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MCS Vision

Petascale Computing Grid Computing Computational Science and Engineering. Increase by several orders of magnitude the computing power that can be applied to individual scientific problems, thus enabling progress in understanding complex physical and biological systems.

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MCS Vision

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  1. Petascale Computing Grid Computing Computational Science and Engineering Increase by several orders of magnitude the computing power that can be applied to individual scientific problems, thus enabling progress in understanding complex physical and biological systems. Interconnect the world’s most important scientific databases, computing systems, instruments and facilities to improve scientific productivity and remove barriers to collaboration. Make high-end computing a core tool for challenging modeling, simulation and analysis problems. MCS Vision

  2. MCS Products/Resources • Enabling technologies • “middleware” • “tools” • “support applications” • Scientific applications • Hardware • Other fundamental CS research

  3. Enabling Technologies • Globus Toolkit • Software infrastructure/standards for Grid computing • MPICH • Our free implementation of MPI • Jumpshot • Software for analysis of message passing • pNetCDF • High performance parallel I/O library • PetsC • Toolkit for parallel matrix solves • Visualization (“Futures lab”) • Scalable parallel visualization software, large-scale displays • Access Grid • Collaboration environment

  4. Collaboration Technology – the Access Grid • Multi-way meetings and conferences over the Internet • Using high-quality video/audio technology • Large format display: 200+ installations worldwide • Easily replicated configurations, open source software • www.accessgrid.org

  5. The Grid Links People with Distributed Resources on a National Scale Sensors

  6. Some key scientific applications • Flash • Community code for general Astrophysical phenomena • ASCI project with UC • Nek5 • Biological fluids • pNeo • Neo-cortex simulations for study of epileptic seizures • QMC • Monte Carlo simulations of atomic nuclei • Nuclear Reactor Simulations

  7. Hardware Chiba City – Software Scalability R&D Addresses scalability issues in system software,open source software, and applications code. 512 CPUs, 256 nodes, Myrinet, 2TB storage, Linux. DOE OASCR funded. Installed in 1999. Jazz – Linux Cluster for ANL Applications Supports and enhances ANL application community. 50+ projects from a spectrum of S&E divisions 350 CPUs, Myrinet, 20TB storage. ANL funded. Installed in 2002. Achieved 1.1 TF sustained. Blue Gene prototype – coming soon two-rack system scalable to twenty racks

  8. Other HPC areas • Architecture and Performance Evaluation • Programming Models and Languages • Systems Software • Numerical Methods and Optimization • Software components • Software Verification • Automatic Differentiation

  9. I-Wire Impact Two concrete examples of the impact of I-WIRE Flash NLCF Blue Gene I-WIRE Teragrid

  10. I-WIRE (Illinois Wired/Wireless Infrastructure for Research and Education) Starlight International Optical Network Hub (NU-Chicago) • State Funded Dark Fiber Optical Infrastructure to support Networking and Applications Research • $11.5M Total Funding • $6.5M FY00-03 • $5M in process for FY04-5 • Application Driven • Access Grid: Telepresence & Media • TeraGrid: Computational and Data Grids • New Technologies Proving Ground • Optical Network Technologies • Middleware and Computer Science Research • Deliverables • A flexible infrastructure to support advanced applications and networking research UIC Argonne National Laboratory IIT U Chicago 40 Gb/s Distributed Terascale Facility Network Chicago U Chicago Gleacher Center UIUC/NCSA James R. Thompson Center – Illinois Century Network Commercial Fiber Hub

  11. ANL Starlight / NU-C UChicagoGleacher Ctr UChicagoMain UIUC/NCSA UIC IIT ICN Commercial Fiber Hub Status: I-WIRE Geography Northwestern Univ-Chicago “Starlight” I-290 UI-Chicago I-294 I-55 Illinois Inst. Tech I-90/94 Argonne Nat’l Lab (approx 25 miles SW) UIUC/NCSA Urbana (approx 140 miles South) U of Chicago

  12. Largest NSF compute resources Largest DOE instrument (SNS) Fastest network Massive storage Visualization instruments Science Gateways Community databases TeraGrid Vision: A Unified National HPC Infrastructure that is Persistent and Reliable E.g: Geosciences: 4 data collections including high-res CT scans, global telemetry data, worldwide hydrology data, and regional LIDAR terrain data

