Highlights of the 51St TOP500 List

Total Page:16

File Type:pdf, Size:1020Kb

Highlights of the 51St TOP500 List ISC 2018, Frankfurt, Highlights of June 25, 2018 the 51st Erich TOP500 List Strohmaier ISC18 TOP500 TOPICS • New #1 • New TOP5 • Slow-down, aging, and concentration • 25 years of systems and sites • China, a new twist • Industry and GPUs • HPCG petaflops Power # Site Manufacturer Computer Country Cores Rmax ST [Pflops] [MW] Oak Ridge 41 LIST: THESummit TOP10 1 IBM USA 2,282,544 122.3 8.8 National Laboratory IBM Power System, P9 22C 3.07GHz, Mellanox EDR, NVIDIA GV100 National Supercomputing Sunway TaihuLight 2 NRCPC China 10,649,600 93.0 15.4 Center in Wuxi NRCPC Sunway SW26010, 260C 1.45GHz Lawrence Livermore Sierra 3 IBM USA 1,572,480 71.6 National Laboratory IBM Power System, P9 22C 3.1GHz, Mellanox EDR, NVIDIA GV100 National University of Tianhe-2A 4 NUDT China 4,981,760 61.4 18.5 Defense Technology ANUDT TH-IVB-FEP, Xeon 12C 2.2GHz, Matrix-2000 National Institute of Advanced AI Bridging Cloud Infrastructure (ABCI) 5 Fujitsu Japan 391,680 19.9 1.65 Industrial Science and Technology PRIMERGY CX2550 M4, Xeon Gold 20C 2.4GHz, IB-EDR, NVIDIA V100 Swiss National Supercomputing Piz Daint 6 Cray Switzerland 361,760 19.6 2.27 Centre (CSCS) Cray XC50, Xeon E5 12C 2.6GHz, Aries, NVIDIA Tesla P100 Oak Ridge Titan 7 Cray USA 560,640 17.6 8.21 National Laboratory Cray XK7, Opteron 16C 2.2GHz, Gemini, NVIDIA K20x Lawrence Livermore Sequoia 8 IBM USA 1,572,864 17.2 7.89 National Laboratory BlueGene/Q, Power BQC 16C 1.6GHz, Custom Los Alamos NL / Trinity 9 Cray USA 979,968 14.1 3.84 Sandia NL Cray XC40, Intel Xeon Phi 7250 68C 1.4GHz, Aries Cori Lawrence Berkeley 10 Cray Cray XC40, USA 622,336 14.0 3.94 National Laboratory Intel Xeons Phi 7250 68C 1.4 GHz, Aries System Overview System Performance Each node has The system includes • Peak performance of 200 • 2 IBM POWER9 • 4608 nodes petaflops for modeling & processors • Dual-rail Mellanox EDR simulation • 6 NVIDIA Tesla V100 GPUs InfiniBand network • Peak of 3.3 ExaOps for data • 608 GB of fast memory • 250 PB IBM Spectrum analytics and artificial • 1.6 TB of NVMe memory Scale intelligence file system transferring data at 2.5 TB/s 5 Power # Site Manufacturer Computer Country Cores Rmax ST [Pflops] [MW] Oak Ridge 41 LIST: THESummit TOP10 1 IBM USA 2,282,544 122.3 8.8 National Laboratory IBM Power System, P9 22C 3.07GHz, Mellanox EDR, NVIDIA GV100 National Supercomputing Sunway TaihuLight 2 NRCPC China 10,649,600 93.0 15.4 Center in Wuxi NRCPC Sunway SW26010, 260C 1.45GHz Lawrence Livermore Sierra 3 IBM USA 1,572,480 71.6 National Laboratory IBM Power System, P9 22C 3.1GHz, Mellanox EDR, NVIDIA GV100 National University of Tianhe-2A 4 NUDT China 4,981,760 61.4 18.5 Defense Technology ANUDT