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Developments in Supercomputing Ron Perrott Queen’s University United Kingdom
Top500 List of Supercomputers    H. Meuer, H. Simon, E. Strohmaier, & J. Dongarra    - Listing of the 500 most powerful   ...
Performance Development                                                                                             59  PF...
November 2011: The TOP10                                                                                    Rmax      % of...
November 2011: The TOP10                                                                                    Rmax      % of...
Geographical regions                         Count         Share %            Rmax                    Rpeak               ...
South America HPC                                                                                Rmax      Rpeak     Power...
Japanese K Computer  New Linpack run with 705,024 cores at 10.51 Pflop/s (88,128 CPUs)   8
China • First Chinese Supercomputer to   use a Chinese Processor     Sunway BlueLight MPP     ShenWei SW1600 processor, 16...
Commodity plus Accelerator Commodity                 Accelerator (GPU)  Intel Xeon                Nvidia C2070 “Fermi”    ...
Future Computer Systems♦ Most likely be a hybrid design     Standard multicore chips and accelerator     (GPUs)♦ Today acc...
Performance Development in      Top500 1E+11 12 1E+10 1 Eflop/s 1E+09100 Pflop/s00000010 Pflop/s000000 1 Pflop/s          ...
Major Changes to Software &Algorithms• Must rethink the design of our  algorithms and software   Another disruptive techno...
Critical Issues at Peta & Exascale forAlgorithm and Software Design• Synchronization-reducing algorithms     Break Fork-Jo...
International Exascale Software Project Attendees from universities,       Steering Committee research institutes, governm...
International Exascale Software Project Objectives To enable the international HPC community to improve, coordinate and le...
What Next?Moving from “What to Build” to “How to Build”  Technology    Defining and developing the roadmap for software   ...
What Next?Moving from “What to Build” to “How to Build”  Organization    Exploring ways for funding agencies to coordinate...
What Next?Moving from “What to Build” to “How to Build”  Execution    Developing a strategic plan for moving forward    Cr...
US TeraGrid An instrument that delivers high-end IT resources/services   a computational facility – over two PFlops   Scie...
TeraGrid Objectives DEEP Science: enabling terascale and petascale science   make science more productive through an integ...
The eXtreme Digital (XD) ProgramXD : third generation TeraGrid program  2002-2005: Distributed/Extended Terascale Facility...
11 Resource Providers, One Facility                                                                    UW           Grid I...
eXtreme Digital Resources  High-Performance Computing and Storage Services  High-Performance Remote Visualization and Data...
XSEDE : Governance     Leadership       led by NCSA, NICS, PSC, TACC and SDSC: centers with deep       experience       pa...
XSEDE: Extending Impact     Coordinated national program with greater scope and scale       increased diversity of topics,...
Summary HPC Increasingly indispensably to scientific progress and economy competitiveness Industrial competiveness ->time ...
