by applications requirements in computational fluid dynamics, image processing, sensor data management, real-time mission control and autonomous systems. It consists of university research, in-house NASA research, and NASA's Research Institute for Advanced Computer Science (RIACS) and Institute for Computer Applications in Science and Engineering (ICASE). The overall goal is to provide the technical foundation within NASA to exploit advancing computing technology in aerospace applications.

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.

Research Institute for Advanced Computer Science: Annual Report October 1998 through September 1999

Science.gov (United States)

Leiner, Barry M.; Gross, Anthony R. (Technical Monitor)

1999-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center (ARC). It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. ARC has been designated NASA's Center of Excellence in Information Technology. In this capacity, ARC is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA ARC and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to

High Energy Physics Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and High Energy Physics, June 10-12, 2015, Bethesda, Maryland

Energy Technology Data Exchange (ETDEWEB)

Habib, Salman [Argonne National Lab. (ANL), Argonne, IL (United States); Roser, Robert [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Gerber, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Antypas, Katie [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Dart, Eli [Esnet, Berkeley, CA (United States); Dosanjh, Sudip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hack, James [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Monga, Inder [Esnet, Berkeley, CA (United States); Papka, Michael E. [Argonne National Lab. (ANL), Argonne, IL (United States); Riley, Katherine [Argonne National Lab. (ANL), Argonne, IL (United States); Rotman, Lauren [Esnet, Berkeley, CA (United States); Straatsma, Tjerk [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wells, Jack [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Williams, Tim [Argonne National Lab. (ANL), Argonne, IL (United States); Almgren, A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Amundson, J. [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Bailey, Stephen [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bard, Deborah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bloom, Ken [Univ. of Nebraska, Lincoln, NE (United States); Bockelman, Brian [Univ. of Nebraska, Lincoln, NE (United States); Borgland, Anders [SLAC National Accelerator Lab., Menlo Park, CA (United States); Borrill, Julian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Boughezal, Radja [Argonne National Lab. (ANL), Argonne, IL (United States); Brower, Richard [Boston Univ., MA (United States); Cowan, Benjamin [SLAC National Accelerator Lab., Menlo Park, CA (United States); Finkel, Hal [Argonne National Lab. (ANL), Argonne, IL (United States); Frontiere, Nicholas [Argonne National Lab. (ANL), Argonne, IL (United States); Fuess, Stuart [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Ge, Lixin [SLAC National Accelerator Lab., Menlo Park, CA (United States); Gnedin, Nick [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Gottlieb, Steven [Indiana Univ., Bloomington, IN (United States); Gutsche, Oliver [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Han, T. [Indiana Univ., Bloomington, IN (United States); Heitmann, Katrin [Argonne National Lab. (ANL), Argonne, IL (United States); Hoeche, Stefan [SLAC National Accelerator Lab., Menlo Park, CA (United States); Ko, Kwok [SLAC National Accelerator Lab., Menlo Park, CA (United States); Kononenko, Oleksiy [SLAC National Accelerator Lab., Menlo Park, CA (United States); LeCompte, Thomas [Argonne National Lab. (ANL), Argonne, IL (United States); Li, Zheng [SLAC National Accelerator Lab., Menlo Park, CA (United States); Lukic, Zarija [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Mori, Warren [Univ. of California, Los Angeles, CA (United States); Ng, Cho-Kuen [SLAC National Accelerator Lab., Menlo Park, CA (United States); Nugent, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Oleynik, Gene [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); O’Shea, Brian [Michigan State Univ., East Lansing, MI (United States); Padmanabhan, Nikhil [Yale Univ., New Haven, CT (United States); Petravick, Donald [Univ. of Illinois, Urbana, IL (United States). National Center for Supercomputing Applications; Petriello, Frank J. [Argonne National Lab. (ANL), Argonne, IL (United States); Pope, Adrian [Argonne National Lab. (ANL), Argonne, IL (United States); Power, John [Argonne National Lab. (ANL), Argonne, IL (United States); Qiang, Ji [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Reina, Laura [Florida State Univ., Tallahassee, FL (United States); Rizzo, Thomas Gerard [SLAC National Accelerator Lab., Menlo Park, CA (United States); Ryne, Robert [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Schram, Malachi [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Spentzouris, P. [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Toussaint, Doug [Univ. of Arizona, Tucson, AZ (United States); Vay, Jean Luc [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Viren, B. [Brookhaven National Lab. (BNL), Upton, NY (United States); Wuerthwein, Frank [Univ. of California, San Diego, CA (United States); Xiao, Liling [SLAC National Accelerator Lab., Menlo Park, CA (United States); Coffey, Richard [Argonne National Lab. (ANL), Argonne, IL (United States)

