How Supercomputer Performance and Power Efficiency Can Coexist
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File System and Power Management Enhanced for Supercomputer Fugaku
File System and Power Management Enhanced for Supercomputer Fugaku Hideyuki Akimoto Takuya Okamoto Takahiro Kagami Ken Seki Kenichirou Sakai Hiroaki Imade Makoto Shinohara Shinji Sumimoto RIKEN and Fujitsu are jointly developing the supercomputer Fugaku as the successor to the K computer with a view to starting public use in FY2021. While inheriting the software assets of the K computer, the plan for Fugaku is to make improvements, upgrades, and functional enhancements in various areas such as computational performance, efficient use of resources, and ease of use. As part of these changes, functions in the file system have been greatly enhanced with a focus on usability in addition to improving performance and capacity beyond that of the K computer. Additionally, as reducing power consumption and using power efficiently are issues common to all ultra-large-scale computer systems, power management functions have been newly designed and developed as part of the up- grading of operations management software in Fugaku. This article describes the Fugaku file system featuring significantly enhanced functions from the K computer and introduces new power management functions. 1. Introduction application development environment are taken up in RIKEN and Fujitsu are developing the supercom- separate articles [1, 2], this article focuses on the file puter Fugaku as the successor to the K computer and system and operations management software. The are planning to begin public service in FY2021. file system provides a high-performance and reliable The Fugaku is composed of various kinds of storage environment for application programs and as- system software for supporting the execution of su- sociated data. -
Arm Arhitektura Napreduje – No Postoje Izazovi
ARM ARHITEKTURA NAPREDUJE – NO POSTOJE IZAZOVI SAŽETAK Procesori ARM ISA arhitekture ne koriste se više "samo" za mobitele i tablete, nego i za serverska računala (pa i superračunala), te laptop / desktop računala. I Apple je kod Macintosh računala prešao sa Intel arhitekture na ARM arhitekturu. Veliki izazov kod tog prelaska bio je - kako omogućiti da se programski kod pisan za Intelovu ISA arhitekturu, izvršava na procesoru M1 koji ima ARM arhitekturu. Općenito, želja je da se programi pisani za jednu ISA arhitekturu mogu sa što manje napora izvršavati na računalima koja imaju drugačiju ISA arhitekturu. Problem je u tome što različite ISA arhitekture mogu imati dosta različite memorijske modele. ABSTRACT ARM ISA processors are no longer used "only" for mobile phones and tablets, but also for server computers (even supercomputers) and laptops / desktops. Apple has also switched from Intel to ARM on Macintosh computers. The big challenge in that transition was - how to enable program code written for Intel's ISA architecture to run on an M1 processor that has an ARM architecture. In general, the desire is that programs written for one ISA architecture can be executed with as little effort as possible on computers that have a different ISA architecture. The problem is that different ISA architectures can have quite different memory models. 1. UVOD Procesori ARM ISA arhitekture ne koriste se više "samo" za mobitele i tablete, nego i za serverska računala (pa i superračunala), te laptop/desktop računala. Koriste se i u industriji, u proizvodnim procesima, a i kao ugradbeni čipovi u ostale proizvode, npr. za ugradnju u IOT uređaje i u vozila (posebno autonomna vozila). -
Installation and Upgrade General Checklist Report