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  1. 1. Developments in Supercomputing Ron Perrott Queen’s University United Kingdom
  2. 2. Top500 List of Supercomputers H. Meuer, H. Simon, E. Strohmaier, & J. Dongarra - Listing of the 500 most powerful Computers in the World - Yardstick: Rmax from LINPACK MPP Ax=b, dense problem TPP performance Rate - Updated twice a year Size SC‘xy in the States in November Meeting in Germany in June2 - All data available from www.top500.org
  3. 3. Performance Development 59  PFlop/s 100 Pflop/s100000000 10 Pflop/s 8.2 PFlop/s 10000000 1 Pflop/s 1000000 100 Tflop/s SUM 100000 41 TFlop/s 10 Tflop/s 10000 N=1 1 Tflop/s 1.17 TFlop/s 1000 6-8 years 100 Gflop/s 100 N=500 59.7 GFlop/s Laptop (12 Gflop/s) 10 Gflop/s 10 1 Gflop/s iPad2 & iPhone 4s (1.02 Gflop/s) 1 400 MFlop/s 100 Mflop/s 0.1 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011
  4. 4. November 2011: The TOP10 Rmax % of Power MFlopsRank Site Computer Country Cores [Pflops] Peak [MW] /Watt RIKEN Advanced Inst K computer Fujitsu SPARC64 1 Japan 705,024 10.5 93 12.7 826 for Comp Sci VIIIfx + custom Nat. SuperComputer Tianhe-1A, NUDT 2 China 186,368 2.57 55 4.04 636 Center in Tianjin Intel + Nvidia GPU + custom DOE / OS Jaguar, Cray 3 USA 224,162 1.76 75 7.0 251 Oak Ridge Nat Lab AMD + custom Nat. Supercomputer Nebulea, Dawning 4 China 120,640 1.27 43 2.58 493 Center in Shenzhen Intel + Nvidia GPU + IB GSIC Center, Tokyo Tusbame 2.0, HP 5 Japan 73,278 1.19 52 1.40 850 Institute of Technology Intel + Nvidia GPU + IB DOE / NNSA Cielo, Cray 6 USA 142,272 1.11 81 3.98 279 LANL & SNL AMD + custom NASA Ames Research Plelades SGI Altix ICE 7 USA 111,104 1.09 83 4.10 265 Center/NAS 8200EX/8400EX + IB DOE / OS Hopper, Cray 8 Lawrence Berkeley Nat USA 153,408 1.054 82 2.91 362 AMD + custom Lab Commissariat a Tera-10, Bull 9 lEnergie Atomique France 138,368 1.050 84 4.59 229 Intel + IB (CEA) DOE / NNSA Roadrunner, IBM10 USA 122,400 1.04 76 2.35 446 Los Alamos Nat Lab AMD + Cell GPU + IB
  5. 5. November 2011: The TOP10 Rmax % of Power MFlopsRank Site Computer Country Cores [Pflops] Peak [MW] /Watt RIKEN Advanced Inst K computer Fujitsu SPARC64 1 Japan 705,024 10.5 93 12.7 830 for Comp Sci VIIIfx + custom Nat. SuperComputer Tianhe-1A, NUDT 2 China 186,368 2.57 55 4.04 636 Center in Tianjin Intel + Nvidia GPU + custom DOE / OS Jaguar, Cray 3 USA 224,162 1.76 75 7.0 251 Oak Ridge Nat Lab AMD + custom Nat. Supercomputer Nebulea, Dawning 4 China 120,640 1.27 43 2.58 493 Center in Shenzhen Intel + Nvidia GPU + IB GSIC Center, Tokyo Tusbame 2.0, HP 5 Japan 73,278 1.19 52 1.40 865 Institute of Technology Intel + Nvidia GPU + IB DOE / NNSA Cielo, Cray 6 USA 142,272 1.11 81 3.98 279 LANL & SNL AMD + custom NASA Ames Research Plelades SGI Altix ICE 7 USA 111,104 1.09 83 4.10 265 Center/NAS 8200EX/8400EX + IB DOE / OS Hopper, Cray 8 Lawrence Berkeley Nat USA 153,408 1.054 82 2.91 362 AMD + custom Lab Commissariat a Tera-10, Bull 9 lEnergie Atomique France 138,368 1.050 84 4.59 229 Intel + IB (CEA) DOE / NNSA Roadrunner, IBM10 USA 122,400 1.04 76 2.35 446 Los Alamos Nat Lab AMD + Cell GPU + IB500 IT Service IBM Cluster, Intel + GigE USA 7,236 .051 53