2016-11-29

The U.S. Department of Energy (DOE) Office of Science (SC) Offices of High Energy Physics (HEP) and Advanced Scientific Computing Research (ASCR) convened a programmatic Exascale Requirements Review on June 10–12, 2015, in Bethesda, Maryland. This report summarizes the findings, results, and recommendations derived from that meeting. The high-level findings and observations are as follows. Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude — and in some cases greater — than that available currently. The growth rate of data produced by simulations is overwhelming the current ability of both facilities and researchers to store and analyze it. Additional resources and new techniques for data analysis are urgently needed. Data rates and volumes from experimental facilities are also straining the current HEP infrastructure in its ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. A close integration of high-performance computing (HPC) simulation and data analysis will greatly aid in interpreting the results of HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. Long-range planning between HEP and ASCR will be required to meet HEP’s research needs. To best use ASCR HPC resources, the experimental HEP program needs (1) an established, long-term plan for access to ASCR computational and data resources, (2) the ability to map workflows to HPC resources, (3) the ability for ASCR facilities to accommodate workflows run by collaborations potentially comprising thousands of individual members, (4) to transition codes to the next-generation HPC platforms that will be available at ASCR

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

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.

Computer proficiency questionnaire: assessing low and high computer proficient seniors.

Science.gov (United States)

Boot, Walter R; Charness, Neil; Czaja, Sara J; Sharit, Joseph; Rogers, Wendy A; Fisk, Arthur D; Mitzner, Tracy; Lee, Chin Chin; Nair, Sankaran

2015-06-01

Computers and the Internet have the potential to enrich the lives of seniors and aid in the performance of important tasks required for independent living. A prerequisite for reaping these benefits is having the skills needed to use these systems, which is highly dependent on proper training. One prerequisite for efficient and effective training is being able to gauge current levels of proficiency. We developed a new measure (the Computer Proficiency Questionnaire, or CPQ) to measure computer proficiency in the domains of computer basics, printing, communication, Internet, calendaring software, and multimedia use. Our aim was to develop a measure appropriate for individuals with a wide range of proficiencies from noncomputer users to extremely skilled users. To assess the reliability and validity of the CPQ, a diverse sample of older adults, including 276 older adults with no or minimal computer experience, was recruited and asked to complete the CPQ. The CPQ demonstrated excellent reliability (Cronbach's α = .98), with subscale reliabilities ranging from .86 to .97. Age, computer use, and general technology use all predicted CPQ scores. Factor analysis revealed three main factors of proficiency related to Internet and e-mail use; communication and calendaring; and computer basics. Based on our findings, we also developed a short-form CPQ (CPQ-12) with similar properties but 21 fewer questions. The CPQ and CPQ-12 are useful tools to gauge computer proficiency for training and research purposes, even among low computer proficient older adults. © The Author 2013. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

Research directions in computer engineering. Report of a workshop

Energy Technology Data Exchange (ETDEWEB)

Freeman, H

1982-09-01

The results of a workshop held in November 1981 in Washington, DC, to outline research directions for computer engineering are reported upon. The purpose of the workshop was to provide guidance to government research funding agencies, as well as to universities and industry, as to the directions which computer engineering research should take for the next five to ten years. A select group of computer engineers was assembled, drawn from all over the United States and with expertise in virtually every aspect of today's computer technology. Industrial organisations and universities were represented in roughly equal numbers. The panel proceeded to provide a sharper definition of computer engineering than had been in popular use previously, to identify the social and national needs which provide the basis for encouraging research, to probe for obstacles to research and seek means of overcoming them and to delineate high-priority areas in which computer engineering research should be fostered. These included experimental software engineering, architectures in support of programming style, computer graphics, pattern recognition. VLSI design tools, machine intelligence, programmable automation, architectures for speech and signal processing, computer architecture and robotics. 13 references.