  13. Resources and Services(33TF, 1.1PB disk, 12 PB tape)

  14. Current TeraGrid Network Caltech UC/ANL PSC Los Angeles Chicago Atlanta SDSC TACC NCSA Purdue IU ORNL Resources: Compute, Data, Instrument, Science Gateways

  15. Flash • FlashProject • Community Astrophysics code • DOE funded ASCI program at UC/Argonne • 4 million per year over ten years • Currently in 7th year • Flash Code/Framework • Heavy emphasis on software engineering, performance, and usability • 500+ downloads • Active user community • Runs on all major hpc platforms • Public automated testing facility • Extensive user documentation

  16. Flash -- Simulating Astrophysical processes Shortly: Relativistic accretion onto NS Flame-vortex interactions Compressed turbulence Type Ia Supernova Gravitational collapse/Jeans instability Wave breaking on white dwarfs Intracluster interactions Laser-driven shock instabilities Nova outbursts on white dwarfs Rayleigh-Taylor instability Orzag/Tang MHD vortex Helium burning on neutron stars Cellular detonation Magnetic Rayleigh-Taylor Richtmyer-Meshkov instability

  17. How has fast network helped Flash? • Flash in production for five years • Generating terabytes of data • Currently done “by hand” • Data transferred locally from supercomputing centers for visualization/analysis • Data remotely visualized at UC using Argonne servers • Can harness data storage across several sites • Not just “visionary” grid ideas that are useful. Immediate “mundane” things as well!

  18. Buoyed Progress in HPC • FLASH flagship application for BG/L • Currently being run on 4K processors at Watson • Will run on 16K procs in several months • Argonne partnership with Oak Ridge for National Leadership Class Computing Facility • Non-classified computing • BG at Argonne • X1, Black Widow at ORNL • Application focus groups apply for time

  19. We arehere Petaflops Hardware is Just Around the Corner Teraflops Petaflops

  20. Diverse Architectures for Petaflop Systems • IBM – Blue Gene • Puts processors + cache + network interfaces on same chip • Achieves high packaging density, low power consumption • Cray – RS and X1 • 10K processor (40 TF) Red Storm at SNL • 1K processor (20 TF) X1 to ORNL • Emerging • Field Programmable Gate Arrays • Processor in Memory • Streams … • = systems slated for DOE National Leadership Computing Facility

  21. SciDAC Astrophysics Genomesto Life Nanophase Materials SciDAC Climate SciDAC Fusion SciDAC Chemistry NLCF Target Application Areas

  22. The Blue Gene Consortium: Goals • Provide new capabilities to selected applications partnerships. • Provide functional requirements for a petaflop/sec version of BG. • Build a community around a new class of architecture. • Thirty university and lab partners • About ten hardware partners and about twenty software collaborators • Develop a new, sustainable model of partnership. • “Research product” by passing normal “productization” process/costs • Community-based support model (hub and spoke) • Engage (or re-engage) computer science researchers with high-performance computing architecture. • Broad community access to hardware systems • Scalable operating system research and novel software research • Partnership of DOE, NSF, NIH, NNSA, and IBM will work on computer science, computational science, and architecture development. • Kickoff meeting was April 27, 2004, in Chicago.

  23. Determining application fit • How will applications map onto different petaflop architectures? applications Black Widow BG/P BG/Q ? Our focus X1 Red Storm BG/L Cluster Vector/parallel Massively parallel Fine grain

  24. Application Analysis Process • Look for inauspicious scalability bottlenecks • May be based on data from • conventional systems or BGSim • Extrapolate conclusions • Model 0th order behavior A priori algorithmic performance analysis 0th order scaling problems Rewrite algorithms? Scalability Analysis(Jumpshot, FPMPI) Detailed message passing statistics on BG hardware Validate model (BG/L hardware) • Use of memory hierarchy • Use of pipeline • Instruction mix • Bandwidth vs. latency • etc. Performance Analysis (PAPI, hpmlib) Detailed architectural adjustments Refine model Tune code

  25. High performance resources operate in complex and highly distributed environments • Argonne co-founded the Grid • Establishing a persistent, standards-based infrastructure and applications interfaces that enable high performance assess to computation and data • ANL created the Global Grid Forum, an international standards body • We lead development of the Globus Toolkit • ANL staff are PIs and key contributors in many grid technology development and application projects • High performance data transport, Grid security, virtual organization mgt., Open Grid Services Architecture, … • Access Grid – group-to-group collaboration via large multimedia displays

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