DOCSLIB.ORG

2020 ALCF Science Report

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
2020 ALCF Science Report ARGONNE LEADERSHIP 2020 COMPUTING FACILITY Science On the cover: A snapshot of a visualization of the SARS-CoV-2 viral envelope comprising 305 million atoms. A multi-institutional research team used multiple supercomputing resources, including the ALCF’s Theta system, to optimize codes in preparation for large-scale simulations of the SARS-CoV-2 spike protein that were recognized with the ACM Gordon Bell Special Prize for HPC-Based COVID-19 Research. Image: Rommie Amaro, Lorenzo Casalino, Abigail Dommer, and Zied Gaieb, University of California San Diego 2020 SCIENCE CONTENTS 03 Message from ALCF Leadership 04 Argonne Leadership Computing Facility 10 Advancing Science with HPC 06 About ALCF 12 ALCF Resources Contribute to Fight Against COVID-19 07 ALCF Team 16 Edge Services Propel Data-Driven Science 08 ALCF Computing Resources 18 Preparing for Science in the Exascale Era 26 Science 28 Accessing ALCF GPCNeT: Designing a Benchmark 43 Materials Science 51 Physics Resources for Science Suite for Inducing and Measuring Constructing and Navigating Hadronic Light-by-Light Scattering Contention in HPC Networks Polymorphic Landscapes of and Vacuum Polarization Sudheer Chunduri Molecular Crystals Contributions to the Muon 30 2020 Science Highlights Parallel Relational Algebra for Alexandre Tkatchenko Anomalous Magnetic Moment Thomas Blum 31 Biological Sciences Logical Inferencing at Scale Data-Driven Materials Sidharth Kumar Scalable Reinforcement-Learning- Discovery for Optoelectronic The Last Journey Based Neural Architecture Search Applications Katrin Heitmann Jacqueline Cole for Cancer Research 38 Earth Science Lattice QCD Prasanna Balaprakash Energy Exascale Earth System Model Electronic Stopping Simulation of Paul Mackenzie X-ray Microscopy of Extended 3D Mark Taylor Complex Systems Yosuke Kanai PLASM-IN-SILICO: HPC Modeling Objects: Scaling Towards the Future of High-Intensity Laser-Solid Chris Jacobsen 39 Engineering Imaging and Controlling Elemental Interaction DNS Reference Data for Turbulence Contrast of Nanocluster in Intense Jean-Luc Vay 33 Chemistry Model Development on the X-ray Pulses Phay Ho Studying Astrophysical Particle Dynamic Nanocluster Catalysis Bachalo-Johnson ATB Acceleration in HED Plasmas Anastassia Alexandrova Koen Hillewaert Materials and Interfaces for Organic Frederico Fiuza Laminar-Turbulent Transition in and Hybrid Photovoltaics Towards Exascale Internal Noa Marom Towards a Definitive Model of Combustion Engine Simulation with Swept-Wing Boundary Layers Core-Collapse Supernova Explosions In-Situ Analysis Lian Duan Metascalable Layered Materials Adam Burrows Muhsin Ameen Shock-Induced Multi-Material Mixing Genome Sanjiva Lele Aiichiro Nakano 60 ALCF Projects 35 Computer Science Towards Ultimate Rayleigh-Bénard Modeling the Response of Fusion Balsam: Near Real-Time Convection Plasma Facing Components Experimental Data Analysis on Janet Scheel Brian Wirth Supercomputers Predictive Modeling and Machine Michael Salim Learning for Functional Nanoporous Materials J. Ilja Siepmann MICHAEL E. PAPKA ALCF Director JINI RAMPRAKASH ALCF Deputy Director KATHERINE RILEY ALCF Director of Science KALYAN KUMARAN ALCF Director of Technology MARK FAHEY ALCF Director of Operations SUSAN COGHLAN ALCF-X Project Director 0 2 ALCF.ANL.GOV MESSAGE FROM ALCF LEADERSHIP In many ways, 2020 was an extraordinary moment There were also many other achievements, unrelated to for science. Scientists worldwide rapidly responded to the COVID-19—which you will read about in the pages that follow. COVID-19 crisis, aided greatly by today’s technology and The Last Journey, a six-month, massive simulation of the the pace of information sharing, all the while continuing to cosmos—one of the five largest cosmological simulations make progress in many fields beyond infectious diseases. ever—provided data that will form the basis for sky maps Advanced computational user facilities, such as the used by numerous surveys. This project both capped the ALCF, and major experimental research facilities, such as service life of one ALCF supercomputer and prepared Argonne’s Advanced Photon Source (APS), play a vital role the science team to run even more extensive cosmological in the