VeritasTM Services and Operations Readiness Tools Installation and Upgrade Checklist Report for InfoScale Storage 7.3.1, Solaris 11, SPARC Index Back to top Important Notes Components for InfoScale System requirements Product features Product documentation Patches for InfoScale Storage and Platform Platform configuration Host bus adapter (HBA) parameters and switch parameters Operations Manager Array Support Libraries (ASLs) Additional tasks to consider Important Notes Back to top Note: You have not selected the latest product version. Consider installing or upgrading to the latest version; otherwise, you may encounter issues that have already been fixed. To run a new report for the latest product version, select it from the Veritas product drop-down list. Array Support Libraries (ASLs) When installing Veritas products, please be aware that ASLs updates are not included in the patches update bundle. Please go to the Array Support Libraries (ASLs) to get the latest updates for your disk arrays. Components for InfoScale Back to top The InfoScale product you selected contains the following component(s). Dynamic Multi-Pathing Storage Foundation Storage Foundation Cluster File System Get more introduction of Veritas InfoScale. System requirements Back to top Required CPU number and memory: Required number of CPUs Required memory SF or SFHA N/A 2GB SFCFS or SFCFSHA 2 2GB 1 of 11 VeritasTM Services and Operations Readiness Tools Required disk space: Partitions Minimum space required Maximum space required Recommended space /opt 99 MB 1051 MB 134 MB /root 1 MB 30 MB 1 MB /usr 3 MB 237 MB 3 MB /var 1 MB 1 MB 1 MB Supported architectures: SPARC M5 series [1] SPARC M6 series [1] SPARC M7 series [1][2] SPARC S7 series [1] SPARC T3 series [1] SPARC T4 series [1] SPARC T5 series [1] SPARC T7 series [1][2] SPARC T8 series [1][2] SPARC64 X+ series [1] SPARC64 XII series [1] SPARC64-V series SPARC64-VI series SPARC64-VII/VII+ series SPARC64-X series [1] UltraSPARC II series UltraSPARC III series UltraSPARC IV series UltraSPARC T1 series [1] UltraSPARC T2/T2+ series [1] 1. -
BDEC2 Poznan Japanese HPC Infrastructure Update
BDEC2 Poznan Japanese HPC Infrastructure Update Presenter: Masaaki Kondo, Riken R-CCS/Univ. of Tokyo (on behalf of Satoshi Matsuoka, Director, Riken R-CCS) 1 Post-K: The Game Changer (2020) 1. Heritage of the K-Computer, HP in simulation via extensive Co-Design • High performance: up to x100 performance of K in real applications • Multitudes of Scientific Breakthroughs via Post-K application programs • Simultaneous high performance and ease-of-programming 2. New Technology Innovations of Post-K Global leadership not just in High Performance, esp. via high memory BW • the machine & apps, but as Performance boost by “factors” c.f. mainstream CPUs in many HPC & Society5.0 apps via BW & Vector acceleration cutting edge IT • Very Green e.g. extreme power efficiency Ultra Power efficient design & various power control knobs • Arm Global Ecosystem & SVE contribution Top CPU in ARM Ecosystem of 21 billion chips/year, SVE co- design and world’s first implementation by Fujitsu High Perf. on Society5.0 apps incl. AI • ARM: Massive ecosystem Architectural features for high perf on Society 5.0 apps from embedded to HPC based on Big Data, AI/ML, CAE/EDA, Blockchain security, etc. Technology not just limited to Post-K, but into societal IT infrastructures e.g. Clouds 2 Arm64fx & Post-K (to be renamed) Fujitsu-Riken design A64fx ARM v8.2 (SVE), 48/52 core CPU HPC Optimized: Extremely high package high memory BW (1TByte/s), on-die Tofu-D network BW (~400Gbps), high SVE FLOPS (~3Teraflops), various AI support (FP16, INT8, etc.) Gen purpose CPU – Linux, -
Supercomputer Fugaku
Supercomputer Fugaku Toshiyuki Shimizu Feb. 18th, 2020 FUJITSU LIMITED Copyright 2020 FUJITSU LIMITED Outline ◼ Fugaku project overview ◼ Co-design ◼ Approach ◼ Design results ◼ Performance & energy consumption evaluation ◼ Green500 ◼ OSS apps ◼ Fugaku priority issues ◼ Summary 1 Copyright 2020 FUJITSU LIMITED Supercomputer “Fugaku”, formerly known as Post-K Focus Approach Application performance Co-design w/ application developers and Fujitsu-designed CPU core w/ high memory bandwidth utilizing HBM2 Leading-edge Si-technology, Fujitsu's proven low power & high Power efficiency performance logic design, and power-controlling knobs Arm®v8-A ISA with Scalable Vector Extension (“SVE”), and Arm standard Usability Linux 2 Copyright 2020 FUJITSU LIMITED Fugaku project schedule 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Fugaku development & delivery Manufacturing, Apps Basic Detailed design & General Feasibility study Installation review design Implementation operation and Tuning Select Architecture & Co-Design w/ apps groups apps sizing 3 Copyright 2020 FUJITSU LIMITED Fugaku co-design ◼ Co-design goals ◼ Obtain the best performance, 100x apps performance than K computer, within power budget, 30-40MW • Design applications, compilers, libraries, and hardware ◼ Approach ◼ Estimate perf & power using apps info, performance counts of Fujitsu FX100, and cycle base simulator • Computation time: brief & precise estimation • Communication time: bandwidth and latency for communication w/ some attributes for communication patterns • I/O time: ◼ Then, optimize apps/compilers etc. and resolve bottlenecks ◼ Estimation of performance and power ◼ Precise performance estimation for primary kernels • Make & run Fugaku objects on the Fugaku cycle base simulator ◼ Brief performance estimation for other sections • Replace performance counts of FX100 w/ Fugaku params: # of inst. commit/cycle, wait cycles of barrier, inst. -
Fujitsu's Vision for High Performance Computing
FujitsuFujitsu’’ss VisionVision forfor HighHigh PerformancePerformance ComputingComputing October 26, 2004 Yuji Oinaga Fujitsu Ltd. 1 CONTENTSCONTENTS HPC Policy and Concept Current HPC Platform HPC2500 IA-Cluster Major HPC customers Road Map Toward Peta-Scale Computing 2 FUJITSUFUJITSU HPCHPC PolicyPolicy ~ Developing & Providing Top Level Supercomputer ~ - High Computational Power - High Speed Interconnect - Reliability/Availability - Leading Edge Semiconductor Technology - Highly Reliable, HPC Featured Operating System & Middleware - Sophisticated Compilers and Development Tools 3 HistoryHistory ofof HPCHPC PlatformPlatform PRIMEPOWER HPC2500 VPP5000 Vector Parallel VPP300/700 IA32/IPF Cluster PRIMEPOWER VPP500 2000 Vector VP2000 AP3000 VP Series AP1000 F230-75APU Scalar 1980 1985 1990 1995 2000 2005 4 ConceptConcept ofof FujitsuFujitsu HPCHPC ProvideProvide thethe best/fastestbest/fastest platformplatform forfor eacheach applications.applications. -Scalar SMP : PRIMEPOWER, New Linux SMP -IA Cluster : PRIMERGY Cluster ProvideProvide thethe highhigh speedspeed interconnect.interconnect. -Crossbar : High Speed Optical Interconnect -Multi-Stage : Infiniband ProvideProvide HighHigh Operability/UsabilityOperability/Usability -Enhancement of Operability/Usability : Extended Partitioning, Dynamic Reconfiguration -Cluster Middleware : Total Cluster Control System ( Parallelnavi ) Shared Rapid File System ( SRFS ) 5 FujitsuFujitsu’’ss CurrentCurrent HPCHPC PlatformPlatform ~ Fujitsu is a leading edge company in HPC field ~ SPARC/Solaris -
Download SC18 Final Program
Program November 11-16, 2018 The International Conference Exhibits November 12-15, 2018 for High Performance KAY BAILEY HUTCHISON CONVENTION CENTER Computing, Networking, DALLAS, TEXAS, USA Storage, and Analysis Sponsored by: MICHAEL S. RAWLINGS Mayor of Dallas November 11, 2018 Supercomputing – SC18 Conference: As Mayor of Dallas, it is my pleasure to welcome SC18 – the ultimate international conference for high performance computing, networking, storage, and analysis – to the Kay Bailey Hutchison Convention Center! I applaud SC18 for bringing together high-performance computing (HPC) professionals and students from across the globe to share ideas, attend and participate in technical presentations, papers and workshops, all while inspiring the next generation of HPC professionals. Dallas is the No. 1 visitor destination in Texas and one of the top cities in the nation for meetings and conventions. In addition to having the resources to host major events and conventions, Dallas is a greatly diverse American city and a melting pot of cultures. This important convergence of uniqueness and differences is reflected throughout the sights and sounds of our city. Dallas' authentic arts, music, food, historic landmarks and urban lifestyle all contribute to the city's rich cultural makeup. Let the bold, vibrant spirit of Dallas, with a touch of Texas charm, guide the way to your BIG Dallas moments. Our city is filled with the unique experiences one can only have in Dallas – from cuisine by celebrity chefs, to the cultural landscape in one of the nation’s largest arts districts, to first-class shopping - make the most of your time in our great city! From transportation to hotels, restaurants, retail and entertainment venues, Dallas is ready to roll out our red carpet to host SC18. -
Mixed Precision Block Fused Multiply-Add