TH-IVB-FEP, Xeon 12C 2.2GHz, Matrix-2000 National Institute of Advanced AI Bridging Cloud Infrastructure (ABCI) 5 Fujitsu Japan 391,680 19.9 1.65 Industrial Science and Technology PRIMERGY CX2550 M4, Xeon Gold 20C 2.4GHz, IB-EDR, NVIDIA V100 Swiss National Supercomputing Piz Daint 6 Cray Switzerland 361,760 19.6 2.27 Centre (CSCS) Cray XC50, Xeon E5 12C 2.6GHz, Aries, NVIDIA Tesla P100 Oak Ridge Titan 7 Cray USA 560,640 17.6 8.21 National Laboratory Cray XK7, Opteron 16C 2.2GHz, Gemini, NVIDIA K20x Lawrence Livermore Sequoia 8 IBM USA 1,572,864 17.2 7.89 National Laboratory BlueGene/Q, Power BQC 16C 1.6GHz, Custom Los Alamos NL / Trinity 9 Cray USA 979,968 14.1 3.84 Sandia NL Cray XC40, Intel Xeon Phi 7250 68C 1.4GHz, Aries Cori Lawrence Berkeley 10 Cray Cray XC40, USA 622,336 14.0 3.94 National Laboratory Intel Xeons Phi 7250 68C 1.4 GHz, Aries AVERAGE SYSTEM AGE 25 20 15 10 7.6 month Age [Months] 5 0 RANK AT WHICH HALF OF TOTAL PERFORMANCE IS ACCUMULATED 100 80 60 40 20 0 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 PERFORMANCE DEVELOPMENT June 2013 10 Eflop/s 1.00E+10 1.21 EFlop/s 1 Eflop/s 1.00E+09 122 PFlop/s 1.00E+08 100 Pflop/s 1.00E+07 10 Pflop/s SUM 716 TFlop/s 1.00E+06 1 Pflop/s 1.00E+05 100 Tflop/s 1.00E+04 10 Tflop/s N=1 1.00E+03 1 Tflop/s 1.17 TFlop/s 1.00E+02 100 Gflop/s N=500 59.7 GFlop/s 1.00E+01 10 Gflop/s June 2008 1.00E+00 1 Gflop/s 422 MFlop/s 1.00E-01 100 Mflop/s 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 ANNUAL PERFORMANCE INCREASE OF THE TOP500 2.6 2.4 TOP500 2.2 1000 x 2 TOP500: Averages 11 y 1.8 15 y 1.6 Moore’s Law 20 y 1.4 1.2 1 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 25 Years – 51 Editions How do we integrate/aggregate over time/editions? • System counts are focused on the low end • Moore’s Law overpowers everything performance based • Normalize each list by average performance • HPL not Peak • Average performance not max (#1) or min • Add up contributions from various lists over time • Each full lists contributed a total of 500 • 51 lists together have a total weight of 25,500 No. 1’s – HPL R_max 11.0E+06 Eflop/s Summit Sunway TaihuLight 1001.0E+05 Pflop/s Tianhe-2 Titan 10 Pflop/s Sequoia 1.0E+04 K computer 1 Pflop/s Tianhe-1A 1.0E+03 Jaguar 100 Tflop/s Roadrunner 1.0E+02 BlueGene/L 10 Tflop/s Earth-Simulator 1.0E+01 ASCI White 1 Tflop/s ASCI Red 1.0E+00 CP-PACS/2048 SR2201/1024 100 Gflop/s 1.0E-01 XP/S140 Numerical Wind Tunnel 10 Gflop/s 1.0E-02 CM-5/1024 1995 2000 2005 2010 2015 # 1’s – Accumulated Norm-HPL 500 Summit Sunway TaihuLight 450 Tianhe-2 Titan 400 Sequoia 350 K computer Tianhe-1A 300 Jaguar Roadrunner 250 BlueGene/L 200 Earth-Simulator ASCI White 150 ASCI Red CP-PACS/2048 100 SR2201/1024 50 XP/S140 Numerical Wind Tunnel 0 CM-5/1024 1995 2000 2005 2010 2015 