nation’s scientific response to crises while continuing simulations on future machines, like the ALCF’s Aurora to serve as the foundation of scientific infrastructure. exascale system. Researchers also tapped Theta for studies ranging from modeling supernova explosions to creating When APS users needed on-demand analysis of experimental automated databases for materials discovery. data on the crystal structure of COVID-19 proteins, ALCF staff put a computational pipeline in place to do that. To apportion We continued to prepare for Aurora. Our collaborative work valuable computing cycles for COVID-19 research, the ALCF through the Early Science Program (ESP) and DOE’s dedicated 10 percent of Theta to focus on supporting COVID-19 Exascale Computing Project and available testing hardware efforts. The ALCF then expanded Theta with graphics in the Joint Laboratory for System Evaluation has helped processing units (GPUs) to bring additional computational numerous teams advance code development efforts for the power to addressing the pandemic. (Theta’s expansion, upcoming system. We also hosted several workshops, called ThetaGPU, was made possible with support from the webinars, and hackathons to provide details and guidance Coronavirus Aid, Relief, and Economic Security (CARES) on using various aspects of the Aurora hardware and Act). The ALCF also joined a national effort as part of the software environment. COVID-19 High Performance Computing (HPC) Consortium The facility itself has been undergoing a major upgrade to to coordinate a unified computational response. make way for Aurora, which is transforming not only All the while, the ALCF, the APS, as well as many other facilities the machine room, but also building out new meeting and across the globe, have continued to produce quality and training spaces at a steady clip. Yet, even amid all the impactful science. ALCF users have always carried out their construction and regular support that ALCF staff provide our computational studies via remote access to our facility, users every day, the facility was able to open up the so their scientific progress kept moving forward despite the connections that allowed the COVID work. pandemic’s impact on our day-to-day lives. We are grateful to our staff’s extra efforts in 2020 to keep the Some of the most noteworthy research carried out at the science flowing and to DOE’s Office of Science and ALCF this year were projects that aimed to shed light on Argonne leadership for their ongoing support of our efforts the coronavirus, including CityCOVID, an agent-based to build out the advanced systems that will drive the next epidemiological model used to support decision makers generation of discoveries. Mostly, we are grateful for your in COVID-19 crisis response and planning, and a finalist interest in our activities, for it is the scientific work done at for the ACM Gordon Bell Special Prize for High Performance user facilities like ours that will have immense impact Computing-Based COVID-19 Research; and the on people in our nation and around the globe for decades multi-institutional collaboration that studied the complex to come. dynamics of the spike protein, a key protein in the SARS-CoV-2 virus, an effort that won the Special Prize. ALCF 2020 SCIENCE REPORT 03 ARGONNE LEADERSHIP COMPUTING FACILITY The ALCF enables breakthroughs in science and engineering by providing supercomputing resources and expertise to the research community. 0 4 ALCF.ANL.GOV In 2020, the ALCF hosted multiple training events, including a hands-on workshop in February, to help researchers advance code development efforts for its upcoming exascale system, Aurora. ALCF 2020 SCIENCE REPORT 05 ALCF About ALCF The ALCF’s Theta system is designed to support research at the nexus of simulation, data analytics, and artificial intelligence. The Argonne Leadership Computing Facility, a U.S. Supported by the DOE’s Advanced Scientific Computing Department of Energy (DOE) Office of Science User Facility Research (ASCR) program, the ALCF and its partner located at Argonne National Laboratory, enables organization, the Oak Ridge Leadership Computing Facility, breakthroughs in science and engineering by providing operate leadership-class supercomputers that are orders supercomputing resources and expertise to the research of magnitude more powerful than the systems typically used community. for open scientific research. ALCF computing resources—available to researchers from academia, industry, and government agencies—support large-scale computing projects aimed at solving some of the world’s most complex and challenging scientific problems. Through awards of supercomputing time and support services, the ALCF enables its users to accelerate the pace of discovery and innovation across disciplines. 