Getting up to Speed: The Future of Supercomputing

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Getting up to Speed: The Future of Supercomputing. Bill Dally Frontiers of Extreme Computing October 25, 2005. Study Process. Sponsored by DOE Office of Science and DOE Advanced Simulation and Computing March 2003 launch meeting Data gathering 5 standard committee meetings
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Getting up to Speed:The Future of SupercomputingBill DallyFrontiers of Extreme ComputingOctober 25, 2005Study Process
  • Sponsored by DOE Office of Science and DOE Advanced Simulation and Computing
  • March 2003 launch meeting
  • Data gathering
  • 5 standard committee meetings
  • Applications Workshop (20+ computational scientists)
  • DOE weapons labs site visits (LLNL, SNL, LANL)
  • DOE science labs site visits (NERSC, Argonne/Oak Ridge)
  • NSA supercomputer center site visit
  • Town Hall (SC2003)
  • Japan forum (25+ supercomputing experts)
  • Japan site visits (ES, U. of Tokyo, JAXA, MEXT, auto manufacturer)
  • Issuance of Interim report (July 2003)
  • Blind peer-review process (17 reviewers); overseen by NRC-selected Monitor and Coordinator
  • Dissemination (DOE, congressional staff, OSTP, SC2004)
  • Study Committee
  • SUSAN L. GRAHAM, University of California, Berkeley, Co-chair
  • MARC SNIR, University of Illinois at Urbana-Champaign, Co-chair
  • WILLIAM J. DALLY, Stanford University
  • JAMES DEMMEL, University of California, Berkeley
  • JACK J. DONGARRA, University of Tennessee, Knoxville
  • KENNETH S. FLAMM, University of Texas at Austin
  • MARY JANE IRWIN, Pennsylvania State University
  • CHARLES KOELBEL, Rice University
  • BUTLER W. LAMPSON, Microsoft Corporation
  • ROBERT LUCAS, University of Southern California, ISI
  • PAUL C. MESSINA, Argonne National Laboratory
  • JEFFREY PERLOFF, Department of Agricultural and Resource Economics, University of California, Berkeley
  • WILLIAM H. PRESS, Los Alamos National Laboratory
  • ALBERT J. SEMTNER, Oceanography Department, Naval Postgraduate School
  • SCOTT STERN, Kellogg School of Management, Northwestern University
  • SHANKAR SUBRAMANIAM, Departments of Bioengineering, Chemistry and Biochemistry, University of California, San Diego
  • LAWRENCE C. TARBELL, JR., Technology Futures Office, Eagle Alliance
  • STEVEN J. WALLACH, Chiaro Networks
  • CSTB: CYNTHIA A. PATTERSON (Study Director), Phil Hilliard, Margaret Huynh
  • Focus of Study
  • Supercomputing – the development and use of the fastest and most powerful computing systems (capability computing).
  • Extends to high-performance computing
  • Does not address grid, networking, storage, special-purpose systems
  • U.S. leadership and government policies.
  • Market forces.
  • Supercomputing Matters
  • Essential for scientific discovery
  • Essential for national security
  • Essential to address broad societal challenges
  • Important contributor to economy and competitiveness through use in engineering and manufacturing
  • Important source of technological advances in IT
  • Challenging research topic per se
  • Supercomputing mattered in the past - Supercomputing will matter in the future
  • Supercomputing is Government Business
  • In 2003 the public sector made > 50% of HPC purchases and > 80% of capability systems purchases (IDC).
  • Supercomputing is mostly used to produce “public goods” (science, security…).
  • Supercomputing technology has historically been developed with public funding.
  • Spillover to commercial/engineering
  • The State of Supercomputing in the U.S. is Good
  • As of June 2004 51% of TOP500 systems were installed in the U.S. and 91% of the TOP500 systems were made in the U.S.
  • In 2003 U.S. vendors had 98% market share in capability systems and 88% in HPC (IDC).
  • Supercomputing is used effectively.
  • Science, ASC, …
  • HPC is broadly available in academia and industry (clusters).