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 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.

Center for Computing Research Summer Research Proceedings 2015.

Energy Technology Data Exchange (ETDEWEB)

Bradley, Andrew Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Parks, Michael L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-12-18

The Center for Computing Research (CCR) at Sandia National Laboratories organizes a summer student program each summer, in coordination with the Computer Science Research Institute (CSRI) and Cyber Engineering Research Institute (CERI).

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

An energy-efficient high-performance processor with reconfigurable data-paths using RSFQ circuits

International Nuclear Information System (INIS)

Takagi, Naofumi

2013-01-01

Highlights: ► An idea of a high-performance computer using RSFQ circuits is shown. ► An outline of processor with reconfigurable data-paths (RDPs) is shown. ► Architectural details of an SFQ-RDP are described. -- Abstract: We show recent progress in our research on an energy-efficient high-performance processor with reconfigurable data-paths (RDPs) using rapid single-flux-quantum (RSFQ) circuits. We mainly describe the architectural details of an RDP implemented using RSFQ circuits. An RDP consists of a lot of floating-point units (FPUs) and operand routing networks (ORNs) which connect the FPUs. We reconfigure the RDP to fit a computation, i.e., a group of floating-point operations, appearing in a ‘for’ loop of programs for numerical computations by setting the route in ORNs before the execution of the loop. In the RDP, a lot of FPUs work in parallel with pipelined fashion, and hence, very high-performance computation is achieved

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.

The effects of laboratory inquire-based experiments and computer simulations on high school students‘ performance and cognitive load in physics teaching

Directory of Open Access Journals (Sweden)

Radulović Branka

2016-01-01

Full Text Available The main goal of this study was to examine the extent to which different teaching instructions focused on the application of laboratory inquire-based experiments (LIBEs and interactive computer based simulations (ICBSs improved understanding of physical contents in high school students, compared to traditional teaching approach. Additionally, the study examined how the applied instructions influenced students’ assessment of invested cognitive load. A convenience sample of this research included 187 high school students. A multiple-choice test of knowledge was used as a measuring instrument for the students’ performance. Each task in the test was followed by the five-point Likert-type scale for the evaluation of invested cognitive load. In addition to descriptive statistics, determination of significant differences in performance and cognitive load as well as the calculation of instructional efficiency of applied instructional design, computed one-factor analysis of variance and Tukey’s post-hoc test. The findings indicate that teaching instructions based on the use of LIBEs and ICBSs equally contribute to an increase in students’ performance and the reduction of cognitive load unlike traditional teaching of Physics. The results obtained by the students from the LIBEs and ICBSs groups for calculated instructional efficiency suggest that the applied teaching strategies represent effective teaching instructions. [Projekat Ministarstva nauke Republike Srbije, br. 179010: The Quality of Education System in Serbia from European Perspective

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

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

High Burnup Fuel Performance and Safety Research

Energy Technology Data Exchange (ETDEWEB)

Bang, Je Keun; Lee, Chan Bok; Kim, Dae Ho (and others)

2007-03-15

The worldwide trend of nuclear fuel development is to develop a high burnup and high performance nuclear fuel with high economies and safety. Because the fuel performance evaluation code, INFRA, has a patent, and the superiority for prediction of fuel performance was proven through the IAEA CRP FUMEX-II program, the INFRA code can be utilized with commercial purpose in the industry. The INFRA code was provided and utilized usefully in the universities and relevant institutes domesticallly and it has been used as a reference code in the industry for the development of the intrinsic fuel rod design code.