0 6 ALCF.ANL.GOV ALCF Team The ALCF’s talented and diverse staff make the facility one of the world’s premier centers for scientific computing. Science Technology Computational scientists with multidisciplinary domain The ALCF team plays a key role in designing and validating expertise work directly with ALCF users to maximize and the facility’s next-generation supercomputers. By accelerate their research efforts. In addition, the collaborating with compute vendors and the performance ALCF team applies broad expertise in data science,
Load more

Recommended publications
  • Biology at the Exascale
    Biology at the Exascale Advances in computational hardware and algorithms that have transformed areas of physics and engineering have recently brought similar benefits to biology and biomedical research. Contributors: Laura Wolf and Dr. Gail W. Pieper, Argonne National Laboratory Biological sciences are undergoing a revolution. High‐performance computing has accelerated the transition from hypothesis‐driven to design‐driven research at all scales, and computational simulation of biological systems is now driving the direction of biological experimentation and the generation of insights. As recently as ten years ago, success in predicting how proteins assume their intricate three‐dimensional forms was considered highly unlikely if there was no related protein of known structure. For those proteins whose sequence resembles a protein of known structure, the three‐dimensional structure of the known protein can be used as a “template” to deduce the unknown protein structure. At the time, about 60 percent of protein sequences arising from the genome sequencing projects had no homologs of known structure. In 2001, Rosetta, a computational technique developed by Dr. David Baker and colleagues at the Howard Hughes Medical Institute, successfully predicted the three‐dimensional structure of a folded protein from its linear sequence of amino acids. (Baker now develops tools to enable researchers to test new protein scaffolds, examine additional structural hypothesis regarding determinants of binding, and ultimately design proteins that tightly bind endogenous cellular proteins.) Two years later, a thirteen‐year project to sequence the human genome was declared a success, making available to scientists worldwide the billions of letters of DNA to conduct postgenomic research, including annotating the human genome.
    [Show full text]
  • ECP Software Technology Capability Assessment Report
    ECP-RPT-ST-0001-2018 ECP Software Technology Capability Assessment Report Michael A. Heroux, Director ECP ST Jonathan Carter, Deputy Director ECP ST Rajeev Thakur, Programming Models & Runtimes Lead Jeffrey Vetter, Development Tools Lead Lois Curfman McInnes, Mathematical Libraries Lead James Ahrens, Data & Visualization Lead J. Robert Neely, Software Ecosystem & Delivery Lead July 1, 2018 DOCUMENT AVAILABILITY Reports produced after January 1, 1996, are generally available free via US Department of Energy (DOE) SciTech Connect. Website http://www.osti.gov/scitech/ Reports produced before January 1, 1996, may be purchased by members of the public from the following source: National Technical Information Service 5285 Port Royal Road Springfield, VA 22161 Telephone 703-605-6000 (1-800-553-6847) TDD 703-487-4639 Fax 703-605-6900 E-mail [email protected] Website http://www.ntis.gov/help/ordermethods.aspx Reports are available to DOE employees, DOE contractors, Energy Technology Data Exchange representatives, and International Nuclear Information System representatives from the following source: Office of Scientific and Technical Information PO Box 62 Oak Ridge, TN 37831 Telephone 865-576-8401 Fax 865-576-5728 E-mail [email protected] Website http://www.osti.gov/contact.html This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights.