Dominant Sites # Site Country Norm-HPL 1 LLNL USA 1,504 2 LANL USA 816 3 ORNL USA 795 4 SNL USA 658 5 NSCC Guangzhou China 474 6 RIKEN AICS Japan 361 7 NASA/Ames USA 356 8 FZ Jülich Germany 339 9 JAMSTEC Japan 325 10 NERSC / LBNL USA 310 11 ANL USA 305 COUNTRIES 500 China 400 Korea, South Italy 300 Canada 200 France United Kingdom 100 Germany 0 Japan United States 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 COUNTRIES / SYSTEM SHARE South Korea, 1% Others, 10% United States Ireland, 1% China Netherlands, 2% Japan France, 4% United United Kindom Germany, 4% States, 25% United Kindom, Germany 5% China, 41% France Japan, 7% Netherlands Ireland 100 200 300 400 500 0 1993 1995 1997 1999 2001 PRODUCERS 2003 2005 2007 2009 2011 2013 2015 2017 Japan Europe China USA Russia VENDORS / SYSTEM SHARE Penguin Others, 38, 8% Fujitsu, Compung, Lenovo 13, 3% 11, 2% HPE Dell EMC, 13, 3% Lenovo, 117, 23% Inspur Huawei, 14, 3% Sugon IBM, 18, 4% HPE, 79, Cray Inc. Bull, 21, 4% 16% Bull Cray Inc., 53, IBM 10% Inspur, 68, 13% Huawei Sugon, 55, 11% # of systems, % of 500 VENDORS / PERFORMANCE SHARE others, 132, 11% Lenovo, 143, Lenovo NRCPC, 12% Penguin 94, 8% HPE Compung, HPE, 120, 10% 15, 1% Inspur Fujitsu, 64, 5% Sugon Inspur, 73, 6% Dell EMC, 26, 2% Cray Inc. Huawei, 12, IBM, 239, Sugon, 53, 4% Bull 1% 20% IBM Cray Inc., 188, Huawei Bull, 52, 4% 16% Sum of Pflop/s, % of whole list ACCELERATORS 130 Matrix-2000 120 PEZY-SC 110 100 Kepler/Phi 90 Xeon Phi Main 80 Intel Xeon Phi 70 Clearspeed 60 IBM Cell Systems 50 40 ATI Radeon 30 Nvidia Volta 20 Nvidia Pascal 10 Nvidia Kepler 0 Nvidia Fermi 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 PERFORMANCE SHARE OF ACCELERATORS 60% 50% Xeon Phi Main 40% Accelerators 30% Performance 20% 10% FracYon of Total TOP500 0% 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 MOST ENERGY EFFICIENT ARCHITECTURES Rmax/ Computer Power Shoubou system B, ZettaScaler-2.2 Xeon 16C 1.3GHz Infiniband EDR PEZY-SC2 18.4 Suiren2, ZettaScaler-2.2 Xeon 16C 1.3GHz Infiniband EDR PEZY-SC2 16.8 Sakura, ZettaScaler-2.2 Xeon 8C 2.3GHz Infiniband EDR PEZY-SC2 16.7 DGX Saturn V, NVIDIA DGX-1 Volta36 Xeon 20C 2.2GHz Infiniband EDR Tesla V100 15.1* Summit, IBM Power System Power9 22C 3.07GHz Infiniband EDR Volta GV100 13.9 Tsubame 3.0, SGI ICE XA Xeon 14C 2.4GHz Intel Omni-Path Tesla P100 SXM2 13.7* AIST AI Cloud, NEC 4U-8GPU Xeon 10C 1.8GHz Infiniband EDR Tesla P100 SXM2 12.7 AI Bridging Cloud Infrastructure (ABCI), Xeon Gold 20C Infiniband EDR Tesla V100 SXM2 12.1 Fujitsu PRIMERGY, NVIDIA Tesla V100 2.4GHz MareNostrum P9 CTE, IBM Power System Power9 22C 3.1GHz Infiniband EDR Tesla V100 11.9 Wilkes-2, Dell C4130 Xeon 12C 2.2GHz Infiniband EDR Tesla P100 10.4 * Efficiency based on Power op`mized HPL runs of equal size to TOP500 run.
