Performance Comparison of Capability Application Benchmarks on the IBM p5-575 and the Cray XT3. Mike Ashworth
|
|
|
- Andrew Kelly
- 5 years ago
- Views:
Transcription
1 Performance Comparison of Capability Application Benchmarks on the IBM p5-575 and the Cray XT3 Mike Ashworth Computational Science and CCLRC Daresbury Laboratory Warrington UK
2 Abstract The UK s flagship scientific computing service is currently provided by an IBM p5-575 cluster comprising GHz POWER5 processors operated by the HPCx Consortium. The next generation high-performance resource for UK academic computing has recently been announced. The HECToR project (High-End Computing Technology Resource) will be provided with technology from Cray Inc., the system being the followon to the Cray XT3, with a target performance of some Tflop/s. We present initial results of a benchmarking programme to compare the performance of the IBM POWER5 system and the Cray XT3 across a range of capability applications of key importance to UK science. Codes are considered from a diverse section of application domains, including environmental science, molecular simulation and computational engineering. We find a range of performance with some algorithms performing better on one system and some on the other and we use low-level kernel benchmarks and performance analysis tools to examine the underlying causes of the performance.
3 Outline Introduction CCLRC Daresbury Laboratory HPCx A perspective on UK academic HPC provision HECToR a new resource for UK computational science Performance comparison IBM p5-575 vs. Cray XT3 IMB POLCOMS PCHAN DL_POLY3 GAMESS-US Single-core vs. dual-core Conclusions
4 Introduction
5 CCLRC Daresbury Laboratory Home of HPCx 2560-CPU IBM POWER5
6 The HPCx Project Operated by CCLRC Daresbury Laboratory and the University of Edinburgh Located at Daresbury Six year project from November 2002 through to 2008 First Tera-scale academic research computing facility in the UK Funded by the Research Councils: EPSRC, NERC, BBSRC IBM is the technology partner 02 Phase1: 3 Tflops sustained POWER4 cpus + SP Switch 04 Phase2: 6 Tflops sustained POWER4+ cpus + HPS 05 Phase2A: Performance-neutral upgrade to 1536 POWER5 cpus 06 Phase3: 12 Tflops sustained 2560 POWER5 cpus
7 HPCx Phase2A System doubled in size last month Phase processors
8 UK Strategy for HPC Current UK Strategy for HPC Services Funded by the UK Government Office of Science & Technology Managed by EPSRC on behalf of the community Initiate a competitive procurement exercise every 3 years for both the system (hardware and software) and service (accommodation, management and support) Award a 6 year contract for a service Consequently, have 2 overlapping services at any one time The contract to include at least one, typically two, technology upgrades Resources allocated on both national systems through normal peer review process for research grants Virement of resources is allowed e.g. when one of the services has a technology upgrade
9 UK Overlapping Services EPCC T3D T3E Technology Upgrade CSAR T3E Origin Altix HPCx IBM p690 p690+ p5-575 Cray XT4??? HECToR Child of HECToR
10 Total academic provision EPCC T3D/T3E HPCx IBM CSAR SGI
11 Total academic provision + ECMWF
12 Total academic provision + HECToR