  6. 6. Geographical regions Count Share % Rmax Rpeak Cores North America 272 54.40% 32923947 48374869 4659645 Eastern Asia 109 21.80% 25868736 38046465 2520930 Western Europe 49 9.80% 8020850 10532996 1173728 Northern Europe 36 7.20% 3652751 5071283 428832 Eastern Europe 11 2.20% 1482188 2519402 126856 Southern Europe 7 1.40% 665279 1047276 60904 Western Asia 6 1.20% 530526.6 808867.6 115540 Australia and New 4 0.80% 353753.5 479797.9 35424 Zealand South America 2 0.40% 269730 330444.8 37184 South-central Asia 2 0.40% 187910 242995.2 18128 Southern Africa 1 0.20% 61330 74257.9 6336 South-eastern Asia 1 0.20% 52633 98995 9304 Sums 500 100% 74069633.68 107627649.54 9192811 6
  7. 7. South America HPC Rmax Rpeak PowerRank Site System Cores (TFlop/s) (TFlop/s) (Kw) INPE (National Institute for Space Tup - Cray XT6 12-core 49 Research) 2.1 GHz 30720 205.1 258 Brazil Cray Inc. Galileu - Sun Blade NACAD/COPPE/UFRJ x6048, Xeon X5560 2.8 Ghz, Infiniband QDR 290 6464 64.6 72.4 430 Brazil Sun Microsystems 7
  8. 8. Japanese K Computer New Linpack run with 705,024 cores at 10.51 Pflop/s (88,128 CPUs) 8
  9. 9. China • First Chinese Supercomputer to use a Chinese Processor Sunway BlueLight MPP ShenWei SW1600 processor, 16 core, 65 nm, fabbed in China 125 Gflop/s peak In the Top20 with 139,364 cores & 1.07 Pflop/s Peak • Coming soon, Loongson (Godson) processor 8-core, 65nm Loongson 3B processor runs at 1.05 GHz, with a peak performance of 128 Gflop/s 9
  10. 10. Commodity plus Accelerator Commodity Accelerator (GPU) Intel Xeon Nvidia C2070 “Fermi” 8 cores 448 “Cuda cores” 3 GHz 1.15 GHz 8*4 ops/cycle 448 ops/cycle96 Gflop/s (DP) 515 Gflop/s (DP) 6 GB Interconnect PCI-X 16 lane 10 64 Gb/s 1 GW/s
  11. 11. Future Computer Systems♦ Most likely be a hybrid design Standard multicore chips and accelerator (GPUs)♦ Today accelerators are attached♦ Next generation more integrated♦ Intel’s MIC architecture “Knights Corner” 48 x86 cores♦ AMD’s Fusion Multicore with embedded graphics ATI♦ Nvidia’s Project Denver plans to develop an integrated chip using ARM architecture 11
  12. 12. Performance Development in Top500 1E+11 12 1E+10 1 Eflop/s 1E+09100 Pflop/s00000010 Pflop/s000000 1 Pflop/s N=1000000100 Tflop/s100000 10 Tflop/s 10000 1 Tflop/s N=500 1000 100 Gflop/s 100 10 Gflop/s 10 1 Gflop/s 1100 Mflop/s 0.1 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020
  13. 13. Major Changes to Software &Algorithms• Must rethink the design of our algorithms and software Another disruptive technology • Similar to what happened with cluster computing and message passing Rethink and rewrite the applications, algorithms, and software Data movement is expense Flop/s are cheap, so are provisioned in excess 13
  14. 14. Critical Issues at Peta & Exascale forAlgorithm and Software Design• Synchronization-reducing algorithms Break Fork-Join model• Communication-reducing algorithms Use methods which have lower bound on communication• Autotuning Today’s machines are too complicated, build “smarts” into software to adapt to the hardware• Fault resilient algorithms Implement algorithms that can recover from failures/bit flips• Reproducibility of results Today can’t guarantee this.