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-06-20

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

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

Science.gov (United States)

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

2014-01-01

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

Australia's new high performance research reactor

International Nuclear Information System (INIS)

Miller, R.; Abbate, P.M.

2003-01-01

A contract for the design and construction of the Replacement Research Reactor was signed in July 2000 between ANSTO and INVAP from Argentina. Since then the detailed design has been completed, a construction authorization has been obtained, and construction has commenced. The reactor design embodies modern safety thinking together with innovative solutions to ensure a highly safe and reliable plant. Also significant effort has been placed on providing the facility with diverse and ample facilities to maximize its use for irradiating material for radioisotope production as well as providing high neutron fluxes for neutron beam research. The project management organization and planing is commensurate with the complexity of the project and the number of players involved. (author)

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.

Parallel computing in genomic research: advances and applications.

Science.gov (United States)

Ocaña, Kary; de Oliveira, Daniel

2015-01-01

Today's genomic experiments have to process the so-called "biological big data" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities.

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.

Automatic processing of radioimmunological research data on a computer

International Nuclear Information System (INIS)

Korolyuk, I.P.; Gorodenko, A.N.; Gorodenko, S.I.

1979-01-01

A program ''CRITEST'' in the language PL/1 for the EC computer intended for automatic processing of the results of radioimmunological research has been elaborated. The program works in the operation system of the OC EC computer and is performed in the section OC 60 kb. When compiling the program Eitken's modified algorithm was used. The program was clinically approved when determining a number of hormones: CTH, T 4 , T 3 , TSH. The automatic processing of the radioimmunological research data on the computer makes it possible to simplify the labour-consuming analysis and to raise its accuracy

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.

Reports on research achievements in developing high-performance industrial furnaces in fiscal 1998 (Research and development of high-performance industrial furnaces). Volume 1; 1998 nendo koseino kogyoro nado ni kansuru kenkyu kaihatsu seika hokokusho. 1

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-03-01

From the reports on research achievements in developing high-performance industrial furnaces in fiscal 1998, the report volume 1 was prepared as a research achievement report of each working group, detailing fundamental researches, heating furnaces, and heat treatment furnaces. The fundamental researches have researched combustion evaluating technology, characteristics of the area in the vicinity of a combustor, characteristics of combustion of high-temperature air, heating characteristics of a furnace to investigate effect of local heat absorption, and combustion evaluation. For the heating furnaces, the following subjects were studied: development of an in-furnace combustion model, summary of an experiment for evaluating high-temperature air combustion, furnace height relative to combustion heat transfer characteristics, heat loss minimizing technology, combustion heat transfer characteristics of liquid fuels, optimal operation of the high-temperature air combustion, basic control in heating control, and steel piece heating control. Studies were performed for the heat treatment furnaces on the case of a direct firing furnace in evaluating the heat transfer characteristics, the case of a radiant tube furnace, application of thermal fluid simulation technology, furnace averaging technology, soot reducing technology, control technology, and trial design on a high-performance heat treatment furnace. (NEDO)

Computational chemistry in pharmaceutical research: at the crossroads.

Science.gov (United States)

Bajorath, Jürgen

2012-01-01

Computational approaches are an integral part of pharmaceutical research. However, there are many of unsolved key questions that limit the scientific progress in the still evolving computational field and its impact on drug discovery. Importantly, a number of these questions are not new but date back many years. Hence, it might be difficult to conclusively answer them in the foreseeable future. Moreover, the computational field as a whole is characterized by a high degree of heterogeneity and so is, unfortunately, the quality of its scientific output. In light of this situation, it is proposed that changes in scientific standards and culture should be seriously considered now in order to lay a foundation for future progress in computational research.

The Overall Research Results of Prestressed I-beams Made of Ultra-high Performance Concrete

Science.gov (United States)

Tej, P.; Kolísko, J.; Kněž, P.; Čech, J.