Mixed Precision Block Fused Multiply-Add: Error Analysis and Application to GPU Tensor Cores Pierre Blanchard, Nicholas Higham, Florent Lopez, Théo Mary, Srikara Pranesh To cite this version: Pierre Blanchard, Nicholas Higham, Florent Lopez, Théo Mary, Srikara Pranesh. Mixed Precision Block Fused Multiply-Add: Error Analysis and Application to GPU Tensor Cores. SIAM Journal on Scientific Computing, Society for Industrial and Applied Mathematics, 2020, 42 (3), pp.C124-C141. 10.1137/19M1289546. hal-02491076v2 HAL Id: hal-02491076 https://hal.archives-ouvertes.fr/hal-02491076v2 Submitted on 28 May 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. MIXED PRECISION BLOCK FUSED MULTIPLY-ADD: ERROR ANALYSIS AND APPLICATION TO GPU TENSOR CORES∗ PIERRE BLANCHARDy , NICHOLAS J. HIGHAMz , FLORENT LOPEZx , THEO MARY{, AND SRIKARA PRANESHk Abstract. Computing units that carry out a fused multiply-add (FMA) operation with matrix arguments, referred to as tensor units by some vendors, have great potential for use in scientific computing. However, these units are inherently mixed precision and existing rounding error analyses do not support them. We consider a mixed precision block FMA that generalizes both the usual scalar FMA and existing tensor units. -
Computer Architectures an Overview
Computer Architectures An Overview PDF generated using the open source mwlib toolkit. See http://code.pediapress.com/ for more information. PDF generated at: Sat, 25 Feb 2012 22:35:32 UTC Contents Articles Microarchitecture 1 x86 7 PowerPC 23 IBM POWER 33 MIPS architecture 39 SPARC 57 ARM architecture 65 DEC Alpha 80 AlphaStation 92 AlphaServer 95 Very long instruction word 103 Instruction-level parallelism 107 Explicitly parallel instruction computing 108 References Article Sources and Contributors 111 Image Sources, Licenses and Contributors 113 Article Licenses License 114 Microarchitecture 1 Microarchitecture In computer engineering, microarchitecture (sometimes abbreviated to µarch or uarch), also called computer organization, is the way a given instruction set architecture (ISA) is implemented on a processor. A given ISA may be implemented with different microarchitectures.[1] Implementations might vary due to different goals of a given design or due to shifts in technology.[2] Computer architecture is the combination of microarchitecture and instruction set design. Relation to instruction set architecture The ISA is roughly the same as the programming model of a processor as seen by an assembly language programmer or compiler writer. The ISA includes the execution model, processor registers, address and data formats among other things. The Intel Core microarchitecture microarchitecture includes the constituent parts of the processor and how these interconnect and interoperate to implement the ISA. The microarchitecture of a machine is usually represented as (more or less detailed) diagrams that describe the interconnections of the various microarchitectural elements of the machine, which may be everything from single gates and registers, to complete arithmetic logic units (ALU)s and even larger elements. -
Programming on K Computer
Programming on K computer Koh Hotta The Next Generation Technical Computing Fujitsu Limited Copyright 2010 FUJITSU LIMITED System Overview of “K computer” Target Performance : 10PF over 80,000 processors Over 640K cores Over 1 Peta Bytes Memory Cutting-edge technologies CPU : SPARC64 VIIIfx 8 cores, 128GFlops Extension of SPARC V9 Interconnect, “Tofu” : 6-D mesh/torus Parallel programming environment. 1 Copyright 2010 FUJITSU LIMITED I have a dream that one day you just compile your programs and enjoy high performance on your high-end supercomputer. So, we must provide easy hybrid parallel programming method including compiler and run-time system support. 2 Copyright 2010 FUJITSU LIMITED User I/F for Programming for K computer K computer Client System FrontFront End End BackBack End End (80000 (80000 Nodes) Nodes) IDE Interface CCommommandand JobJob C Controlontrol IDE IntInteerfrfaceace debugger DDebugebuggerger App IntInteerfrfaceace App Interactive Debugger GUI Data Data Data CoConvnveerrtteerr Data SamplSampleerr debugging partition official op VisualizedVisualized SSaammpplingling Stage out partition Profiler DaDattaa DaDattaa (InfiniBand) 3 Copyright 2010 FUJITSU LIMITED Parallel Programming 4 Copyright 2010 FUJITSU LIMITED Hybrid Parallelism on over-640K cores Too large # of processes to manipulate To reduce number of processes, hybrid thread-process programming is required But Hybrid parallel programming is annoying for programmers Even for multi-threading, procedure level or outer loop parallelism was desired Little opportunity for such coarse grain parallelism System support for “fine grain” parallelism is required 5 Copyright 2010 FUJITSU LIMITED Targeting inner-most loop parallelization Automatic vectorization technology has become mature, and vector-tuning is easy for programmers. Inner-most loop parallelism, which is fine-grain, should be an important portion for peta-scale parallelization. -