    [Show full text]
  • Experimental and Analytical Study of Xeon Phi Reliability
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Lume 5.8 Experimental and Analytical Study of Xeon Phi Reliability Daniel Oliveira Laércio Pilla Nathan DeBardeleben Institute of Informatics, UFRGS Department of Informatics and Los Alamos National Laboratory Porto Alegre, RS, Brazil Statistics, UFSC Los Alamos, NM, US Florianópolis, SC, Brazil Sean Blanchard Heather Quinn Israel Koren Los Alamos National Laboratory Los Alamos National Laboratory University of Massachusetts, UMass Los Alamos, NM, US Los Alamos, NM, US Amherst, MA, US Philippe Navaux Paolo Rech Institute of Informatics, UFRGS Institute of Informatics, UFRGS Porto Alegre, RS, Brazil Porto Alegre, RS, Brazil ABSTRACT 1 INTRODUCTION We present an in-depth analysis of transient faults effects on HPC Accelerators are extensively used to expedite calculations in large applications in Intel Xeon Phi processors based on radiation experi- HPC centers. Tianhe-2, Cori, Trinity, and Oakforest-PACS use Intel ments and high-level fault injection. Besides measuring the realistic Xeon Phi and many other top supercomputers use other forms of error rates of Xeon Phi, we quantify Silent Data Corruption (SDCs) accelerators [17]. The main reasons to use accelerators are their by correlating the distribution of corrupted elements in the out- high computational capacity, low cost, reduced per-task energy put to the application’s characteristics. We evaluate the benefits consumption, and flexible development platforms. Unfortunately, of imprecise computing for reducing the programs’ error rate. For accelerators are also extremely likely to experience transient errors example, for HotSpot a 0.5% tolerance in the output value reduces as they are built with cutting-edge technology, have very high the error rate by 85%.
    [Show full text]
  • Technical Challenges of Exascale Computing
    Technical Challenges of Exascale Computing Contact: Dan McMorrow — [email protected] April 2013 JSR-12-310 Approved for public release; distribution unlimited. JASON The MITRE Corporation 7515 Colshire Drive McLean, Virginia 22102-7508 (703) 983-6997 Contents 1 ABSTRACT 1 2 EXECUTIVE SUMMARY 3 2.1 Overview . 4 2.2 Findings . 7 2.3 Recommendations . 9 3 DOE/NNSA COMPUTING CHALLENGES 11 3.1 Study Charge from DOE/NNSA . 11 3.2 Projected Configuration of an Exascale Computer . 13 3.3 Overview of DOE Exascale Computing Initiative . 15 3.4 The 2008 DARPA Study . 17 3.5 Overview of the Report . 19 4 HARDWARE CHALLENGES FOR EXASCALE COMPUTING 21 4.1 Evolution of Moore’s Law . 21 4.2 Evolution of Memory Size and Memory Bandwidth . 25 4.3 Memory Access Patterns of DOE/NNSA Applications . 32 4.4 The Roof-Line Model . 39 4.5 Energy Costs of Computation . 46 4.6 Memory Bandwidth and Energy . 48 4.7 Some Point Designs for Exascale Computers . 50 4.8 Resilience . 52 4.9 Storage . 57 4.9.1 Density . 58 4.9.2 Power . 60 4.9.3 Storage system reliability . 67 4.10 Summary and Conclusions . 71 5 REQUIREMENTS FOR DOE/NNSA APPLICATIONS 73 5.1 Climate Simulation . 73 5.2 Combustion . 78 5.3 NNSA Applications . 89 5.4 Summary and Conclusion . 90 iii 6 RESEARCH DIRECTIONS 93 6.1 Breaking the Memory Wall . 93 6.2 Role of Photonics for Exascale Computing . 96 6.3 Computation and Communication Patterns of DOE/NNSA Appli- cations . 99 6.4 Optimizing Hardware for Computational Patterns .
    [Show full text]
  • The US DOE Exascale Computing Project (ECP) Perspective for the HEP Community
    The US DOE Exascale Computing Project (ECP) Perspective for the HEP Community Douglas B. Kothe (ORNL), ECP Director Lori Diachin (LLNL), ECP Deputy Director Erik Draeger (LLNL), ECP Deputy Director of Application Development Tom Evans (ORNL), ECP Energy Applications Lead Blueprint Workshop on A Coordinated Ecosystem for HL-LHC Computing R&D Washington, DC October 23, 2019 DOE Exascale Program: The Exascale Computing Initiative (ECI) Three Major Components of the ECI ECI US DOE Office of Science (SC) and National partners Nuclear Security Administration (NNSA) Exascale Selected program Computing office application Project development ECI Accelerate R&D, acquisition, and deployment to (BER, BES, (ECP) deliver exascale computing capability to DOE NNSA) mission national labs by the early- to mid-2020s Exascale system ECI Delivery of an enduring and capable exascale procurement projects & computing capability for use by a wide range facilities focus of applications of importance to DOE and the US ALCF-3 (Aurora) OLCF-5 (Frontier) ASC ATS-4 (El Capitan) 2 ECP Mission and Vision Enable US revolutions in technology development; scientific discovery; healthcare; energy, economic, and national security ECP ECP mission vision Develop exascale-ready applications Deliver exascale simulation and and solutions that address currently data science innovations and intractable problems of strategic solutions to national problems importance and national interest. that enhance US economic competitiveness, change our quality Create and deploy an expanded and of life, and strengthen our national vertically integrated software stack on security. DOE HPC exascale and pre-exascale systems, defining the enduring US exascale ecosystem. Deliver US HPC vendor technology advances and deploy ECP products to DOE HPC pre-exascale and exascale systems.
