CFD) Applications on HPC Systems
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The Reliability Wall for Exascale Supercomputing Xuejun Yang, Member, IEEE, Zhiyuan Wang, Jingling Xue, Senior Member, IEEE, and Yun Zhou
. IEEE TRANSACTIONS ON COMPUTERS, VOL. *, NO. *, * * 1 The Reliability Wall for Exascale Supercomputing Xuejun Yang, Member, IEEE, Zhiyuan Wang, Jingling Xue, Senior Member, IEEE, and Yun Zhou Abstract—Reliability is a key challenge to be understood to turn the vision of exascale supercomputing into reality. Inevitably, large-scale supercomputing systems, especially those at the peta/exascale levels, must tolerate failures, by incorporating fault- tolerance mechanisms to improve their reliability and availability. As the benefits of fault-tolerance mechanisms rarely come without associated time and/or capital costs, reliability will limit the scalability of parallel applications. This paper introduces for the first time the concept of “Reliability Wall” to highlight the significance of achieving scalable performance in peta/exascale supercomputing with fault tolerance. We quantify the effects of reliability on scalability, by proposing a reliability speedup, defining quantitatively the reliability wall, giving an existence theorem for the reliability wall, and categorizing a given system according to the time overhead incurred by fault tolerance. We also generalize these results into a general reliability speedup/wall framework by considering not only speedup but also costup. We analyze and extrapolate the existence of the reliability wall using two representative supercomputers, Intrepid and ASCI White, both employing checkpointing for fault tolerance, and have also studied the general reliability wall using Intrepid. These case studies provide insights on how to mitigate reliability-wall effects in system design and through hardware/software optimizations in peta/exascale supercomputing. Index Terms—fault tolerance, exascale, performance metric, reliability speedup, reliability wall, checkpointing. ! 1INTRODUCTION a revolution in computing at a greatly accelerated pace [2]. -
March 11, 2010 Presentation
IBM Power Systems POWER7TM Announcement, The Next Generation of Power Systems Power your planet. February 25, 2010 IBM Power Systems 2 February 25, 2010 IBM Power Systems POWER7 System Highlights .Balance System Design - Cache, Memory, and IO .POWER7 Processor Technology - 6th Implementation of multi-core design - On chip L2 & L3 caches .POWER7 System Architecture - Blades to High End offerings - Enhances memory implementation - PCIe, SAS / SATA .Built in Virtualization - Memory Expansion - VM Control .Green Technologies - Processor Nap & Sleep Mode - Memory Power Down support - Aggressive Power Save / Capping Modes 600 500 .Availability 400 - Processor Instruction Retry 300 - Alternate Process Recovery 200 100 - Concurrent Add & Services 0 JS23 JS43 520 550 560 570/16 570/32 595 3 February 25, 2010 IBM Power Systems 4 February 25, 2010 IBM Power Systems Power Processor Technology IBM investment in the Power Franchise Dependable Execution for a decade POWER8 POWER7 45 nm Globalization and globally POWER6 available resources 65 nm •Performance/System Capacity POWER5 •4-5X increase from Power6 130 nm •Multi Core – Up to 8 POWER4 •SMT4 – 4 threads/core 180 nm . Dual Core •On-Chip eDRAM . High Frequencies • Energy . Dual Core . Virtualization + . Enhanced Scaling • Efficiency: 3-4X Power6 . Memory Subsystem + . SMT • Dynamic Energy . Dual Core . Altivec . Distributed Switch + Management . Chip Multi Processing . Instruction Retry . Distributed Switch . Core Parallelism + • Reliability + . Dyn Energy Mgmt . Shared L2 . FP Performance + . SMT + •Memory DIMM – DRAM . Dynamic LPARs (32) . Memory bandwidth + . Protection Keys Sparing . Virtualization •N+2 Voltage Regulator Redundancy •Protection Keys + 5 February 25, 2010 IBM Power Systems POWER6 – POWER7 Compare Wireless world Mobile platforms are developing as new means of identification. -
POWER® Processor-Based Systems