13 HECToR and Beyond High End Computing Technology Resource Budget capped at 100M including all costs over 6 years Three phases with performance doubling (like HPCx) Tflop/s, Tflop/s, Tflop/s peak Three separate procurements Hardware technology (Cray are preferred vendor XT4) support (NAG core + distributed support) Accommodation & Management (2 nd tender issued October 2006) Child of HECToR Competition for better name! Possible collaboration with UK Met Office Procurement due mid-2007 Possible HPC Eur: european scale procurement and accommodation
14 All this provides motivation for this talk a Comparison of the Cray XT3 and IBM p5-575 (current vs. future UK provision)
15 Systems under Evaluation Make/Model Ncpus CPU Interconnect Site Cray X1/E 4096 Cray SSP CNS ORNL Cray XT Opteron 2.6 GHz SeaStar CSCS Cray XD1 72 Opteron GHz RapidArray CCLRC IBM 2560 POWER5 1.5 GHz HPS CCLRC SGI 384 Itanium2 1.3 GHz NUMAlink CSAR SGI 128 Itanium2 1.5 GHz NUMAlink CSAR Streamline cluster 256 Opteron GHz Myrinet 2k CCLRC all Opteron systems: used PGI compiler: -O3 fastsse Cray XT3: used small_pages (see Neil Stringfellow s talk on Thursday) Altix: used Intel 7.1 or 8.0 (7.1 faster for PCHAN) IBM: used xlf 9.1 O3 qarch=pwr4 qtune=pwr4
16 Acknowledgements Thanks are due to the following for access to machines Swiss National Supercomputer Centre (CSCS) Neil Stringfellow Oak Ridge National Laboratory (ORNL) Pat Worley (Performance Evaluation Research Center) Engineering and Physical Sciences Research Council (EPSRC) access to CSAR systems HPCx time s DisCo programme (Cray XD1) Council for the Central Laboratories for the Research Councils (CCLRC) SCARF Streamline cluster
17 Kernel benchmarks
18 Intel MPI benchmark 2000 PingPong - Bandwidth Bandwith (MB/s) IBM p5-575 Cray XT Message Length
19 Intel MPI benchmark PingPong - Latency IBM p5-575 Cray XT3 Time (us) Message Length
20 Intel MPI benchmark MPI_AllReduce 128 procs Time (us) Cray XT3 IBM p Message Length (bytes)
21 Intel MPI benchmark MPI_Reduce 128 procs IBM p5-575 Cray XT3 Time (us) Message Length (bytes)
22 Intel MPI benchmark MPI_AllGather 128 procs IBM p5-575 Cray XT3 Time (us) Message Length (bytes)
23 Intel MPI benchmark MPI_AllGatherV 128 procs IBM p5-575 Cray XT3 Time (us) Message Length (bytes)
24 Intel MPI benchmark MPI_AllToAll 128 procs IBM p5-575 Cray XT3 Time (us) Message Length (bytes)
25 Intel MPI benchmark MPI_Bcast 128 procs Time (us) IBM p5-575 Cray XT Message Length (bytes)
26 IMB Summary <<< Cray XT3 worse Cray XT3 better >>> -100% -50% 0% 50% 100% Latency Bandwidth AllReduce Reduce AllGather AllGatherV 32 proc 128 procs AllToAll Bcast 8192 bytes
27 Kernel benchmarks are interesting but it s the application performance that counts
28 Benchmark Applications POLCOMS Proudman Oceanographic Laboratory Coastal Ocean Modelling System Coupled marine ecosystem modelling (ERSEM), also wave modelling (WAM), and sea-ice modelling (CICE) Medium resolution continental shelf model - hydrodynamics alone. PDNS3D UK Turbulence Consortium, led by Southampton University Direct Numerical Simulation of Turbulence T3 channel flow benchmark on a grid 360 x 360 x 360 DL_POLY3 Molecular dynamics code developed at Daresbury Laboratory Macromolecular simulation of 8 Gramicidin-A species (792,960 atoms) GAMESS-US ab initio molecular quantum chemistry SiC 3 benchmark Si n C m clusters of interest in materials science and astronomy
29 POLCOMS Structure Meteorological forcing UKMO Operational forecasting Climatology and extreme statistics Tidal forcing 3D baroclinic hydrodynamic coastal-ocean model ERSEM biology UKMO Ocean model forcing Fish larvae modelling Contaminant modelling Sediment transport and resuspension Visualisation, data banking & high-performance computing