    [Show full text]
  • Advanced Scientific Computing Research
    Advanced Scientific Computing Research Overview The Advanced Scientific Computing Research (ASCR) program’s mission is to advance applied mathematics and computer science; deliver the most sophisticated computational scientific applications in partnership with disciplinary science; advance computing and networking capabilities; and develop future generations of computing hardware and software tools for science and engineering in partnership with the research community, including U.S. industry. ASCR supports state-of- the-art capabilities that enable scientific discovery through computation. The Computer Science and Applied Mathematics activities in ASCR provide the foundation for increasing the capability of the national high performance computing (HPC) ecosystem by focusing on long-term research to develop innovative software, algorithms, methods, tools and workflows that anticipate future hardware challenges and opportunities as well as science application needs. ASCR’s partnerships and coordination with the other Office of Science (SC) programs and with industry are essential to these efforts. At the same time, ASCR partners with disciplinary sciences to deliver some of the most advanced scientific computing applications in areas of strategic importance to SC and the Department of Energy (DOE). ASCR also deploys and operates world-class, open access high performance computing facilities and a high performance network infrastructure for scientific research. For over half a century, the U.S. has maintained world-leading computing capabilities
    [Show full text]
  • Developing Exascale Computing at JSC
    Developing Exascale Computing at JSC E. Suarez, W. Frings, S. Achilles, N. Attig, J. de Amicis, E. Di Napoli, Th. Eickermann, E. B. Gregory, B. Hagemeier, A. Herten, J. Jitsev, D. Krause, J. H. Meinke, K. Michielsen, B. Mohr, D. Pleiter, A. Strube, Th. Lippert published in NIC Symposium 2020 M. Muller,¨ K. Binder, A. Trautmann (Editors) Forschungszentrum Julich¨ GmbH, John von Neumann Institute for Computing (NIC), Schriften des Forschungszentrums Julich,¨ NIC Series, Vol. 50, ISBN 978-3-95806-443-0, pp. 1. http://hdl.handle.net/2128/24435 c 2020 by Forschungszentrum Julich¨ Permission to make digital or hard copies of portions of this work for personal or classroom use is granted provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise requires prior specific permission by the publisher mentioned above. Developing Exascale Computing at JSC Estela Suarez1, Wolfgang Frings1, Sebastian Achilles2, Norbert Attig1, Jacopo de Amicis1, Edoardo Di Napoli1, Thomas Eickermann1, Eric B. Gregory1, Bjorn¨ Hagemeier1, Andreas Herten1, Jenia Jitsev1, Dorian Krause1, Jan H. Meinke1, Kristel Michielsen1, Bernd Mohr1, Dirk Pleiter1, Alexandre Strube1, and Thomas Lippert1 1 Julich¨ Supercomputing Centre (JSC), Institute for Advanced Simulation (IAS), Forschungszentrum Julich,¨ 52425 Julich,¨ Germany E-mail: fe.suarez, w.frings, [email protected] 2 RWTH Aachen University, 52062 Aachen, Germany The first Exaflop-capable systems will be installed in the USA and China beginning in 2020. Europe intends to have its own machines starting in 2023. It is therefore very timely for com- puter centres, software providers, and application developers to prepare for the challenge of operating and efficiently using such Exascale systems.