IBM® Power® Systems RAS Introduction to IBM® Power® Reliability, Availability, and Serviceability for POWER9® processor-based systems using IBM PowerVM™ With Updates covering the latest 4+ Socket Power10 processor-based systems IBM Systems Group Daniel Henderson, Irving Baysah Trademarks, Copyrights, Notices and Acknowledgements Trademarks IBM, the IBM logo, and ibm.com are trademarks or registered trademarks of International Business Machines Corporation in the United States, other countries, or both. These and other IBM trademarked terms are marked on their first occurrence in this information with the appropriate symbol (® or ™), indicating US registered or common law trademarks owned by IBM at the time this information was published. Such trademarks may also be registered or common law trademarks in other countries. A current list of IBM trademarks is available on the Web at http://www.ibm.com/legal/copytrade.shtml The following terms are trademarks of the International Business Machines Corporation in the United States, other countries, or both: Active AIX® POWER® POWER Power Power Systems Memory™ Hypervisor™ Systems™ Software™ Power® POWER POWER7 POWER8™ POWER® PowerLinux™ 7® +™ POWER® PowerHA® POWER6 ® PowerVM System System PowerVC™ POWER Power Architecture™ ® x® z® Hypervisor™ Additional Trademarks may be identified in the body of this document. Other company, product, or service names may be trademarks or service marks of others. Notices The last page of this document contains copyright information, important notices, and other information. Acknowledgements While this whitepaper has two principal authors/editors it is the culmination of the work of a number of different subject matter experts within IBM who contributed ideas, detailed technical information, and the occasional photograph and section of description. -
Openpower AI CERN V1.Pdf
Moore’s Law Processor Technology Firmware / OS Linux Accelerator sSoftware OpenStack Storage Network ... Price/Performance POWER8 2000 2020 DRAM Memory Chips Buffer Power8: Up to 12 Cores, up to 96 Threads L1, L2, L3 + L4 Caches Up to 1 TB per socket https://www.ibm.com/blogs/syst Up to 230 GB/s sustained memory ems/power-systems- openpower-enable- bandwidth acceleration/ System System Memory Memory 115 GB/s 115 GB/s POWER8 POWER8 CPU CPU NVLink NVLink 80 GB/s 80 GB/s P100 P100 P100 P100 GPU GPU GPU GPU GPU GPU GPU GPU Memory Memory Memory Memory GPU PCIe CPU 16 GB/s System bottleneck Graphics System Memory Memory IBM aDVantage: data communication and GPU performance POWER8 + 78 ms Tesla P100+NVLink x86 baseD 170 ms GPU system ImageNet / Alexnet: Minibatch size = 128 ADD: Coherent Accelerator Processor Interface (CAPI) FPGA CAPP PCIe POWER8 Processor ...FPGAs, networking, memory... Typical I/O MoDel Flow Copy or Pin MMIO Notify Poll / Int Copy or Unpin Ret. From DD DD Call Acceleration Source Data Accelerator Completion Result Data Completion Flow with a Coherent MoDel ShareD Mem. ShareD Memory Acceleration Notify Accelerator Completion Focus on Enterprise Scale-Up Focus on Scale-Out and Enterprise Future Technology and Performance DriVen Cost and Acceleration DriVen Partner Chip POWER6 Architecture POWER7 Architecture POWER8 Architecture POWER9 Architecture POWER10 POWER8/9 2007 2008 2010 2012 2014 2016 2017 TBD 2018 - 20 2020+ POWER6 POWER6+ POWER7 POWER7+ POWER8 POWER8 P9 SO P9 SU P9 SO 2 cores 2 cores 8 cores 8 cores 12 cores w/ NVLink -
LLNL Computation Directorate Annual Report (2014)
PRODUCTION TEAM LLNL Associate Director for Computation Dona L. Crawford Deputy Associate Directors James Brase, Trish Damkroger, John Grosh, and Michel McCoy Scientific Editors John Westlund and Ming Jiang Art Director Amy Henke Production Editor Deanna Willis Writers Andrea Baron, Rose Hansen, Caryn Meissner, Linda Null, Michelle Rubin, and Deanna Willis Proofreader Rose Hansen Photographer Lee Baker LLNL-TR-668095 3D Designer Prepared by LLNL under Contract DE-AC52-07NA27344. Ryan Chen This document was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, Print Production manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or Lawrence Livermore National Security, LLC. The views and opinions of authors expressed herein do not necessarily state or reflect those of the Charlie Arteago, Jr., and Monarch Print Copy and Design Solutions United States government or Lawrence Livermore National Security, LLC, and shall not be used for advertising or product endorsement purposes. CONTENTS Message from the Associate Director . 2 An Award-Winning Organization . 4 CORAL Contract Awarded and Nonrecurring Engineering Begins . 6 Preparing Codes for a Technology Transition . 8 Flux: A Framework for Resource Management . -