  • Companies primarily making custom supercomputers (e.g., Cray, ISVs) have a hard time surviving.Supercomputing is a diminishing fraction of total computer marketSupercomputing market is unstableDelayed acquisitions can jeopardize company Private share is decreasingCapability private sectorCapability public sectorFraction public$1,200M90.0%80.0%$1,000M70.0%$800M60.0%50.0%$600M40.0%$400M30.0%20.0%$200M10.0%$00.0%199819992000200120022003The State of Supercomputing is BadSupercomputing is a Fragile Ecosystem
  • Small, unstable market, totally dependent on government purchases
  • Weakened by wavering policies and investments (people leave, companies disappear)
  • Recovery is expensive and takes a long time
  • Current State is Largely Due to Success of Commodity Based Supercomputing
  • Supercomputing performance growth in the last decade was almost entirely due to growth in uniprocessor performance (Moore’s law). No progress in unique supercomputing technologies was needed and little occurred.
  • Increase in parallelism has been modest – top commodity/hybrid system had 3,689 nodes in 6/94 and 4,096 nodes in 6/04.
  • As of June 2004, 60% of TOP500 systems are clusters using commodity processors and switches; 95% of the systems use commodity processors.
  • Good: Commodity clusters have democratized and broadened HPC.
  • Bad: Commodity clusters have narrowed the market for non commodity systems. Lack of investment has reduced their viability.
  • Commodity Systems Satisfy Most HPC Needs
  • Good parallel performance can be achieved by clusters of commodity processors connected by commodity switches and switch interfaces, e.g., ASC Q.
  • For problems with good locality (e.g., bioinformatics) such systems provide better time-to-solution than customized systems at any cost level.
  • But Customization Needed to Achieve Certain Critical Goals
  • Higher bandwidth and lower overhead for global communication can be achieved by hybrid systems (custom switch and custom switch interfaces, e.g., Red Storm).
  • For problems with heavy global communication requirements, or when scaling to large node numbers is needed (e.g., climate) such systems provide better time-to-solution at a given cost, or may be only way to meet deadlines.
  • Customization is Becoming Essential
  • Higher bandwidth to local memory and better latency hiding can be achieved by custom systems (systems with custom processors, e.g., Cray X1).
  • For problems with little locality (e.g., GUPS), such systems provide better time-to-solution at given cost or may be the only way to meet deadlines.
  • It will be harder in the future to “ride on the coattails” of Moore’s Law.
  • Memory latency increases relative to processor speed (the memory wall): by 2020 about 800 loads and 90,000 floating-point operations would be executed while waiting for one local memory access to complete.
  • Global communication latency increases and bandwidth decreases relative to processor speed: by 2020 a global bandwidth of about 0.001 word/flops and global latency equivalent to about 0.7Mflops.
  • Improvement in single processor performance is slowing down; future performance improvement in commodity processors will come from increasing on-chip parallelism.
  • Mean Time to Failure is growing shorter as systems grow and devices shrink.
  • Software Productivity is Low
  • Need high-level notations that capture parallelism and locality.
  • Application development environment and execution environment in HPC are less advanced and less robust than for general computing.
  • Will need increasing levels of parallelism in future supercomputing.
  • Custom/hybrid systems can support a simpler programming model.
  • But that potential is largely unrealized
  • What Will We Need?
  • Fundamentally new architectures before 2010 for supercomputing and before 2020 for general computing
  • New algorithms, new languages, new tools, and new systems for higher degrees of parallelism
  • A stable supply of trained engineers and scientists
  • Continuity through institutions and rules that encourage the transfer of knowledge and experience into the future
  • Technological diversity in hardware and software to enhance future technological options
  • We Start at a Disadvantage
  • The research pipeline has emptied.
  • NSF grants decreased 75%, published papers decreased 50%, no funding for significant demonstration systems
  • The human pipeline is dry.
  • Averages: 36 PhDs/year in computational sciences (800 in CS); 3 hired by national labs
  • Less focus on supercomputing among other CS/CE disciplines
  • Planning and coordination are lacking.
  • The Time to Act is Now
  • Fundamental changes take decades to mature.
  • Recall vectors, MPPs …
  • Current strengths are being lost.
  • People, companies, corporate memory
  • What Lessons Should we Learn from the Japanese Earth Simulator?
  • ES demonstrates the advantages of custom supercomputers.
  • ES shows the importance of perseverance.
  • ES does not show that Japan has overtaken the U.S.