30 POLCOMS code characteristics 3D Shallow Water equations Horizontal finite difference discretization on an Arakawa B-grid Depth following sigma coordinate Piecewise Parabolic Method (PPM) for accurate representation of sharp gradients, fronts, thermoclines etc. Implicit method for vertical diffusion Equations split into depth-mean and depth-fluctuating components Prescribed surface elevation and density at open boundaries Four-point wide relaxation zone Meteorological data are used to calculate wind stress and heat flux Parallelisation 2D horizontal decomposition with recursive bi-section Nearest neighbour comms but low compute/communicate ratio Compute is heavy on memory access with low cache re-use
31 MRCS model Medium-resolution Continental Shelf model (MRCS): 1/10 degree x 1/15 degree grid size is 251 x 206 x 20 used as an operational forecast model by the UK Met Office image shows surface temperature for Saturday 28 th Oct
32 POLCOMS MRCS Performance (1000 model days/day) Number of processors Cray XT3 Cray XD1 SGI Altix 1.5GHz SGI Altix 1.3GHz IBM p5-575 Streamline cluster
33 Computational Engineering UK Turbulence Consortium Led by Prof. Neil Sandham, University of Southampton Focus on compute-intensive methods (Direct Numerical Simulation, Large Eddy Simulation, etc) for the simulation of turbulent flows Shock boundary layer interaction modelling - critical for accurate aerodynamic design but still poorly understood
34 PDNS3D Code - characteristics Structured grid with finite difference formulation Communication limited to nearest neighbour halo exchange High-order methods lead to high compute/communicate ratio Performance profiling shows that single cpu performance is limited by memory accesses very little cache re-use Vectorises well VERY heavy on memory accesses
35 PDNS3D high-end PCHAN T3 ( 360 x 360 x 360) Performance (Mgridpoints*iterations/sec) Cray X1 IBM p5-575 SGI Altix 1.5 GHz SGI Altix 1.3 GHz Cray XT3 Cray XD1 Streamline cluster Number of processors
36 DL_POLY3 Gramicidin-A 150 Performance (arbitrary) Cray XT3 SGI Altix 1500 IBM p5-575 HPS SGI Altix Number of processors
37 GAMESS-US SiC 3 40 Performance (arbitrary) Thanks to Graham Fletcher for these data IBM p5-575 HPS Cray XT Number of processors
38 So how did the applications do?
39 Application Summary <<< Cray XT3 worse Cray XT3 better >>> -100% -50% 0% 50% 100% PCHAN POLCOMS DL_POLY3 GAMESS-US 128 proc 256 proc
40 What about dual-core on the Cray XT3?
41 POLCOMS MRCS dual-core Performance (1000 model days/day) Number of MPI tasks Average 95% of singlecore Cray XT3 single-core Cray XT3 dual-core IBM p5-575 dual-core
42 PDNS3D T3 dual-core 6 IBM p5-575 dual-core IBM p5-575 is dual-core Performance (Mgridpoints*iterations/sec) 4 2 Cray XT3 single-core Cray XT3 dual-core 62% of single-core Number of processors
43 Conclusions We have shown initial results from an applications level benchmark comparison between IBM POWER5 and Cray XT3 Intel MPI benchmarks are very similar Latency is almost identical at us IBM HPS has better achieved bandwidth: 1.6 GB/s vs. 1.1 GB/s Applications performance depends on the application So far most (3:1) apps perform better on the Cray XT3 One memory intensive app performs much better on the IBM Memory intensive apps appear to be badly affected by the move to dual-core (& multi-core?)