Recommended publications
  • ORNL Debuts Titan Supercomputer Table of Contents
    ReporterRetiree Newsletter December 2012/January 2013 SCIENCE ORNL debuts Titan supercomputer ORNL has completed the installation of Titan, a supercomputer capable of churning through more than 20,000 trillion calculations each second—or 20 petaflops—by employing a family of processors called graphic processing units first created for computer gaming. Titan will be 10 times more powerful than ORNL’s last world-leading system, Jaguar, while overcoming power and space limitations inherent in the previous generation of high- performance computers. ORNL is now home to Titan, the world’s most powerful supercomputer for open science Titan, which is supported by the DOE, with a theoretical peak performance exceeding 20 petaflops (quadrillion calculations per second). (Image: Jason Richards) will provide unprecedented computing power for research in energy, climate change, efficient engines, materials and other disciplines and pave the way for a wide range of achievements in “Titan will provide science and technology. unprecedented computing Table of Contents The Cray XK7 system contains 18,688 nodes, power for research in energy, with each holding a 16-core AMD Opteron ORNL debuts Titan climate change, materials 6274 processor and an NVIDIA Tesla K20 supercomputer ............1 graphics processing unit (GPU) accelerator. and other disciplines to Titan also has more than 700 terabytes of enable scientific leadership.” Betty Matthews memory. The combination of central processing loves to travel .............2 units, the traditional foundation of high- performance computers, and more recent GPUs will allow Titan to occupy the same space as Service anniversaries ......3 its Jaguar predecessor while using only marginally more electricity. “One challenge in supercomputers today is power consumption,” said Jeff Nichols, Benefits ..................4 associate laboratory director for computing and computational sciences.
    [Show full text]
  • Linpack Evaluation on a Supercomputer with Heterogeneous Accelerators
    Linpack Evaluation on a Supercomputer with Heterogeneous Accelerators Toshio Endo Akira Nukada Graduate School of Information Science and Engineering Global Scientific Information and Computing Center Tokyo Institute of Technology Tokyo Institute of Technology Tokyo, Japan Tokyo, Japan [email protected] [email protected] Satoshi Matsuoka Naoya Maruyama Global Scientific Information and Computing Center Global Scientific Information and Computing Center Tokyo Institute of Technology/National Institute of Informatics Tokyo Institute of Technology Tokyo, Japan Tokyo, Japan [email protected] [email protected] Abstract—We report Linpack benchmark results on the Roadrunner or other systems described above, it includes TSUBAME supercomputer, a large scale heterogeneous system two types of accelerators. This is due to incremental upgrade equipped with NVIDIA Tesla GPUs and ClearSpeed SIMD of the system, which has been the case in commodity CPU accelerators. With all of 10,480 Opteron cores, 640 Xeon cores, 648 ClearSpeed accelerators and 624 NVIDIA Tesla GPUs, clusters; they may have processors with different speeds as we have achieved 87.01TFlops, which is the third record as a result of incremental upgrade. In this paper, we present a heterogeneous system in the world. This paper describes a Linpack implementation and evaluation results on TSUB- careful tuning and load balancing method required to achieve AME with 10,480 Opteron cores, 624 Tesla GPUs and 648 this performance. On the other hand, since the peak speed is ClearSpeed accelerators. In the evaluation, we also used a 163 TFlops, the efficiency is 53%, which is lower than other systems.