IBM Power Systems Performance Report Apr 13, 2021
IBM Power Performance Report Power7 to Power10 September 8, 2021 Table of Contents 3 Introduction to Performance of IBM UNIX, IBM i, and Linux Operating System Servers 4 Section 1 – SPEC® CPU Benchmark Performance 4 Section 1a – Linux Multi-user SPEC® CPU2017 Performance (Power10) 4 Section 1b – Linux Multi-user SPEC® CPU2017 Performance (Power9) 4 Section 1c – AIX Multi-user SPEC® CPU2006 Performance (Power7, Power7+, Power8) 5 Section 1d – Linux Multi-user SPEC® CPU2006 Performance (Power7, Power7+, Power8) 6 Section 2 – AIX Multi-user Performance (rPerf) 6 Section 2a – AIX Multi-user Performance (Power8, Power9 and Power10) 9 Section 2b – AIX Multi-user Performance (Power9) in Non-default Processor Power Mode Setting 9 Section 2c – AIX Multi-user Performance (Power7 and Power7+) 13 Section 2d – AIX Capacity Upgrade on Demand Relative Performance Guidelines (Power8) 15 Section 2e – AIX Capacity Upgrade on Demand Relative Performance Guidelines (Power7 and Power7+) 20 Section 3 – CPW Benchmark Performance 19 Section 3a – CPW Benchmark Performance (Power8, Power9 and Power10) 22 Section 3b – CPW Benchmark Performance (Power7 and Power7+) 25 Section 4 – SPECjbb®2015 Benchmark Performance 25 Section 4a – SPECjbb®2015 Benchmark Performance (Power9) 25 Section 4b – SPECjbb®2015 Benchmark Performance (Power8) 25 Section 5 – AIX SAP® Standard Application Benchmark Performance 25 Section 5a – SAP® Sales and Distribution (SD) 2-Tier – AIX (Power7 to Power8) 26 Section 5b – SAP® Sales and Distribution (SD) 2-Tier – Linux on Power (Power7 to Power7+) -
Biomolecular Simulation Data Management In
BIOMOLECULAR SIMULATION DATA MANAGEMENT IN HETEROGENEOUS ENVIRONMENTS Julien Charles Victor Thibault A dissertation submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Biomedical Informatics The University of Utah December 2014 Copyright © Julien Charles Victor Thibault 2014 All Rights Reserved The University of Utah Graduate School STATEMENT OF DISSERTATION APPROVAL The dissertation of Julien Charles Victor Thibault has been approved by the following supervisory committee members: Julio Cesar Facelli , Chair 4/2/2014___ Date Approved Thomas E. Cheatham , Member 3/31/2014___ Date Approved Karen Eilbeck , Member 4/3/2014___ Date Approved Lewis J. Frey _ , Member 4/2/2014___ Date Approved Scott P. Narus , Member 4/4/2014___ Date Approved And by Wendy W. Chapman , Chair of the Department of Biomedical Informatics and by David B. Kieda, Dean of The Graduate School. ABSTRACT Over 40 years ago, the first computer simulation of a protein was reported: the atomic motions of a 58 amino acid protein were simulated for few picoseconds. With today’s supercomputers, simulations of large biomolecular systems with hundreds of thousands of atoms can reach biologically significant timescales. Through dynamics information biomolecular simulations can provide new insights into molecular structure and function to support the development of new drugs or therapies. While the recent advances in high-performance computing hardware and computational methods have enabled scientists to run longer simulations, they also created new challenges for data management. Investigators need to use local and national resources to run these simulations and store their output, which can reach terabytes of data on disk. -
System Automation for Z/OS : Planning and Installation About This Publication