  • U.S. had the technology to build a similar system with a similar investment in the same time frame
  • Most of the software technology used on the ES originates from the U.S.
  • ES is not a security risk for the U.S.
  • ES shows how precarious the worldwide state of custom supercomputing is
  • U.S. should invest in supercomputing to satisfy its own needs, not to beat Japan.
  • Overall Recommendation To meet the current and future needs of the United States, the government agencies that depend on supercomputing, together with the U.S. Congress, need to take primary responsibility for accelerating advances in supercomputing and ensuring that there are multiple strong domestic suppliers of both hardware and software. Recommendation 1To get the maximum leverage from the national effort, the government agencies that are the major users of supercomputing should be jointly responsible for the strength and continued evolution of the supercomputing infrastructure in the United States, from basic research to suppliers and deployed platforms. The Congress should provide adequate and sustained funding.
  • Long-term (5-10 years) integrated HEC plan
  • Budget requests matched to plan
  • Loose coordination of research funding; tight coordination of industrial R&D
  • Joint planning and coordination of acquisitions (reduce procurement overheads, reduce variability)
  • Recommendation 2The government agencies that are the primary users of supercomputing should ensure domestic leadership in those technologies that are essential to meet national needs.
  • Unique technologies are needed (custom processors, interconnects, scalable software); these will not come from broad market
  • Need U.S. suppliers because may want to restrict export
  • Need U.S. suppliers because no other country is certain to do it
  • Leadership both helps mainstream computing and draws from it
  • Recommendation 3To satisfy its need for unique supercomputing technologies such as high-bandwidth systems, the government needs to ensure the viability of multiple domestic suppliers.
  • Viability achieved by stable, long-term government investments at adequate levels
  • Either subsidize R&D or support from stable, long-term procurement contracts (UK model)
  • Custom processors are a key technology that will not be provided by the broad market
  • Other technologies also important
  • Recommendation 4The creation and long-term maintenance of the software that is key to supercomputing requires the support of those agencies that are responsible for supercomputing R&D. That software includes operating systems, libraries, compilers, software development and data analysis tools, application codes, and databases.
  • Need larger and more targeted coordinated investments
  • Multiple models: vertical vendor, horizontal vendor, not for profit organization, open source model…
  • Need stability and continuity (corporate memory)
  • Build only what cannot be bought
  • Recommendation 5The government agencies responsible for supercomputing should underwrite a community effort to develop and maintain a roadmap that identifies key obstacles and synergies in all of supercomputing.
  • Roadmap should inform R&D investments
  • Wide participation from researchers, developers and users
  • Driven top-down (requirements) and bottom-up (technologies)
  • Must be quantitative and measurable
  • Must reflect interdependence of technologies
  • Informs, but does not fully determine research agenda
  • Recommendation 6Government agencies responsible for supercomputing should increase their levels of stable, robust, sustained multiagency investment in basic research. More research is needed in all the key technologies required for the design and use of supercomputers (architecture, software, algorithms, and applications).
  • Mix of small and large projects, including demonstration systems
  • Emphasis on university projects - education and free flow of information
  • Estimated investment needed for core technologies is $140M per year (more needed for applications)
  • Recommendation 7Supercomputing research is an international activity; barriers to international collaboration should be minimized.
  • Barriers reduce broad benefit of supercomputing to science
  • Early-stage sharing of ideas compensates for small size of community
  • Collaborators should have access to domestic supercomputing systems
  • Technology advances flow to and from broader IT industry; fast development cycles and fast technology evolution require close interaction
  • No single supercomputing technology presents major risk; US strategic advantage is in its broad capability
  • Export restrictions have hurt U.S. manufacturers; some (e.g., on commodity clusters) lack any rationale
  • Recommendation 8The U. S. government should ensure that researchers with the most demanding computational requirements have access to the most powerful supercomputing systems
  • Important for advancement of science
  • Needed to educate next generation and create the needed software infrastructure
  • Sufficient stable funding must be provided
  • Infrastructure funding should be separated from funding for IT research
  • Capability systems should be used for jobs that need that capability
  • Questions?
  • The report is available online a
  • http://www.nap.edu/catalog/11148.htmland athttp://www.sc.doe.gov/ascr/FOSCfinalreport.pdf
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