44 If you have been Thank you for listening
Performance of Cray Systems Kernels, Applications & Experiences
Performance of Cray Systems Kernels, Applications & Experiences Mike Ashworth, Miles Deegan, Martyn Guest, Christine Kitchen, Igor Kozin and Richard Wain Computational Science and CCLRC Daresbury Laboratory
Performance of Cray Systems Kernels, Applications & Experiences
Performance of Cray Systems Kernels, Applications & Experiences Mike Ashworth, Miles Deegan, Martyn Guest, Christine Kitchen, Igor Kozin and Richard Wain Computational Science & Engineering Department,
Early Evaluation of the Cray XD1
Early Evaluation of the Cray XD1 (FPGAs not covered here) Mark R. Fahey Sadaf Alam, Thomas Dunigan, Jeffrey Vetter, Patrick Worley Oak Ridge National Laboratory Cray User Group May 16-19, 2005 Albuquerque,
A Performance Comparison of HPCx and HECToR
A Performance Comparison of HPCx and A. Gray 1, M. Ashworth 2, J. Hein 1, F. Reid 1, M. Weiland 1, T. Edwards 1, R. Johnstone 2, P. Knight 3 1 EPCC, The University of Edinburgh, James Clerk Maxwell Building,
Comparison of XT3 and XT4 Scalability
Comparison of XT3 and XT4 Scalability Patrick H. Worley Oak Ridge National Laboratory CUG 2007 May 7-10, 2007 Red Lion Hotel Seattle, WA Acknowledgements Research sponsored by the Climate Change Research
Performance Analysis of the PSyKAl Approach for a NEMO-based Benchmark
Performance Analysis of the PSyKAl Approach for a NEMO-based Benchmark Mike Ashworth, Rupert Ford and Andrew Porter Scientific Computing Department and STFC Hartree Centre STFC Daresbury Laboratory United
The Cray Rainier System: Integrated Scalar/Vector Computing
THE SUPERCOMPUTER COMPANY The Cray Rainier System: Integrated Scalar/Vector Computing Per Nyberg 11 th ECMWF Workshop on HPC in Meteorology Topics Current Product Overview Cray Technology Strengths Rainier
HECToR. The new UK National High Performance Computing Service. Dr Mark Parsons Commercial Director, EPCC
HECToR The new UK National High Performance Computing Service Dr Mark Parsons Commercial Director, EPCC m.parsons@epcc.ed.ac.uk +44 131 650 5022 Summary Why we need supercomputers The HECToR Service Technologies
Update on Cray Activities in the Earth Sciences
Update on Cray Activities in the Earth Sciences Presented to the 13 th ECMWF Workshop on the Use of HPC in Meteorology 3-7 November 2008 Per Nyberg nyberg@cray.com Director, Marketing and Business Development
Scheduling Strategies for HPC as a Service (HPCaaS) for Bio-Science Applications
Scheduling Strategies for HPC as a Service (HPCaaS) for Bio-Science Applications Sep 2009 Gilad Shainer, Tong Liu (Mellanox); Jeffrey Layton (Dell); Joshua Mora (AMD) High Performance Interconnects for
The Effect of Page Size and TLB Entries on Application Performance
The Effect of Page Size and TLB Entries on Application Performance Neil Stringfellow CSCS Swiss National Supercomputing Centre June 5, 2006 Abstract The AMD Opteron processor allows for two page sizes
Early Evaluation of the Cray X1 at Oak Ridge National Laboratory
Early Evaluation of the Cray X1 at Oak Ridge National Laboratory Patrick H. Worley Thomas H. Dunigan, Jr. Oak Ridge National Laboratory 45th Cray User Group Conference May 13, 2003 Hyatt on Capital Square
HECToR. UK National Supercomputing Service. Andy Turner & Chris Johnson
HECToR UK National Supercomputing Service Andy Turner & Chris Johnson Outline EPCC HECToR Introduction HECToR Phase 3 Introduction to AMD Bulldozer Architecture Performance Application placement the hardware
The NEMO Ocean Modelling Code: A Case Study
The NEMO Ocean Modelling Code: A Case Study CUG 24 th 27 th May 2010 Dr Fiona J. L. Reid Applications Consultant, EPCC f.reid@epcc.ed.ac.uk +44 (0)131 651 3394 Acknowledgements Cray Centre of Excellence
An Introduction to OpenACC
