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Petaflops for the People
PETAFLOPS SPOTLIGHT: NERSC housands of researchers have used facilities of the Advanced T Scientific Computing Research (ASCR) program and its EXTREME-WEATHER Department of Energy (DOE) computing predecessors over the past four decades. Their studies of hurricanes, earthquakes, NUMBER-CRUNCHING green-energy technologies and many other basic and applied Certain problems lend themselves to solution by science problems have, in turn, benefited millions of people. computers. Take hurricanes, for instance: They’re They owe it mainly to the capacity provided by the National too big, too dangerous and perhaps too expensive Energy Research Scientific Computing Center (NERSC), the Oak to understand fully without a supercomputer. Ridge Leadership Computing Facility (OLCF) and the Argonne Leadership Computing Facility (ALCF). Using decades of global climate data in a grid comprised of 25-kilometer squares, researchers in These ASCR installations have helped train the advanced Berkeley Lab’s Computational Research Division scientific workforce of the future. Postdoctoral scientists, captured the formation of hurricanes and typhoons graduate students and early-career researchers have worked and the extreme waves that they generate. Those there, learning to configure the world’s most sophisticated same models, when run at resolutions of about supercomputers for their own various and wide-ranging projects. 100 kilometers, missed the tropical cyclones and Cutting-edge supercomputing, once the purview of a small resulting waves, up to 30 meters high. group of experts, has trickled down to the benefit of thousands of investigators in the broader scientific community. Their findings, published inGeophysical Research Letters, demonstrated the importance of running Today, NERSC, at Lawrence Berkeley National Laboratory; climate models at higher resolution. -
Materials Modelling and the Challenges of Petascale and Exascale
Multiscale Materials Modelling on High Performance Computer Architectures Materials modelling and the challenges of petascale and exascale Andrew Emerson Cineca Supercomputing Centre, Bologna, Italy The project MMM@HPC is funded by the 7th Framework Programme of the European Commission within the Research Infrastructures 26/09/2013 with grant agreement number RI-261594. Contents Introduction to HPC HPC and the MMM@HPC project Petascale computing The Road to Exascale Observations 26/09/2013 A. Emerson, International Forum on Multiscale Materials Modelling, Bologna 2013 2 High Performance Computing High Performance Computing (HPC). What is it ? High-performance computing (HPC) is the use of parallel processing for running advanced application programs efficiently, reliably and quickly. The term applies especially to systems that function above a teraflop or 10 12 floating- point operations per second. (http://searchenterpriselinux.techtarget.com/definition/high -performance -computing ) A branch of computer science that concentrates on developing supercomputers and software to run on supercomputers. A main area of this discipline is developing parallel processing algorithms and software: programs that can be divided into little pieces so that each piece can be executed simultaneously by separate processors. (WEBOPEDIA ) 26/09/2013 A. Emerson, International Forum on Multiscale Materials Modelling, Bologna 2013 3 High Performance Computing Advances due to HPC, e.g. Molecular dynamics early 1990s . Lysozyme, 40k atoms 2006. Satellite tobacco mosaic virus (STMV). 1M atoms, 50ns 2008. Ribosome. 3.2M atoms, 230ns. 2011 . Chromatophore, 100M atoms (SC 2011) 26/09/2013 A. Emerson, International Forum on Multiscale Materials Modelling, Bologna 2013 4 High Performance Computing Cray-1 Supercomputer (1976) 80MHz , Vector processor → 250Mflops Cray XMP (1982) 2 CPUs+vectors, 400 MFlops “FERMI”, Bluegene/Q 168,000 cores 2.1 Pflops 26/09/2013 A. -
Science-Driven Development of Supercomputer Fugaku