2017-09-01

The design process of short-term and long-term loading of prestressed I-beams made of ultra-high performance concrete (UHPC) and the overall research results are presented in this article. The prestressed I-beams are intended and designed to replace steel HEB beams mainly in the construction of railway bridges with fully concreted height of the beams. These types of structures have the advantage of a low construction height. The prestressed I-beams were made of UHPC with dispersed steel fibres and are reinforced by prestressing cables in the bottom flange. Two specimens of 9 m span, three specimens of 7 m span and two specimens of 12 m span were made for the short-term loading. For the purpose of the long-term loading, two specimens of 12 m span were made and subsequently loaded for 450 days. All specimens were tested in four-point bending tests in the laboratory. The article presents also comparison of results of the experiments with computer simulations.

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

Research of Performance Linux Kernel File Systems

Directory of Open Access Journals (Sweden)

Andrey Vladimirovich Ostroukh

2015-10-01

Full Text Available The article describes the most common Linux Kernel File Systems. The research was carried out on a personal computer, the characteristics of which are written in the article. The study was performed on a typical workstation running GNU/Linux with below characteristics. On a personal computer for measuring the file performance, has been installed the necessary software. Based on the results, conclusions and proposed recommendations for use of file systems. Identified and recommended by the best ways to store data.

Review of research on advanced computational science in FY2016

International Nuclear Information System (INIS)

2017-12-01

Research on advanced computational science for nuclear applications, based on “Plan to Achieve Medium- to Long-term Objectives of the Japan Atomic Energy Agency (Medium- to Long-term Plan)”, has been performed at Center for Computational Science and e-Systems (CCSE), Japan Atomic Energy Agency. CCSE established the committee consisting of outside experts and authorities which does research evaluation and advices for the assistance of the research and development. This report summarizes the followings. (1) Results of the R and D performed at CCSE in FY 2016 (April 1st, 2016 - March 31st, 2017), (2) Results of the evaluation on the R and D by the committee in FY 2016. (author)

Use of the Web by a Distributed Research group Performing Distributed Computing

Science.gov (United States)

Burke, David A.; Peterkin, Robert E.

2001-06-01

A distributed research group that uses distributed computers faces a spectrum of challenges--some of which can be met by using various electronic means of communication. The particular challenge of our group involves three physically separated research entities. We have had to link two collaborating groups at AFRL and NRL together for software development, and the same AFRL group with a LANL group for software applications. We are developing and using a pair of general-purpose, portable, parallel, unsteady, plasma physics simulation codes. The first collaboration is centered around a formal weekly video teleconference on relatively inexpensive equipment that we have set up in convenient locations in our respective laboratories. The formal virtual meetings are augmented with informal virtual meetings as the need arises. Both collaborations share research data in a variety of forms on a secure URL that is set up behind the firewall at the AFRL. Of course, a computer-generated animation is a particularly efficient way of displaying results from time-dependent numerical simulations, so we generally like to post such animations (along with proper documentation) on our web page. In this presentation, we will discuss some of our accomplishments and disappointments.

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....

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

Science.gov (United States)

2009-04-01

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

Computer Science Research at Langley

Science.gov (United States)

Voigt, S. J. (Editor)

1982-01-01

A workshop was held at Langley Research Center, November 2-5, 1981, to highlight ongoing computer science research at Langley and to identify additional areas of research based upon the computer user requirements. A panel discussion was held in each of nine application areas, and these are summarized in the proceedings. Slides presented by the invited speakers are also included. A survey of scientific, business, data reduction, and microprocessor computer users helped identify areas of focus for the workshop. Several areas of computer science which are of most concern to the Langley computer users were identified during the workshop discussions. These include graphics, distributed processing, programmer support systems and tools, database management, and numerical methods.

Agglomeration Economies and the High-Tech Computer

OpenAIRE

Wallace, Nancy E.; Walls, Donald

2004-01-01

This paper considers the effects of agglomeration on the production decisions of firms in the high-tech computer cluster. We build upon an alternative definition of the high-tech computer cluster developed by Bardhan et al. (2003) and we exploit a new data source, the National Establishment Time-Series (NETS) Database, to analyze the spatial distribution of firms in this industry. An essential contribution of this research is the recognition that high-tech firms are heterogeneous collections ...