HPC Systems in the Next Decade – What to Expect, When, Where
EPJ Web of Conferences 245, 11004 (2020) https://doi.org/10.1051/epjconf/202024511004 CHEP 2019 HPC Systems in the Next Decade – What to Expect, When, Where Dirk Pleiter1;∗ 1Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany Abstract. HPC systems have seen impressive growth in terms of performance over a period of many years. Soon the next milestone is expected to be reached with the deployment of exascale systems in 2021. In this paper, we provide an overview of the exascale challenges from a computer architecture’s perspec- tive and explore technological and other constraints. The analysis of upcoming architectural options and emerging technologies allow for setting expectations for application developers, which will have to cope with heterogeneous archi- tectures, increasingly diverse compute technologies as well as deeper memory and storage hierarchies. Finally, needs resulting from changing science and en- gineering workflows will be discussed, which need to be addressed by making HPC systems available as part of more open e-infrastructures that provide also other compute and storage services. 1 Introduction Over several decades, high-performance computing (HPC) has seen an exponential growth of performance when solving large-scale numerical problems involving dense-matrix opera- tions. This development is well documented by the Top500 list [1], which is published twice a year since 1993. In various regions around the world, significant efforts are being per- formed to reach the next milestone of performance with the deployment of exascale systems. For various reasons, improving on the performance of HPC systems has become increasingly more difficult. In this paper, we discuss some of the reasons. -
Microprocessor
MICROPROCESSOR www.MPRonline.com THE REPORTINSIDER’S GUIDE TO MICROPROCESSOR HARDWARE FUJITSU’S SPARC64 V IS REAL DEAL Fujitsu’s design differs from HAL’s version; faster than US III By Kevin Krewell {10/21/02-01} At Microprocessor Forum 2002, Fujitsu stepped forward to carry the banner for the fastest SPARC processor, surpassing Sun’s fastest UltraSPARC III on clock frequency and SPEC performance. In fact, at 1.35GHz, the Fujitsu processor has the highest clock frequency of any 64-bit server processor now in production. This by a Fujitsu acquisition, HAL Computer. At Micro- clock-speed advantage—plus large on-chip processor Forum 1999, Mike Shebanow, then vice caches; a fast system-crossbar switch; and a four- president and CTO of the HAL Computer Divi- issue, out-of-order core—translates into good sion of Fujitsu, proposed a complex and very wide SPEC benchmark performance for Fujitsu’s superscalar version of the SPARC64 V processor, SPARC64 V processor. The SPARC64 V is an evo- with an instruction trace cache, superspeculation, lutionary step in Fujitsu’s SPARC processor line and split L2 cache (see MPR 11/15/99-01,“Hal instead of the more-radical approach proposed three Makes Sparcs Fly”). Mike’s innovative chip never made years ago by HAL Computer at Microprocessor Forum it to market, but the trace-cache idea became a mainstream 1999. This latest version of Fujitsu’s SPARC processor fam- processor feature, shipping in Intel’s Pentium 4 microarchi- ily, revealed by Fujitsu’s director of Development Depart- tecture. The Pentium 4 also paralleled another of Mike’s ment (Processor Development Division) Aiichiro Inoue, is based on an enhanced version of the previous SPARC64 GP processor core, with larger caches and advanced semicon- L1I$ Decode & FP (16) L1D$ L2$ 128KB I-buffer Issue (4) SP (10) 128KB 2MB ductor process technology.