Special Contribution Science-driven Development of Supercomputer Fugaku Hirofumi Tomita Flagship 2020 Project, Team Leader RIKEN Center for Computational Science In this article, I would like to take a historical look at activities on the application side during supercomputer Fugaku’s climb to the top of supercomputer rankings as seen from a vantage point in early July 2020. I would like to describe, in particular, the change in mindset that took place on the application side along the path toward Fugaku’s top ranking in four benchmarks in 2020 that all began with the Application Working Group and Computer Architecture/Compiler/ System Software Working Group in 2011. Somewhere along this path, the application side joined forces with the architecture/system side based on the keyword “co-design.” During this journey, there were times when our opinions clashed and when efforts to solve problems came to a halt, but there were also times when we took bold steps in a unified manner to surmount difficult obstacles. I will leave the description of specific technical debates to other articles, but here, I would like to describe the flow of Fugaku development from the application side based heavily on a “science-driven” approach along with some of my personal opinions. Actually, we are only halfway along this path. We look forward to the many scientific achievements and so- lutions to social problems that Fugaku is expected to bring about. 1. Introduction In this article, I would like to take a look back at On June 22, 2020, the supercomputer Fugaku the flow along the path toward Fugaku’s top ranking became the first supercomputer in history to simul- as seen from the application side from a vantage point taneously rank No. -
Unlocking the Full Potential of the Cray XK7 Accelerator
Unlocking the Full Potential of the Cray XK7 Accelerator ∗ † Mark D. Klein , and, John E. Stone ∗National Center for Supercomputing Application, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA †Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA Abstract—The Cray XK7 includes NVIDIA GPUs for ac- [2], [3], [4], and for high fidelity movie renderings with the celeration of computing workloads, but the standard XK7 HVR volume rendering software.2 In one example, the total system software inhibits the GPUs from accelerating OpenGL turnaround time for an HVR movie rendering of a trillion- and related graphics-specific functions. We have changed the operating mode of the XK7 GPU firmware, developed a custom cell inertial confinement fusion simulation [5] was reduced X11 stack, and worked with Cray to acquire an alternate driver from an estimate of over a month for data transfer to and package from NVIDIA in order to allow users to render and rendering on a conventional visualization cluster down to post-process their data directly on Blue Waters. Users are able just one day when rendered locally using 128 XK7 nodes to use NVIDIA’s hardware OpenGL implementation which has on Blue Waters. The fully-graphics-enabled GPU state is many features not available in software rasterizers. By elim- inating the transfer of data to external visualization clusters, currently considered an unsupported mode of operation by time-to-solution for users has been improved tremendously. In Cray, and to our knowledge Blue Waters is presently the one case, XK7 OpenGL rendering has cut turnaround time only Cray system currently running in this mode. -
Recent Developments in Supercomputing
John von Neumann Institute for Computing Recent Developments in Supercomputing Th. Lippert published in NIC Symposium 2008, G. M¨unster, D. Wolf, M. Kremer (Editors), John von Neumann Institute for Computing, J¨ulich, NIC Series, Vol. 39, ISBN 978-3-9810843-5-1, pp. 1-8, 2008. c 2008 by John von Neumann Institute for Computing 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. http://www.fz-juelich.de/nic-series/volume39 Recent Developments in Supercomputing Thomas Lippert J¨ulich Supercomputing Centre, Forschungszentrum J¨ulich 52425 J¨ulich, Germany E-mail: [email protected] Status and recent developments in the field of supercomputing on the European and German level as well as at the Forschungszentrum J¨ulich are presented. Encouraged by the ESFRI