High Performance Proactive Digital Forensics

International Nuclear Information System (INIS)

Alharbi, Soltan; Traore, Issa; Moa, Belaid; Weber-Jahnke, Jens

2012-01-01

With the increase in the number of digital crimes and in their sophistication, High Performance Computing (HPC) is becoming a must in Digital Forensics (DF). According to the FBI annual report, the size of data processed during the 2010 fiscal year reached 3,086 TB (compared to 2,334 TB in 2009) and the number of agencies that requested Regional Computer Forensics Laboratory assistance increasing from 689 in 2009 to 722 in 2010. Since most investigation tools are both I/O and CPU bound, the next-generation DF tools are required to be distributed and offer HPC capabilities. The need for HPC is even more evident in investigating crimes on clouds or when proactive DF analysis and on-site investigation, requiring semi-real time processing, are performed. Although overcoming the performance challenge is a major goal in DF, as far as we know, there is almost no research on HPC-DF except for few papers. As such, in this work, we extend our work on the need of a proactive system and present a high performance automated proactive digital forensic system. The most expensive phase of the system, namely proactive analysis and detection, uses a parallel extension of the iterative z algorithm. It also implements new parallel information-based outlier detection algorithms to proactively and forensically handle suspicious activities. To analyse a large number of targets and events and continuously do so (to capture the dynamics of the system), we rely on a multi-resolution approach to explore the digital forensic space. Data set from the Honeynet Forensic Challenge in 2001 is used to evaluate the system from DF and HPC perspectives.

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

Directory of Open Access Journals (Sweden)

Ginés D. Guerrero

2014-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2018-01-22

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

High Performance Computing and Visualization Infrastructure for Simultaneous Parallel Computing and Parallel Visualization Research

Science.gov (United States)

2016-11-09

Total Number: Sub Contractors (DD882) Names of Personnel receiving masters degrees Names of personnel receiving PHDs Names of other research staff...Broadcom 5720 QP 1Gb Network Daughter Card (2) Intel Xeon E5-2680 v3 2.5GHz, 30M Cache, 9.60GT/s QPI, Turbo, HT , 12C/24T (120W...Broadcom 5720 QP 1Gb Network Daughter Card (2) Intel Xeon E5-2680 v3 2.5GHz, 30M Cache, 9.60GT/s QPI, Turbo, HT , 12C/24T (120W

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)

Big Data solutions on a small scale: Evaluating accessible high-performance computing for social research

OpenAIRE

Murthy, Dhiraj; Bowman, S. A.

2014-01-01

Though full of promise, Big Data research success is often contingent on access to the newest, most advanced, and often expensive hardware systems and the expertise needed to build and implement such systems. As a result, the accessibility of the growing number of Big Data-capable technology solutions has often been the preserve of business analytics. Pay as you store/process services like Amazon Web Services have opened up possibilities for smaller scale Big Data projects. There is high dema...

Big Data solutions on a small scale: Evaluating accessible high-performance computing for social research

Directory of Open Access Journals (Sweden)

Dhiraj Murthy

2014-11-01

Full Text Available Though full of promise, Big Data research success is often contingent on access to the newest, most advanced, and often expensive hardware systems and the expertise needed to build and implement such systems. As a result, the accessibility of the growing number of Big Data-capable technology solutions has often been the preserve of business analytics. Pay as you store/process services like Amazon Web Services have opened up possibilities for smaller scale Big Data projects. There is high demand for this type of research in the digital humanities and digital sociology, for example. However, scholars are increasingly finding themselves at a disadvantage as available data sets of interest continue to grow in size and complexity. Without a large amount of funding or the ability to form interdisciplinary partnerships, only a select few find themselves in the position to successfully engage Big Data. This article identifies several notable and popular Big Data technologies typically implemented using large and extremely powerful cloud-based systems and investigates the feasibility and utility of development of Big Data analytics systems implemented using low-cost commodity hardware in basic and easily maintainable configurations for use within academic social research. Through our investigation and experimental case study (in the growing field of social Twitter analytics, we found that not only are solutions like Cloudera’s Hadoop feasible, but that they can also enable robust, deep, and fruitful research outcomes in a variety of use-case scenarios across the disciplines.