An Introduction to OpenACC Alistair Hart Cray Exascale Research Initiative Europe 3 Timetable Day 1: Wednesday 29th August 2012 13:00 Welcome and overview 13:15 Session 1: An Introduction to OpenACC 13:15
CESM (Community Earth System Model) Performance Benchmark and Profiling. August 2011
CESM (Community Earth System Model) Performance Benchmark and Profiling August 2011 Note The following research was performed under the HPC Advisory Council activities Participating vendors: Intel, Dell,
PARALLEL DNS USING A COMPRESSIBLE TURBULENT CHANNEL FLOW BENCHMARK
European Congress on Computational Methods in Applied Sciences and Engineering ECCOMAS Computational Fluid Dynamics Conference 2001 Swansea, Wales, UK, 4-7 September 2001 ECCOMAS PARALLEL DNS USING A COMPRESSIBLE
Preparing GPU-Accelerated Applications for the Summit Supercomputer
Preparing GPU-Accelerated Applications for the Summit Supercomputer Fernanda Foertter HPC User Assistance Group Training Lead foertterfs@ornl.gov This research used resources of the Oak Ridge Leadership
Application Performance on Dual Processor Cluster Nodes
Application Performance on Dual Processor Cluster Nodes by Kent Milfeld milfeld@tacc.utexas.edu edu Avijit Purkayastha, Kent Milfeld, Chona Guiang, Jay Boisseau TEXAS ADVANCED COMPUTING CENTER Thanks Newisys
HPCS HPCchallenge Benchmark Suite
HPCS HPCchallenge Benchmark Suite David Koester, Ph.D. () Jack Dongarra (UTK) Piotr Luszczek () 28 September 2004 Slide-1 Outline Brief DARPA HPCS Overview Architecture/Application Characterization Preliminary
BlueGene/L. Computer Science, University of Warwick. Source: IBM
BlueGene/L Source: IBM 1 BlueGene/L networking BlueGene system employs various network types. Central is the torus interconnection network: 3D torus with wrap-around. Each node connects to six neighbours
MIKE 21 & MIKE 3 Flow Model FM. Transport Module. Short Description
MIKE 21 & MIKE 3 Flow Model FM Transport Module Short Description DHI headquarters Agern Allé 5 DK-2970 Hørsholm Denmark +45 4516 9200 Telephone +45 4516 9333 Support +45 4516 9292 Telefax mike@dhigroup.com
CRAY XK6 REDEFINING SUPERCOMPUTING. - Sanjana Rakhecha - Nishad Nerurkar
CRAY XK6 REDEFINING SUPERCOMPUTING - Sanjana Rakhecha - Nishad Nerurkar CONTENTS Introduction History Specifications Cray XK6 Architecture Performance Industry acceptance and applications Summary INTRODUCTION
CPMD Performance Benchmark and Profiling. February 2014
CPMD Performance Benchmark and Profiling February 2014 Note The following research was performed under the HPC Advisory Council activities Special thanks for: HP, Mellanox For more information on the supporting
Alfa-SCAT Scientific Computing Advanced Training
Alfa-SCAT Scientific Computing Advanced Training impa Concepts in Parallel Computing Dr Mike Ashworth Computational Science & Engineering Dept CCLRC Daresbury Laboratory & HPCx Terascaling Team Outline
NEMO Performance Benchmark and Profiling. May 2011
NEMO Performance Benchmark and Profiling May 2011 Note The following research was performed under the HPC Advisory Council HPC works working group activities Participating vendors: HP, Intel, Mellanox
HPCC Results. Nathan Wichmann Benchmark Engineer
HPCC Results Nathan Wichmann Benchmark Engineer Outline What is HPCC? Results Comparing current machines Conclusions May 04 2 HPCChallenge Project Goals To examine the performance of HPC architectures
Outline. Execution Environments for Parallel Applications. Supercomputers. Supercomputers
Outline Execution Environments for Parallel Applications Master CANS 2007/2008 Departament d Arquitectura de Computadors Universitat Politècnica de Catalunya Supercomputers OS abstractions Extended OS
Assessment of LS-DYNA Scalability Performance on Cray XD1
5 th European LS-DYNA Users Conference Computing Technology (2) Assessment of LS-DYNA Scalability Performance on Cray Author: Ting-Ting Zhu, Cray Inc. Correspondence: Telephone: 651-65-987 Fax: 651-65-9123