    [Show full text]
  • High-Performance I/O Programming Models for Exascale Computing
    High-Performance I/O Programming Models for Exascale Computing SERGIO RIVAS-GOMEZ Doctoral Thesis Stockholm, Sweden 2019 KTH Royal Institute of Technology School of Electrical Engineering and Computer Science TRITA-EECS-AVL-2019:77 SE-100 44 Stockholm ISBN 978-91-7873-344-6 SWEDEN Akademisk avhandling som med tillstånd av Kungl Tekniska Högskolan framlägges till offentlig granskning för avläggande av teknologie doktorsexamen i högprestan- daberäkningar fredag den 29 Nov 2019 klockan 10.00 i B1, Brinellvägen 23, Bergs, våningsplan 1, Kungl Tekniska Högskolan, 114 28 Stockholm, Sverige. © Sergio Rivas-Gomez, Nov 2019 Tryck: Universitetsservice US AB iii Abstract The success of the exascale supercomputer is largely dependent on novel breakthroughs that overcome the increasing demands for high-performance I/O on HPC. Scientists are aggressively taking advantage of the available compute power of petascale supercomputers to run larger scale and higher- fidelity simulations. At the same time, data-intensive workloads have recently become dominant as well. Such use-cases inherently pose additional stress into the I/O subsystem, mostly due to the elevated number of I/O transactions. As a consequence, three critical challenges arise that are of paramount importance at exascale. First, while the concurrency of next-generation su- percomputers is expected to increase up to 1000 , the bandwidth and access × latency of the I/O subsystem is projected to remain roughly constant in com- parison. Storage is, therefore, on the verge of becoming a serious bottleneck. Second, despite upcoming supercomputers expected to integrate emerging non-volatile memory technologies to compensate for some of these limitations, existing programming models and interfaces (e.g., MPI-IO) might not provide any clear technical advantage when targeting distributed intra-node storage, let alone byte-addressable persistent memories.
    [Show full text]
  • High Performance Computing for Geospatial Applications: a Prospective View
    Forthcoming in W. Tang and S. Wang (eds.) High-Performance Computing for Geospatial Applications, Springer. High Performance Computing for Geospatial Applications: A Prospective View Marc P. Armstrong The University of Iowa [email protected] Abstract The pace of improvement in the performance of conventional computer hardware has slowed significantly during the past decade, largely as a consequence of reaching the physical limits of manufacturing processes. To offset this slowdown, new approaches to HPC are now undergoing rapid development. This chapter describes current work on the development of cutting-edge exascale computing systems that are intended to be in place in 2021 and then turns to address several other important developments in HPC, some of which are only in the early stage of development. Domain- specific heterogeneous processing approaches use hardware that is tailored to specific problem types. Neuromorphic systems are designed to mimic brain function and are well suited to machine learning. And then there is quantum computing, which is the subject of some controversy despite the enormous funding initiatives that are in place to ensure that systems continue to scale-up from current small demonstration systems. 1.0 Introduction Rapid gains in computing performance were sustained for several decades by several interacting forces, that, taken together, became widely known as Moore’s Law (Moore, 1965). The basic idea is simple: transistor density would double approximately every two years. This increase in density yielded continual improvements in processor performance even though it was long-known that the model could not be sustained indefinitely (Stone and Cocke, 1991). And this has come to pass.
    [Show full text]
  • Technological Forecasting of Supercomputer Development: the March to Exascale Computing
    Portland State University PDXScholar Engineering and Technology Management Faculty Publications and Presentations Engineering and Technology Management 10-2014 Technological Forecasting of Supercomputer Development: The March to Exascale Computing Dong-Joon Lim Portland State University Timothy R. Anderson Portland State University, [email protected] Tom Shott Portland State University, [email protected] Follow this and additional works at: https://pdxscholar.library.pdx.edu/etm_fac Part of the Engineering Commons Let us know how access to this document benefits ou.y Citation Details Lim, Dong-Joon; Anderson, Timothy R.; and Shott, Tom, "Technological Forecasting of Supercomputer Development: The March to Exascale Computing" (2014). Engineering and Technology Management Faculty Publications and Presentations. 46. https://pdxscholar.library.pdx.edu/etm_fac/46 This Post-Print is brought to you for free and open access. It has been accepted for inclusion in Engineering and Technology Management Faculty Publications and Presentations by an authorized administrator of PDXScholar. Please contact us if we can make this document more accessible: [email protected]. Technological forecasting of supercomputer development: The march to Exascale computing Dong-Joon Lim *, Timothy R. Anderson, Tom Shott Dept. of Engineering and Technology Management, Portland State University, USA Abstract- Advances in supercomputers have come at a steady pace over the past 20 years. The next milestone is to build an Exascale computer however this requires not only speed improvement but also significant enhancements for energy efficiency and massive parallelism. This paper examines technological progress of supercomputer development to identify the innovative potential of three leading technology paths toward Exascale development: hybrid system, multicore system and manycore system.