  15. 15. International Exascale Software Project Attendees from universities, Steering Committee research institutes, government, Jack Dongarra, U of Tennessee/Oak funding agencies, research Ridge National Lab, US councils, hardware and software Pete Beckman, Argonne Nat. Lab, US vendors, industry Franck Cappello, INRIA, FR Thom Dunning, NCSA, US Thomas Lippert, Jülich Supercomputing Centre, DE Satoshi Matsuoka, Tokyo Inst. of Tech, JP Paul Messina, Argonne Nat. Lab, US Patrick Aerts, Netherlands Organization for Scientific Research, NL Anne Trefethen, Oxford, UK Mateo Valero, Barcelona Supercomptuing Ceneter, Spain
  16. 16. International Exascale Software Project Objectives To enable the international HPC community to improve, coordinate and leverage their collective investments and development efforts. To develop a plan for producing a software infrastructure capable of supporting exascale applications Thorough assessment of needs, issues and strategies Develop a coordinated software roadmap Provide a framework for organizing the software research community Engage vendors to coordinate on how to deal with anticipated scale Encourage and facilitate collaboration in education and training 16
  17. 17. What Next?Moving from “What to Build” to “How to Build” Technology Defining and developing the roadmap for software and algorithms on extreme-scale systems Assessing the short-term, medium-term and long-term software and algorithm needs of applications for peta/exascale systems www.exascale.org
  18. 18. What Next?Moving from “What to Build” to “How to Build” Organization Exploring ways for funding agencies to coordinate their support so that they complement each other Exploring how laboratories, universities, and vendors can work together on coordinated HPC software Creating a plan for working closely with HW vendors and application teams to co-design future architectures www.exascale.org
  19. 19. What Next?Moving from “What to Build” to “How to Build” Execution Developing a strategic plan for moving forward Creating a realistic timeline for constructing key organizational structures and achieving initial goals Exploring community development techniques and risk plans to ensure key components are delivered on time www.exascale.org
  20. 20. US TeraGrid An instrument that delivers high-end IT resources/services a computational facility – over two PFlops Science Gateways –discipline-specific web-portal front-ends a data storage and management facility – 20 PetaBytes a high-bandwidth national data network Support, education and training events Available freely to research and education projects with a US lead
  21. 21. TeraGrid Objectives DEEP Science: enabling terascale and petascale science make science more productive through an integrated set of very- high capability resources address key challenges prioritized by users WIDE Impact: empowering communities bring TeraGrid capabilities to the broad science community partner with science community leaders OPEN Infrastructure, OPEN Partnership a coordinated, general purpose, reliable set of services and resources partner with campuses and facilities
  22. 22. The eXtreme Digital (XD) ProgramXD : third generation TeraGrid program 2002-2005: Distributed/Extended Terascale Facility 2005-2011: Grid Infrastructure + Resource Providers 2010-2016: eXtreme Digital (XD) + Service Providers
  23. 23. 11 Resource Providers, One Facility UW Grid Infrastructure Group (UChicago) UC/ANL PSC NCAR PU NCSA Caltech IU UNC/RENCI ORNLUSC/ISI NICS SDSC LONI TACC Resource Provider (RP) Software Integration Partner Network Hub
  24. 24. eXtreme Digital Resources High-Performance Computing and Storage Services High-Performance Remote Visualization and Data Analysis Services 2 awards; 5 years; $3M/year Integrating Services (5 years, $26M/year) Coordination and Management Service (CMS) 5 years; $12M/year Technology Audit and Insertion Service (TAIS) 5 years; $3M/year Advanced User Support Service (AUSS) 5 years; $8M/year Training, Education and Outreach Service (TEOS) 5 years, $3M/year
  25. 25. XSEDE : Governance Leadership led by NCSA, NICS, PSC, TACC and SDSC: centers with deep experience partners who strongly complement these centers with expertise in science, engineering, technology and education Balanced governance model strong central management, rapid response to issues and opportunities delegation and decentralization of decision-making authority openness to genuine stakeholder participation stakeholder engagement, advisory committees improved professional project management practices formal risk management and change control25
  26. 26. XSEDE: Extending Impact Coordinated national program with greater scope and scale increased diversity of topics, modes of delivery, and reach to new communities and audiences broaden participation among under-represented communities Campus bridging for effective use of resources more tightly integrate with campuses through expanded Champions program and additional bridging activities Establish certificate and degree programs institutional incorporation of CS&E curricula; professional development certificate prepare undergraduates, graduates and future K-12 teachers26
  27. 27. Summary HPC Increasingly indispensably to scientific progress and economy competitiveness Industrial competiveness ->time to market National security Quality of human life Key element for the competiveness of knowledge based economies Not HPC Leadership but innovation leadership www.exascale.org
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