    [Show full text]
  • Tsubame 2.5 Towards 3.0 and Beyond to Exascale
    Being Very Green with Tsubame 2.5 towards 3.0 and beyond to Exascale Satoshi Matsuoka Professor Global Scientific Information and Computing (GSIC) Center Tokyo Institute of Technology ACM Fellow / SC13 Tech Program Chair NVIDIA Theater Presentation 2013/11/19 Denver, Colorado TSUBAME2.0 NEC Confidential TSUBAME2.0 Nov. 1, 2010 “The Greenest Production Supercomputer in the World” TSUBAME 2.0 New Development >600TB/s Mem BW 220Tbps NW >12TB/s Mem BW >400GB/s Mem BW >1.6TB/s Mem BW Bisecion BW 80Gbps NW BW 35KW Max 1.4MW Max 32nm 40nm ~1KW max 3 Performance Comparison of CPU vs. GPU 1750 GPU 200 GPU ] 1500 160 1250 GByte/s 1000 120 750 80 500 CPU CPU 250 40 Peak Performance [GFLOPS] Performance Peak 0 Memory Bandwidth [ Bandwidth Memory 0 x5-6 socket-to-socket advantage in both compute and memory bandwidth, Same power (200W GPU vs. 200W CPU+memory+NW+…) NEC Confidential TSUBAME2.0 Compute Node 1.6 Tflops Thin 400GB/s Productized Node Mem BW as HP 80GBps NW ProLiant Infiniband QDR x2 (80Gbps) ~1KW max SL390s HP SL390G7 (Developed for TSUBAME 2.0) GPU: NVIDIA Fermi M2050 x 3 515GFlops, 3GByte memory /GPU CPU: Intel Westmere-EP 2.93GHz x2 (12cores/node) Multi I/O chips, 72 PCI-e (16 x 4 + 4 x 2) lanes --- 3GPUs + 2 IB QDR Memory: 54, 96 GB DDR3-1333 SSD:60GBx2, 120GBx2 Total Perf 2.4PFlops Mem: ~100TB NEC Confidential SSD: ~200TB 4-1 2010: TSUBAME2.0 as No.1 in Japan > All Other Japanese Centers on the Top500 COMBINED 2.3 PetaFlops Total 2.4 Petaflops #4 Top500, Nov.
    [Show full text]
  • 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.
    [Show full text]
  • 2017 HPC Annual Report Team Would Like to Acknowledge the Invaluable Assistance Provided by John Noe
    sandia national laboratories 2017 HIGH PERformance computing The 2017 High Performance Computing Annual Report is dedicated to John Noe and Dino Pavlakos. Building a foundational framework Editor in high performance computing Yasmin Dennig Contributing Writers Megan Davidson Sandia National Laboratories has a long history of significant contributions to the high performance computing Mattie Hensley community and industry. Our innovative computer architectures allowed the United States to become the first to break the teraflop barrier—propelling us to the international spotlight. Our advanced simulation and modeling capabilities have been integral in high consequence US operations such as Operation Burnt Frost. Strong partnerships with industry leaders, such as Cray, Inc. and Goodyear, have enabled them to leverage our high performance computing capabilities to gain a tremendous competitive edge in the marketplace. Contributing Editor Laura Sowko As part of our continuing commitment to provide modern computing infrastructure and systems in support of Sandia’s missions, we made a major investment in expanding Building 725 to serve as the new home of high performance computer (HPC) systems at Sandia. Work is expected to be completed in 2018 and will result in a modern facility of approximately 15,000 square feet of computer center space. The facility will be ready to house the newest National Nuclear Security Administration/Advanced Simulation and Computing (NNSA/ASC) prototype Design platform being acquired by Sandia, with delivery in late 2019 or early 2020. This new system will enable continuing Stacey Long advances by Sandia science and engineering staff in the areas of operating system R&D, operation cost effectiveness (power and innovative cooling technologies), user environment, and application code performance.