Young Researchers Advancing Computational Science: Perspectives of the Young Scientists Conference 2015

CERN Document Server

Boukhanovsky, Alexander V; Krzhizhanovskaya, Valeria V; Athanassoulis, Gerassimos A; Klimentov, Alexei A; Sloot, Peter M A

2015-01-01

We present an annual international Young Scientists Conference (YSC) on computational science http://ysc.escience.ifmo.ru/, which brings together renowned experts and young researchers working in high-performance computing, data-driven modeling, and simulation of large-scale complex systems. The first YSC event was organized in 2012 by the University of Amsterdam, the Netherlands and ITMO University, Russia with the goal of opening a dialogue on the present and the future of computational science and its applications. We believe that the YSC conferences will strengthen the ties between young scientists in different countries, thus promoting future collaboration. In this paper we briefly introduce the challenges the millennial generation is facing; describe the YSC conference history and topics; and list the keynote speakers and program committee members. This volume of Procedia Computer Science presents selected papers from the 4th International Young Scientists Conference on Computational Science held on 25 ...

WImpiBLAST: web interface for mpiBLAST to help biologists perform large-scale annotation using high performance computing.

Directory of Open Access Journals (Sweden)

Parichit Sharma

Full Text Available The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture

WImpiBLAST: web interface for mpiBLAST to help biologists perform large-scale annotation using high performance computing.

Science.gov (United States)

Sharma, Parichit; Mantri, Shrikant S

2014-01-01

The function of a newly sequenced gene can be discovered by determining its sequence homology with known proteins. BLAST is the most extensively used sequence analysis program for sequence similarity search in large databases of sequences. With the advent of next generation sequencing technologies it has now become possible to study genes and their expression at a genome-wide scale through RNA-seq and metagenome sequencing experiments. Functional annotation of all the genes is done by sequence similarity search against multiple protein databases. This annotation task is computationally very intensive and can take days to obtain complete results. The program mpiBLAST, an open-source parallelization of BLAST that achieves superlinear speedup, can be used to accelerate large-scale annotation by using supercomputers and high performance computing (HPC) clusters. Although many parallel bioinformatics applications using the Message Passing Interface (MPI) are available in the public domain, researchers are reluctant to use them due to lack of expertise in the Linux command line and relevant programming experience. With these limitations, it becomes difficult for biologists to use mpiBLAST for accelerating annotation. No web interface is available in the open-source domain for mpiBLAST. We have developed WImpiBLAST, a user-friendly open-source web interface for parallel BLAST searches. It is implemented in Struts 1.3 using a Java backbone and runs atop the open-source Apache Tomcat Server. WImpiBLAST supports script creation and job submission features and also provides a robust job management interface for system administrators. It combines script creation and modification features with job monitoring and management through the Torque resource manager on a Linux-based HPC cluster. Use case information highlights the acceleration of annotation analysis achieved by using WImpiBLAST. Here, we describe the WImpiBLAST web interface features and architecture, explain design

Review of research on advanced computational science in FY2015

International Nuclear Information System (INIS)

2017-01-01

Research on advanced computational science for nuclear applications, based on 'Plan to Achieve Medium- to Long-term Objectives of the Japan Atomic Energy Agency (Medium- to Long-term Plan)', has been performed at Center for Computational Science and e-Systems (CCSE), Japan Atomic Energy Agency. CCSE established the committee consisting of outside experts and authorities which does research evaluation and advices for the assistance of the research and development. This report summarizes the followings. (1) Results of the R and D performed at CCSE in FY 2015 (April 1st, 2015 - March 31st, 2016), (2) Results of the evaluation on the R and D by the committee in FY 2015 (April 1st, 2015 - March 31st, 2016). (author)

Design of a high-performance rotary stratified-charge research aircraft engine

Science.gov (United States)

Jones, C.; Mount, R. E.