committee, the European PRACE Initiative is going to create a world-leading European tier-0 supercomputer infrastructure. In Germany, the BMBF formed the Gauss Centre for Supercom- puting, the largest national association for supercomputing in Europe. The Gauss Centre is the German partner in PRACE. With its new Blue Gene/P system, the J¨ulich supercomputing centre has realized its vision of a dual system complex and is heading for Petaflop/s already in 2009. In the framework of the JuRoPA-Project, in cooperation with German and European industrial partners, the JSC will build a next generation general purpose system with very good price-performance ratio and energy efficiency. -
This Is Your Presentation Title
Introduction to GPU/Parallel Computing Ioannis E. Venetis University of Patras 1 Introduction to GPU/Parallel Computing www.prace-ri.eu Introduction to High Performance Systems 2 Introduction to GPU/Parallel Computing www.prace-ri.eu Wait, what? Aren’t we here to talk about GPUs? And how to program them with CUDA? Yes, but we need to understand their place and their purpose in modern High Performance Systems This will make it clear when it is beneficial to use them 3 Introduction to GPU/Parallel Computing www.prace-ri.eu Top 500 (June 2017) CPU Accel. Rmax Rpeak Power Rank Site System Cores Cores (TFlop/s) (TFlop/s) (kW) National Sunway TaihuLight - Sunway MPP, Supercomputing Center Sunway SW26010 260C 1.45GHz, 1 10.649.600 - 93.014,6 125.435,9 15.371 in Wuxi Sunway China NRCPC National Super Tianhe-2 (MilkyWay-2) - TH-IVB-FEP Computer Center in Cluster, Intel Xeon E5-2692 12C 2 Guangzhou 2.200GHz, TH Express-2, Intel Xeon 3.120.000 2.736.000 33.862,7 54.902,4 17.808 China Phi 31S1P NUDT Swiss National Piz Daint - Cray XC50, Xeon E5- Supercomputing Centre 2690v3 12C 2.6GHz, Aries interconnect 3 361.760 297.920 19.590,0 25.326,3 2.272 (CSCS) , NVIDIA Tesla P100 Cray Inc. DOE/SC/Oak Ridge Titan - Cray XK7 , Opteron 6274 16C National Laboratory 2.200GHz, Cray Gemini interconnect, 4 560.640 261.632 17.590,0 27.112,5 8.209 United States NVIDIA K20x Cray Inc. DOE/NNSA/LLNL Sequoia - BlueGene/Q, Power BQC 5 United States 16C 1.60 GHz, Custom 1.572.864 - 17.173,2 20.132,7 7.890 4 Introduction to GPU/ParallelIBM Computing www.prace-ri.eu How do -
Hardware Complexity and Software Challenges
Trends in HPC: hardware complexity and software challenges Mike Giles Oxford University Mathematical Institute Oxford e-Research Centre ACCU talk, Oxford June 30, 2015 Mike Giles (Oxford) HPC Trends June 30, 2015 1 / 29 1 { 10? 10 { 100? 100 { 1000? Answer: 4 cores in Intel Core i7 CPU + 384 cores in NVIDIA K1100M GPU! Peak power consumption: 45W for CPU + 45W for GPU Question ?! How many cores in my Dell M3800 laptop? Mike Giles (Oxford) HPC Trends June 30, 2015 2 / 29 Answer: 4 cores in Intel Core i7 CPU + 384 cores in NVIDIA K1100M GPU! Peak power consumption: 45W for CPU + 45W for GPU Question ?! How many cores in my Dell M3800 laptop? 1 { 10? 10 { 100? 100 { 1000? Mike Giles (Oxford) HPC Trends June 30, 2015 2 / 29 Question ?! How many cores in my Dell M3800 laptop? 1 { 10? 10 { 100? 100 { 1000? Answer: 4 cores in Intel Core i7 CPU + 384 cores in NVIDIA K1100M GPU! Peak power consumption: 45W for CPU + 45W for GPU Mike Giles (Oxford) HPC Trends June 30, 2015 2 / 29 Top500 supercomputers Really impressive { 300× more capability in 10 years! Mike Giles (Oxford) HPC Trends June 30, 2015 3 / 29 My personal experience 1982: CDC Cyber 205 (NASA Langley) 1985{89: Alliant FX/8 (MIT) 1989{92: Stellar (MIT) 1990: Thinking Machines CM5 (UTRC) 1987{92: Cray X-MP/Y-MP (NASA Ames, Rolls-Royce) 1993{97: IBM SP2 (Oxford) 1998{2002: SGI Origin (Oxford) 2002 { today: various x86 clusters (Oxford) 2007 { today: various GPU systems/clusters (Oxford) 2011{15: GPU cluster (Emerald @ RAL) 2008 { today: Cray XE6/XC30 (HECToR/ARCHER @ EPCC) 2013 { today: Cray XK7 with GPUs (Titan @ ORNL) Mike Giles (Oxford) HPC Trends June 30, 2015 4 / 29 Top500 supercomputers Power requirements are raising the question of whether this rate of improvement is sustainable. -
Providing a Robust Tools Landscape for CORAL Machines