System Automation for z/OS Version 4.Release 1 Planning and Installation IBM SC34-2716-01 Note Before using this information and the product it supports, read the information in Appendix H, “Notices,” on page 201. Edition Notes This edition applies to IBM System Automation for z/OS® (Program Number 5698-SA4) Version 4 Release 1, an IBM licensed program, and to all subsequent releases and modifications until otherwise indicated in new editions. This edition replaces SC34-2716-00. © Copyright International Business Machines Corporation 1996, 2017. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents Figures................................................................................................................. xi Tables................................................................................................................ xiii Accessibility........................................................................................................ xv Using assistive technologies...................................................................................................................... xv Keyboard navigation of the user interface................................................................................................. xv About this publication........................................................................................ xvii Who Should Use This Publication.............................................................................................................xvii -
Measuring Power Consumption on IBM Blue Gene/P
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Springer - Publisher Connector Comput Sci Res Dev DOI 10.1007/s00450-011-0192-y SPECIAL ISSUE PAPER Measuring power consumption on IBM Blue Gene/P Michael Hennecke · Wolfgang Frings · Willi Homberg · Anke Zitz · Michael Knobloch · Hans Böttiger © The Author(s) 2011. This article is published with open access at Springerlink.com Abstract Energy efficiency is a key design principle of the Top10 supercomputers on the November 2010 Top500 list IBM Blue Gene series of supercomputers, and Blue Gene [1] alone (which coincidentally are also the 10 systems with systems have consistently gained top GFlops/Watt rankings an Rpeak of at least one PFlops) are consuming a total power on the Green500 list. The Blue Gene hardware and man- of 33.4 MW [2]. These levels of power consumption are al- agement software provide built-in features to monitor power ready a concern for today’s Petascale supercomputers (with consumption at all levels of the machine’s power distribu- operational expenses becoming comparable to the capital tion network. This paper presents the Blue Gene/P power expenses for procuring the machine), and addressing the measurement infrastructure and discusses the operational energy challenge clearly is one of the key issues when ap- aspects of using this infrastructure on Petascale machines. proaching Exascale. We also describe the integration of Blue Gene power moni- While the Flops/Watt metric is useful, its emphasis on toring capabilities into system-level tools like LLview, and LINPACK performance and thus computational load ne- highlight some results of analyzing the production workload glects the fact that the energy costs of memory references at Research Center Jülich (FZJ). -
Upgrade to POWER9 Planning Checklist
Achieve your full business potential with IBM POWER9 Future-forward infrastructure designed to crush data-intensive workloads Upgrade to POWER9 Planning Checklist Using this checklist will help to ensure that your infrastructure strategy is aligned to your needs, avoiding potential cost overruns or capability shortfalls. 1 Determine current and future capacity 5 Identify all dependencies for major database requirements. Bring your team together, platforms, including Oracle, DB2, SAP HANA, assess your current application workload and open-source databases like EnterpriseDB, requirements and three- to five-year MongoDB, neo4j, and Redis. You’re likely outlook. You’ll then have a good picture running major databases on the Power of when and where application growth Systems platform; co-locating your current will take place, enabling you to secure servers may be a way to reduce expenditure capacity at the appropriate time on an and increase flexibility. as-needed basis. 