1984-01-01

The power section for an advanced rotary stratified-charge general aviation engine has been designed under contract to NASA. The single-rotor research engine of 40 cubic-inches displacement (RCI-40), now being procured for test initiation this summer, is targeted for 320 T.O. horse-power in a two-rotor production engine. The research engine is designed for operating on jet-fuel, gasoline or diesel fuel and will be used to explore applicable advanced technologies and to optimize high output performance variables. Design of major components of the engine is described in this paper.

Harnessing the Department of Energy’s High-Performance Computing Expertise to Strengthen the U.S. Chemical Enterprise

Energy Technology Data Exchange (ETDEWEB)

Dixon, David A.; Dupuis, Michel; Garrett, Bruce C.; Neaton, Jeffrey B.; Plata, Charity; Tarr, Matthew A.; Tomb, Jean-Francois; Golab, Joseph T.

2012-01-17

High-performance computing (HPC) is one area where the DOE has developed extensive expertise and capability. However, this expertise currently is not properly shared with or used by the private sector to speed product development, enable industry to move rapidly into new areas, and improve product quality. Such use would lead to substantial competitive advantages in global markets and yield important economic returns for the United States. To stimulate the dissemination of DOE's HPC expertise, the Council for Chemical Research (CCR) and the DOE jointly held a workshop on this topic. Four important energy topic areas were chosen as the focus of the meeting: Biomass/Bioenergy, Catalytic Materials, Energy Storage, and Photovoltaics. Academic, industrial, and government experts in these topic areas participated in the workshop to identify industry needs, evaluate the current state of expertise, offer proposed actions and strategies, and forecast the expected benefits of implementing those strategies.

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

Science.gov (United States)

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

2000-01-01

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

A parametric study on characteristics for nuclear design of high-performance research reactor

International Nuclear Information System (INIS)

Joe, D. G.; Lee, C. S.; Lee, B. C.; Seo, C. G.; Chae, H. T.; Park, C.

2003-01-01

A conceptual design of advanced research reactor with high neutron performance has been performed at KAERI based on design and operation experience obtained from HANARO. In this study, nuclear characteristics of design parameters such as various types of fuel assemblies, structural materials of core and fuel assembly, and the number of absorber rods were analyzed. Among rod, plate and tube type fuel assemblies considered, tube type assembly seems to be preferable as a high performance research reactor fuel because of high thermal margin and neutron flux in reflector. Aluminium block as a structural material of core was shown to be superior to flow tube due to higher reactivity and thermal flux in reflector. The stiffener to fix plates in th fuel assembly had the no impact on fast flux in central trap. The reduction of thermal flux in reflector caused by the stiffener was about 7%. If the control absorber rods of 4 mm thickness were chosen, it would be possible to operate the reactor with fresh fuel assemblies from the initial core

High-order hydrodynamic algorithms for exascale computing

Energy Technology Data Exchange (ETDEWEB)

Morgan, Nathaniel Ray [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-02-05

Hydrodynamic algorithms are at the core of many laboratory missions ranging from simulating ICF implosions to climate modeling. The hydrodynamic algorithms commonly employed at the laboratory and in industry (1) typically lack requisite accuracy for complex multi- material vortical flows and (2) are not well suited for exascale computing due to poor data locality and poor FLOP/memory ratios. Exascale computing requires advances in both computer science and numerical algorithms. We propose to research the second requirement and create a new high-order hydrodynamic algorithm that has superior accuracy, excellent data locality, and excellent FLOP/memory ratios. This proposal will impact a broad range of research areas including numerical theory, discrete mathematics, vorticity evolution, gas dynamics, interface instability evolution, turbulent flows, fluid dynamics and shock driven flows. If successful, the proposed research has the potential to radically transform simulation capabilities and help position the laboratory for computing at the exascale.