    [Show full text]
  • Exascale Computing Study: Technology Challenges in Achieving Exascale Systems
    ExaScale Computing Study: Technology Challenges in Achieving Exascale Systems Peter Kogge, Editor & Study Lead Keren Bergman Shekhar Borkar Dan Campbell William Carlson William Dally Monty Denneau Paul Franzon William Harrod Kerry Hill Jon Hiller Sherman Karp Stephen Keckler Dean Klein Robert Lucas Mark Richards Al Scarpelli Steven Scott Allan Snavely Thomas Sterling R. Stanley Williams Katherine Yelick September 28, 2008 This work was sponsored by DARPA IPTO in the ExaScale Computing Study with Dr. William Harrod as Program Manager; AFRL contract number FA8650-07-C-7724. This report is published in the interest of scientific and technical information exchange and its publication does not constitute the Government’s approval or disapproval of its ideas or findings NOTICE Using Government drawings, specifications, or other data included in this document for any purpose other than Government procurement does not in any way obligate the U.S. Government. The fact that the Government formulated or supplied the drawings, specifications, or other data does not license the holder or any other person or corporation; or convey any rights or permission to manufacture, use, or sell any patented invention that may relate to them. APPROVED FOR PUBLIC RELEASE, DISTRIBUTION UNLIMITED. This page intentionally left blank. DISCLAIMER The following disclaimer was signed by all members of the Exascale Study Group (listed below): I agree that the material in this document reects the collective views, ideas, opinions and ¯ndings of the study participants only, and not those of any of the universities, corporations, or other institutions with which they are a±liated. Furthermore, the material in this document does not reect the o±cial views, ideas, opinions and/or ¯ndings of DARPA, the Department of Defense, or of the United States government.
    [Show full text]
  • Intel Delivers New Architecture for Discovery with Intel® Xeon Phi™ Coprocessors
    November 12, 2012 Intel Delivers New Architecture for Discovery with Intel® Xeon Phi™ Coprocessors Combination of Intel® Xeon® Processors and Intel® Xeon Phi™ Coprocessors Promises to Drive High Performance Computing Innovation NEWS HIGHLIGHTS ● Intel® Xeon Phi™ coprocessors, when combined with the Intel® Xeon® processor E5 family, will deliver unprecedented parallel performance, increasing the productivity and efficiency of high- performance computing. ● Efficient performance and a familiar programming model foster a thriving development community and extensive industry support from key OEMs, making high-performance computing easier to access for content creators, developers and scientists. ● Optimizing applications with tools such as Intel Cluster Studio XE 2013 helps achieve industry's best performance per watt for high degrees of parallelism on Intel Xeon Phi coprocessors as well asa significant increase in productivity on Intel Xeon processors E5 product family. ● Ninety-one percent of all newly listed systems on the recently announced Top500 list of the world's most powerful supercomputers are powered by Intel processors. Intel Xeon Phi coprocessors are already featured in 7 systems including the most power-efficient supercomputer on the list –"Beacon" delivering 2.44 GFlops/Watt. SALT LAKE CITY, Utah, Nov. 12, 2012 – Marking a new era in high-performance computing, Intel Corporation introduced the Intel® Xeon Phi™ coprocessor, a culmination of years of research and collaboration, to bring unprecedented performance for innovative breakthroughs in manufacturing, life sciences, energy and other areas. The ability to quickly compute, simulate and make more informed decisions has propelled the growth of high performance computing (HPC) and analytics. This has been driven by global business and research priorities to more accurately predict weather patterns, create more efficient energy resources, and develop cures for diseases among many other pressing issues.
    [Show full text]