Providing a Robust Tools Landscape for CORAL Machines 4th Workshop on Extreme Scale Programming Tools @ SC15 in AusGn, Texas November 16, 2015 Dong H. Ahn Lawrence Livermore Naonal Lab Michael Brim Oak Ridge Naonal Lab Sco4 Parker Argonne Naonal Lab Gregory Watson IBM Wesley Bland Intel CORAL: Collaboration of ORNL, ANL, LLNL Current DOE Leadership Computers Objective - Procure 3 leadership computers to be Titan (ORNL) Sequoia (LLNL) Mira (ANL) 2012 - 2017 sited at Argonne, Oak Ridge and Lawrence Livermore 2012 - 2017 2012 - 2017 in 2017. Leadership Computers - RFP requests >100 PF, 2 GiB/core main memory, local NVRAM, and science performance 4x-8x Titan or Sequoia Approach • Competitive process - one RFP (issued by LLNL) leading to 2 R&D contracts and 3 computer procurement contracts • For risk reduction and to meet a broad set of requirements, 2 architectural paths will be selected and Oak Ridge and Argonne must choose different architectures • Once Selected, Multi-year Lab-Awardee relationship to co-design computers • Both R&D contracts jointly managed by the 3 Labs • Each lab manages and negotiates its own computer procurement contract, and may exercise options to meet their specific needs CORAL Innova,ons and Value IBM, Mellanox, and NVIDIA Awarded $325M U.S. Department of Energy’s CORAL Contracts • Scalable system solu.on – scale up, scale down – to address a wide range of applicaon domains • Modular, flexible, cost-effec.ve, • Directly leverages OpenPOWER partnerships and IBM’s Power system roadmap • Air and water cooling • Heterogeneous -
Summit Supercomputer
Cooling System Overview: Summit Supercomputer David Grant, PE, CEM, DCEP HPC Mechanical Engineer Oak Ridge National Laboratory Corresponding Member of ASHRAE TC 9.9 Infrastructure Co-Lead - EEHPCWG ORNL is managed by UT-Battelle, LLC for the US Department of Energy Today’s Presentation #1 ON THE TOP 500 LIST • System Description • Cooling System Components • Cooling System Performance NOVEMBER 2018 #1 JUNE 2018 #1 2 Feature Titan Summit Summit Node Overview Application Baseline 5-10x Titan Performance Number of 18,688 4,608 Nodes Node 1.4 TF 42 TF performance Memory per 32 GB DDR3 + 6 GB 512 GB DDR4 + 96 GB Node GDDR5 HBM2 NV memory per 0 1600 GB Node Total System >10 PB DDR4 + HBM2 + 710 TB Memory Non-volatile System Gemini (6.4 GB/s) Dual Rail EDR-IB (25 GB/s) Interconnect Interconnect 3D Torus Non-blocking Fat Tree Topology Bi-Section 15.6 TB/s 115.2 TB/s Bandwidth 1 AMD Opteron™ 2 IBM POWER9™ Processors 1 NVIDIA Kepler™ 6 NVIDIA Volta™ 32 PB, 1 TB/s, File System 250 PB, 2.5 TB/s, GPFS™ Lustre® Peak Power 9 MW 13 MW Consumption 3 System Description – How do we cool it? • >100,000 liquid connections 4 System Description – What’s in the data center? • Passive RDHXs- 215,150ft2 (19,988m2) of total heat exchange surface (>20X the area of the data center) – With a 70°F (21.1 °C) entering water temperature, the room averages ~73°F (22.8°C) with ~3.5MW load and ~75.5°F (23.9°C) with ~10MW load. -
Nascent Exascale Supercomputers Offer Promise, Present Challenges CORE CONCEPTS Adam Mann, Science Writer
CORE CONCEPTS Nascent exascale supercomputers offer promise, present challenges CORE CONCEPTS Adam Mann, Science Writer Sometime next year, managers at the US Department Laboratory in NM. “We have to change our computing of Energy’s (DOE) Argonne National Laboratory in paradigms, how we write our programs, and how we Lemont, IL, will power up a calculating machine the arrange computation and data management.” size of 10 tennis courts and vault the country into That’s because supercomputers are complex a new age of computing. The $500-million main- beasts, consisting of cabinets containing hundreds of frame, called Aurora, could become the world’sfirst thousands of processors. For these processors to oper- “exascale” supercomputer, running an astounding ate as a single entity, a supercomputer needs to pass 1018, or 1 quintillion, operations per second. data back and forth between its various parts, running Aurora is expected to have more than twice the huge numbers of computations at the same time, all peak performance