Titan - Early Experience with the Titan System at Oak Ridge National Laboratory
Office of Science Titan - Early Experience with the Titan System at Oak Ridge National Laboratory Buddy Bland Project Director Oak Ridge Leadership Computing Facility November 13, 2012 ORNL s Titan Hybrid
The Hopper System: How the Largest* XE6 in the World Went From Requirements to Reality! Katie Antypas, Tina Butler, and Jonathan Carter
The Hopper System: How the Largest* XE6 in the World Went From Requirements to Reality! Katie Antypas, Tina Butler, and Jonathan Carter CUG 2011, May 25th, 2011 1 Requirements to Reality Develop RFP Select
Impact and Optimum Placement of Off-Shore Energy Generating Platforms
Available on-line at www.prace-ri.eu Partnership for Advanced Computing in Europe Impact and Optimum Placement of Off-Shore Energy Generating Platforms Charles Moulinec a,, David R. Emerson a a STFC Daresbury,
An LPAR-customized MPI_AllToAllV for the Materials Science code CASTEP
An LPAR-customized MPI_AllToAllV for the Materials Science code CASTEP M. Plummer and K. Refson CLRC Daresbury Laboratory, Daresbury, Warrington, Cheshire, WA4 4AD, UK CLRC Rutherford Appleton Laboratory,
Comparing Linux Clusters for the Community Climate System Model
Comparing Linux Clusters for the Community Climate System Model Matthew Woitaszek, Michael Oberg, and Henry M. Tufo Department of Computer Science University of Colorado, Boulder {matthew.woitaszek, michael.oberg}@colorado.edu,
Communication has significant impact on application performance. Interconnection networks therefore have a vital role in cluster systems.
Cluster Networks Introduction Communication has significant impact on application performance. Interconnection networks therefore have a vital role in cluster systems. As usual, the driver is performance
Maxwell: a 64-FPGA Supercomputer
Maxwell: a 64-FPGA Supercomputer Copyright 2007, the University of Edinburgh Dr Rob Baxter Software Development Group Manager, EPCC R.Baxter@epcc.ed.ac.uk +44 131 651 3579 Outline The FHPCA Why build Maxwell?
Computer Architectures and Aspects of NWP models
Computer Architectures and Aspects of NWP models Deborah Salmond ECMWF Shinfield Park, Reading, UK Abstract: This paper describes the supercomputers used in operational NWP together with the computer aspects
AMBER 11 Performance Benchmark and Profiling. July 2011
AMBER 11 Performance Benchmark and Profiling July 2011 Note The following research was performed under the HPC Advisory Council activities Participating vendors: AMD, Dell, Mellanox Compute resource -
Interconnect Performance Evaluation of SGI Altix Cray X1, Cray Opteron, and Dell PowerEdge
Interconnect Performance Evaluation of SGI Altix 3700 Cray X1, Cray Opteron, and Dell PowerEdge Panagiotis Adamidis University of Stuttgart High Performance Computing Center, Nobelstrasse 19, D-70569 Stuttgart,
OP2 FOR MANY-CORE ARCHITECTURES
OP2 FOR MANY-CORE ARCHITECTURES G.R. Mudalige, M.B. Giles, Oxford e-research Centre, University of Oxford gihan.mudalige@oerc.ox.ac.uk 27 th Jan 2012 1 AGENDA OP2 Current Progress Future work for OP2 EPSRC
HPC SERVICE PROVISION FOR THE UK
HPC SERVICE PROVISION FOR THE UK 5 SEPTEMBER 2016 Dr Alan D Simpson ARCHER CSE Director EPCC Technical Director Overview Tiers of HPC Tier 0 PRACE Tier 1 ARCHER DiRAC Tier 2 EPCC Oxford Cambridge UCL Tiers
Porting and Optimisation of UM on ARCHER. Karthee Sivalingam, NCAS-CMS. HPC Workshop ECMWF JWCRP
Porting and Optimisation of UM on ARCHER Karthee Sivalingam, NCAS-CMS HPC Workshop ECMWF JWCRP Acknowledgements! NCAS-CMS Bryan Lawrence Jeffrey Cole Rosalyn Hatcher Andrew Heaps David Hassell Grenville
Parallel Programming Concepts. Tom Logan Parallel Software Specialist Arctic Region Supercomputing Center 2/18/04. Parallel Background. Why Bother?