    [Show full text]
  • Safety and Security Challenge
    SAFETY AND SECURITY CHALLENGE TOP SUPERCOMPUTERS IN THE WORLD - FEATURING TWO of DOE’S!! Summary: The U.S. Department of Energy (DOE) plays a very special role in In fields where scientists deal with issues from disaster relief to the keeping you safe. DOE has two supercomputers in the top ten supercomputers in electric grid, simulations provide real-time situational awareness to the whole world. Titan is the name of the supercomputer at the Oak Ridge inform decisions. DOE supercomputers have helped the Federal National Laboratory (ORNL) in Oak Ridge, Tennessee. Sequoia is the name of Bureau of Investigation find criminals, and the Department of the supercomputer at Lawrence Livermore National Laboratory (LLNL) in Defense assess terrorist threats. Currently, ORNL is building a Livermore, California. How do supercomputers keep us safe and what makes computing infrastructure to help the Centers for Medicare and them in the Top Ten in the world? Medicaid Services combat fraud. An important focus lab-wide is managing the tsunamis of data generated by supercomputers and facilities like ORNL’s Spallation Neutron Source. In terms of national security, ORNL plays an important role in national and global security due to its expertise in advanced materials, nuclear science, supercomputing and other scientific specialties. Discovery and innovation in these areas are essential for protecting US citizens and advancing national and global security priorities. Titan Supercomputer at Oak Ridge National Laboratory Background: ORNL is using computing to tackle national challenges such as safe nuclear energy systems and running simulations for lower costs for vehicle Lawrence Livermore's Sequoia ranked No.
    [Show full text]
  • Towards Exascale Computing
    TowardsTowards ExascaleExascale Computing:Computing: TheThe ECOSCALEECOSCALE ApproachApproach Dirk Koch, The University of Manchester, UK ([email protected]) 1 Motivation: let’s build a 1,000,000,000,000,000,000 FLOPS Computer (Exascale computing: 1018 FLOPS = one quintillion or a billion billion floating-point calculations per sec.) 2 1,000,000,000,000,000,000 FLOPS . 10,000,000,000,000,000,00 FLOPS 1975: MOS 6502 (Commodore 64, BBC Micro) 3 Sunway TaihuLight Supercomputer . 2016 (fully operational) . 12,543,6000,000,000,000,00 FLOPS (125.436 petaFLOPS) . Architecture Sunway SW26010 260C (Digital Alpha clone) 1.45GHz 10,649,600 cores . Power “The cooling system for TaihuLight uses a closed- coupled chilled water outfit suited for 28 MW with a custom liquid cooling unit”* *https://www.nextplatform.com/2016/06/20/look-inside-chinas-chart-topping-new-supercomputer/ . Cost US$ ~$270 million 4 TOP500 Performance Development We need more than all the performance of all TOP500 machines together! 5 TaihuLight for Exascale Computing? We need 8x the worlds fastest supercomputer: . Architecture Sunway SW26010 260C (Digital Alpha clone) @1.45GHz: > 85M cores . Power 224 MW (including cooling) costs ~ US$ 40K/hour, US$ 340M/year from coal: 2,302,195 tons of CO2 per year . Cost US$ 2.16 billion We have to get at least 10x better in energy efficiency 2-3x better in cost Also: scalable programming models 6 Alternative: Green500 Shoubu supercomputer (#1 Green500 in 2015): . Cores: 1,181,952 . Theoretical Peak: 1,535.83 TFLOPS/s . Memory: 82 TB . Processor: Xeon E5-2618Lv3 8C 2.3GHz .
    [Show full text]
  • Computational PHYSICS Shuai Dong
    Computational physiCs Shuai Dong Evolution: Is this our final end-result? Outline • Brief history of computers • Supercomputers • Brief introduction of computational science • Some basic concepts, tools, examples Birth of Computational Science (Physics) The first electronic general-purpose computer: Constructed in Moore School of Electrical Engineering, University of Pennsylvania, 1946 ENIAC: Electronic Numerical Integrator And Computer ENIAC Electronic Numerical Integrator And Computer • Design and construction was financed by the United States Army. • Designed to calculate artillery firing tables for the United States Army's Ballistic Research Laboratory. • It was heralded in the press as a "Giant Brain". • It had a speed of one thousand times that of electro- mechanical machines. • ENIAC was named an IEEE Milestone in 1987. Gaint Brain • ENIAC contained 17,468 vacuum tubes, 7,200 crystal diodes, 1,500 relays, 70,000 resistors, 10,000 capacitors and around 5 million hand-soldered joints. It weighed more than 27 tons, took up 167 m2, and consumed 150 kW of power. • This led to the rumor that whenever the computer was switched on, lights in Philadelphia dimmed. • Input was from an IBM card reader, and an IBM card punch was used for output. Development of micro-computers modern PC 1981 IBM PC 5150 CPU: Intel i3,i5,i7, CPU: 8088, 5 MHz 3 GHz Floppy disk or cassette Solid state disk 1984 Macintosh Steve Jobs modern iMac Supercomputers The CDC (Control Data Corporation) 6600, released in 1964, is generally considered the first supercomputer. Seymour Roger Cray (1925-1996) The father of supercomputing, Cray-1 who created the supercomputer industry. Cray Inc.