6 Understand current and future data center 2 Assess operational efficiencies and identify environmental requirements. You may be opportunities to improve service levels unnecessarily overspending on power, while decreasing exposure to security and cooling and space. Savings here will help your compliancy issues/problems. With new organization avoid costs associated with data technologies that allow you to easily adjust center expansion. capacity, you will be in a much better position to lower costs, improve service Identify the requirements of your strategy for levels, and increase efficiency. 7 on- and off-premises cloud infrastructure. As you move to the cloud, ensure you 3 Create a detailed inventory of servers have a strong strategy to determine which across your entire IT infrastructure. -
Power8 Quser Mspl Nov 2015 Handout
IBM Power Systems Power Systems Hardware: Today and Tomorrow November 2015 Mark Olson [email protected] © 2015 IBM Corporation IBM Power Systems POWER8 Chip © 2015 IBM Corporation IBM Power Systems Processor Technology Roadmap POWER11 Or whatever it is POWER10 named Or whatever it is POWER9 named Or whatever it is named POWER7 POWER8 POWER6 45 nm 22 nm POWER5 65 nm 130 nm POWER4 90 nm 180 nm 130 nm 2001 2004 2007 2010 2014 Future 3 © 2015 IBM Corporation IBM Power Systems Processor Chip Comparisons POWER5 POWER6 POWER7 POWER7+ POWER8 2004 2007 2010 2012 45nm SOI 32nm SOI 22nm SOI Technology 130nm SOI 65nm SOI eDRAM eDRAM eDRAM Compute Cores 2 2 8 8 12 Threads SMT2 SMT2 SMT4 SMT4 SMT8 Caching On-chip 1.9MB (L2) 8MB (L2) 2 + 32MB (L2+3) 2 + 80MB (L2+3) 6 + 96MB (L2+3) Off-chip 36MB (L3) 32MB (L3) None None 128MB (L4) Bandwidth Sust. Mem. 15GB/s 30GB/s 100GB/s 100GB/s 230GB/s Peak I/O 6GB/s 20GB/s 40GB/s 40GB/s 96GB/s 4 © 2015 IBM Corporation IBM Power Systems Processor Designs POWER5+ POWER6 POWER7 POWER7+ POWER8 Max cores 4 2 8 8 12 Technology 90nm 65nm 45nm 32nm 22nm Size 245 mm2 341 mm2 567 mm2 567 mm2 650 mm2 * Transistors 276 M 790 M 1.2 B 2.1 B 4.2 B * 1.9 4 - 5 3 – 4 Up to 4.4 Up to 4.1 Frequencies GHz GHz GHz GHz GHz ** SMT (threads) 2 2 4 4 8 L2 Cache 1.9MB Shared 4MB / Core 256KB / core 256KB / core 512KB/core 4MB / Core 10MB / Core 8MB / Core L3 Cache 36MB 32MB On chip On chip On chip L4 Cache -- -- -- -- Up to 128MB Bandwidth Sust memory 15GB/s 30GB/s 100GB/s 100GB/s 230GB/s Peak I/O 6GB/s 20GB/s 40GB/s 40GB/s 96GB/s * with 12-core -
Blue Gene®/Q Overview and Update
Blue Gene®/Q Overview and Update November 2011 Agenda Hardware Architecture George Chiu Packaging & Cooling Paul Coteus Software Architecture Robert Wisniewski Applications & Configurations Jim Sexton IBM System Technology Group Blue Gene/Q 32 Node Board Industrial Design BQC DD2.0 4-rack system 5D torus 3 © 2011 IBM Corporation IBM System Technology Group Top 10 reasons that you need Blue Gene/Q 1. Ultra-scalability for breakthrough science – System can scale to 256 racks and beyond (>262,144 nodes) – Cluster: typically a few racks (512-1024 nodes) or less. 2. Highest capability machine in the world (20-100PF+ peak) 3. Superior reliability: Run an application across the whole machine, low maintenance 4. Highest power efficiency, smallest footprint, lowest TCO (Total Cost of Ownership) 5. Low latency, high bandwidth inter-processor communication system 6. Low latency, high bandwidth memory system 7. Open source and standards-based programming environment – Red Hat Linux distribution on service, front end, and I/O nodes – Lightweight Compute Node Kernel (CNK) on compute nodes ensures scaling with no OS jitter, enables reproducible runtime results – Automatic SIMD (Single-Instruction Multiple-Data) FPU exploitation enabled by IBM XL (Fortran, C, C++) compilers – PAMI (Parallel Active Messaging Interface) runtime layer. Runs across IBM HPC platforms 8. Software architecture extends application reach – Generalized communication runtime layer allows flexibility of programming model – Familiar Linux execution environment with support for most