of the current supercomputer record while minimizing power consumption. Writing pro- holder, a machine named Fugaku at the RIKEN Center grams for such parallel computing is not easy, and the- for Computational Science in Kobe, Japan. Fugaku and orists will need to leverage new tools such as machine its calculation kin serve a vital function in modern learning and artificial intelligence to make scientific scientific advancement, performing simulations crucial breakthroughs. Given these challenges, researchers for discoveries in a wide range of fields. But the transition have been planning for exascale computing for more to exascale will not be easy. -
Arxiv:2109.00082V1 [Cs.DC] 31 Aug 2021 Threshold of Exascale Computing
Plan-based Job Scheduling for Supercomputers with Shared Burst Buffers Jan Kopanski and Krzysztof Rzadca Institute of Informatics, University of Warsaw Stefana Banacha 2, 02-097 Warsaw, Poland [email protected] [email protected] Preprint of the pa- Abstract. The ever-increasing gap between compute and I/O perfor- per accepted at the mance in HPC platforms, together with the development of novel NVMe 27th International storage devices (NVRAM), led to the emergence of the burst buffer European Conference concept—an intermediate persistent storage layer logically positioned on Parallel and Dis- between random-access main memory and a parallel file system. De- tributed Computing spite the development of real-world architectures as well as research (Euro-Par 2021), Lis- concepts, resource and job management systems, such as Slurm, provide bon, Portugal, 2021, only marginal support for scheduling jobs with burst buffer requirements, DOI: 10.1007/978-3- in particular ignoring burst buffers when backfilling. We investigate the 030-85665-6_8 impact of burst buffer reservations on the overall efficiency of online job scheduling for common algorithms: First-Come-First-Served (FCFS) and Shortest-Job-First (SJF) EASY-backfilling. We evaluate the algorithms in a detailed simulation with I/O side effects. Our results indicate that the lack of burst buffer reservations in backfilling may significantly deteriorate scheduling. We also show that these algorithms can be easily extended to support burst buffers. Finally, we propose a burst-buffer–aware plan-based scheduling algorithm with simulated annealing optimisation, which im- proves the mean waiting time by over 20% and mean bounded slowdown by 27% compared to the burst-buffer–aware SJF-EASY-backfilling. -
Cell Processorprocessor Andand Cellcell Processorprocessor Basedbased Devicesdevices
CellCell ProcessorProcessor andand CellCell ProcessorProcessor BasedBased DevicesDevices May 31, 2005 SPXXL Barry Bolding, WW Deep Computing Thanks to Ashwini Nanda IBM TJ Watson Research Center New York Pathway to the Digital Media Revolution Incremental Technology Innovations Provide Stepping Stones of Progress to the Future Virtual Communities Immersive WEB Portals Virtual Travel & eCommerce 20xx "Matrix" HD Content Virtual Tokyo Creation & Delivery Real-time Creation and Modification of Content Immersive Environment Needs enormous Real-Time Engineering computing Design Collaboration power 2004 Incremental Technology Innovations on the Horizon: On-Demand Computing & Communication Infrastructures Online Games Application Optimized Processor and System Architectures Leading Edge Communication Bandwidth/Storage Capacities Immersion HW and SW Technologies Rich Media Applications, Middleware and OS CellCell ProcessorProcessor OverviewOverview CellCell HistoryHistory • IBM, SCEI/Sony, Toshiba Alliance formed in 2000 • Design Center opened in March 2001 • Based in Austin, Texas • February 7, 2005: First technical disclosures CellCell HighlightsHighlights • Multi-core microprocessor (9 cores) • The possibilities… – Supercomputer on a chip – Digital home to distributed computing and supercomputing – >10x performance potential for many kernels/algorithms • Current prototypes running <3 GHz clock frequency • Demonstrated Beehive at Electronic Entertainment Expo Meeting – TRE (Terrain Rendering Engine application) IntroducingIntroducing CellCell