    [Show full text]
  • Lessons Learned in Deploying the World's Largest Scale Lustre File
    Lessons Learned in Deploying the World’s Largest Scale Lustre File System Galen M. Shipman, David A. Dillow, Sarp Oral, Feiyi Wang, Douglas Fuller, Jason Hill, Zhe Zhang Oak Ridge Leadership Computing Facility, Oak Ridge National Laboratory Oak Ridge, TN 37831, USA fgshipman,dillowda,oralhs,fwang2,fullerdj,hilljj,[email protected] Abstract 1 Introduction The Spider system at the Oak Ridge National Labo- The Oak Ridge Leadership Computing Facility ratory’s Leadership Computing Facility (OLCF) is the (OLCF) at Oak Ridge National Laboratory (ORNL) world’s largest scale Lustre parallel file system. Envi- hosts the world’s most powerful supercomputer, sioned as a shared parallel file system capable of de- Jaguar [2, 14, 7], a 2.332 Petaflop/s Cray XT5 [5]. livering both the bandwidth and capacity requirements OLCF also hosts an array of other computational re- of the OLCF’s diverse computational environment, the sources such as a 263 Teraflop/s Cray XT4 [1], visual- project had a number of ambitious goals. To support the ization, and application development platforms. Each of workloads of the OLCF’s diverse computational plat- these systems requires a reliable, high-performance and forms, the aggregate performance and storage capacity scalable file system for data storage. of Spider exceed that of our previously deployed systems Parallel file systems on leadership-class systems have by a factor of 6x - 240 GB/sec, and 17x - 10 Petabytes, traditionally been tightly coupled to single simulation respectively. Furthermore, Spider supports over 26,000 platforms. This approach had resulted in the deploy- clients concurrently accessing the file system, which ex- ment of a dedicated file system for each computational ceeds our previously deployed systems by nearly 4x.
    [Show full text]
  • Titan: a New Leadership Computer for Science
    Titan: A New Leadership Computer for Science Presented to: DOE Advanced Scientific Computing Advisory Committee November 1, 2011 Arthur S. Bland OLCF Project Director Office of Science Statement of Mission Need • Increase the computational resources of the Leadership Computing Facilities by 20-40 petaflops • INCITE program is oversubscribed • Programmatic requirements for leadership computing continue to grow • Needed to avoid an unacceptable gap between the needs of the science programs and the available resources • Approved: Raymond Orbach January 9, 2009 • The OLCF-3 project comes out of this requirement 2 ASCAC – Nov. 1, 2011 Arthur Bland INCITE is 2.5 to 3.5 times oversubscribed 2007 2008 2009 2010 2011 2012 3 ASCAC – Nov. 1, 2011 Arthur Bland What is OLCF-3 • The next phase of the Leadership Computing Facility program at ORNL • An upgrade of Jaguar from 2.3 Petaflops (peak) today to between 10 and 20 PF by the end of 2012 with operations in 2013 • Built with Cray’s newest XK6 compute blades • When completed, the new system will be called Titan 4 ASCAC – Nov. 1, 2011 Arthur Bland Cray XK6 Compute Node XK6 Compute Node Characteristics AMD Opteron 6200 “Interlagos” 16 core processor @ 2.2GHz Tesla M2090 “Fermi” @ 665 GF with 6GB GDDR5 memory Host Memory 32GB 1600 MHz DDR3 Gemini High Speed Interconnect Upgradeable to NVIDIA’s next generation “Kepler” processor in 2012 Four compute nodes per XK6 blade. 24 blades per rack 5 ASCAC – Nov. 1, 2011 Arthur Bland ORNL’s “Titan” System • Upgrade of existing Jaguar Cray XT5 • Cray Linux Environment
    [Show full text]
  • Musings RIK FARROWOPINION
    Musings RIK FARROWOPINION Rik is the editor of ;login:. While preparing this issue of ;login:, I found myself falling down a rabbit hole, like [email protected] Alice in Wonderland . And when I hit bottom, all I could do was look around and puzzle about what I discovered there . My adventures started with a casual com- ment, made by an ex-Cray Research employee, about the design of current super- computers . He told me that today’s supercomputers cannot perform some of the tasks that they are designed for, and used weather forecasting as his example . I was stunned . Could this be true? Or was I just being dragged down some fictional rabbit hole? I decided to learn more about supercomputer history . Supercomputers It is humbling to learn about the early history of computer design . Things we take for granted, such as pipelining instructions and vector processing, were impor- tant inventions in the 1970s . The first supercomputers were built from discrete components—that is, transistors soldered to circuit boards—and had clock speeds in the tens of nanoseconds . To put that in real terms, the Control Data Corpora- tion’s (CDC) 7600 had a clock cycle of 27 .5 ns, or in today’s terms, 36 4. MHz . This was CDC’s second supercomputer (the 6600 was first), but included instruction pipelining, an invention of Seymour Cray . The CDC 7600 peaked at 36 MFLOPS, but generally got 10 MFLOPS with carefully tuned code . The other cool thing about the CDC 7600 was that it broke down at least once a day .
    [Show full text]
  • FCMSSR Meeting 2018-01 All Slides
    Federal Committee for Meteorological Services and Supporting Research (FCMSSR) Dr. Neil Jacobs Assistant Secretary for Environmental Observation and Prediction and FCMSSR Chair April 30, 2018 Office of the Federal Coordinator for Meteorology Services and Supporting Research 1 Agenda 2:30 – Opening Remarks (Dr. Neil Jacobs, NOAA) 2:40 – Action Item Review (Dr. Bill Schulz, OFCM) 2:45 – Federal Coordinator's Update (OFCM) 3:00 – Implementing Section 402 of the Weather Research And Forecasting Innovation Act Of 2017 (OFCM) 3:20 – Federal Meteorological Services And Supporting Research Strategic Plan and Annual Report. (OFCM) 3:30 – Qualification Standards For Civilian Meteorologists. (Mr. Ralph Stoffler, USAF A3-W) 3:50 – National Earth System Predication Capability (ESPC) High Performance Computing Summary. (ESPC Staff) 4:10 – Open Discussion (All) 4:20 – Wrap-Up (Dr. Neil Jacobs, NOAA) Office of the Federal Coordinator for Meteorology Services and Supporting Research 2 FCMSSR Action Items AI # Text Office Comment Status Due Date Responsible 2017-2.1 Reconvene JAG/ICAWS to OFCM, • JAG/ICAWS convened. Working 04/30/18 develop options to broaden FCMSSR • Options presented to FCMSSR Chairmanship beyond Agencies ICMSSR the Undersecretary of Commerce • then FCMSSR with a for Oceans and Atmosphere. revised Charter Draft a modified FCMSSR • Draft Charter reviewed charter to include ICAWS duties by ICMSSR. as outlined in Section 402 of the • Pending FCMSSR and Weather Research and Forecasting OSTP approval to Innovation Act of 2017 and secure finalize Charter for ICMSSR concurrence. signature. Recommend new due date: 30 June 2018. 2017-2.2 Publish the Strategic Plan for OFCM 1/12/18: Plan published on Closed 11/03/17 Federal Weather Coordination as OFCM website presented during the 24 October 2017 FCMMSR Meeting.
    [Show full text]