Parallel Programming Concepts Tom Logan Parallel Software Specialist Arctic Region Supercomputing Center 2/18/04 Parallel Background Why Bother? 1 What is Parallel Programming? Simultaneous use of multiple
Non-Blocking Collectives for MPI
Non-Blocking Collectives for MPI overlap at the highest level Torsten Höfler Open Systems Lab Indiana University Bloomington, IN, USA Institut für Wissenschaftliches Rechnen Technische Universität Dresden
Introduction to FREE National Resources for Scientific Computing. Dana Brunson. Jeff Pummill
Introduction to FREE National Resources for Scientific Computing Dana Brunson Oklahoma State University High Performance Computing Center Jeff Pummill University of Arkansas High Peformance Computing Center
HPC Issues for DFT Calculations. Adrian Jackson EPCC
HC Issues for DFT Calculations Adrian Jackson ECC Scientific Simulation Simulation fast becoming 4 th pillar of science Observation, Theory, Experimentation, Simulation Explore universe through simulation
NERSC Site Update. National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory. Richard Gerber
NERSC Site Update National Energy Research Scientific Computing Center Lawrence Berkeley National Laboratory Richard Gerber NERSC Senior Science Advisor High Performance Computing Department Head Cori
The IBM Blue Gene/Q: Application performance, scalability and optimisation
The IBM Blue Gene/Q: Application performance, scalability and optimisation Mike Ashworth, Andrew Porter Scientific Computing Department & STFC Hartree Centre Manish Modani IBM STFC Daresbury Laboratory,
ICON Performance Benchmark and Profiling. March 2012
ICON Performance Benchmark and Profiling March 2012 Note The following research was performed under the HPC Advisory Council activities Participating vendors: Intel, Dell, Mellanox Compute resource - HPC
Continued Investigation of Small-Scale Air-Sea Coupled Dynamics Using CBLAST Data
Continued Investigation of Small-Scale Air-Sea Coupled Dynamics Using CBLAST Data Dick K.P. Yue Center for Ocean Engineering Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge,
MIKE 21 & MIKE 3 FLOW MODEL FM. Transport Module. Short Description
MIKE 21 & MIKE 3 FLOW MODEL FM Short Description MIKE213_TR_FM_Short_Description.docx/AJS/EBR/2011Short_Descriptions.lsm//2011-06-17 MIKE 21 & MIKE 3 FLOW MODEL FM Agern Allé 5 DK-2970 Hørsholm Denmark
Implementation and Performance Analysis of Non-Blocking Collective Operations for MPI
Implementation and Performance Analysis of Non-Blocking Collective Operations for MPI T. Hoefler 1,2, A. Lumsdaine 1 and W. Rehm 2 1 Open Systems Lab 2 Computer Architecture Group Indiana University Technical
HPC Integer Benchmarks: An Indepth Analysis of the Performance Sensitivity of Legacy codes on Current Hardware Platforms
HPC Integer Benchmarks: An Indepth Analysis of the Performance Sensitivity of Legacy codes on Current Hardware Platforms Christine A. Kitchen, Martyn F. Guest, Michael Ehrig, Miles J. Deegan, Igor N. Kozin
Benchmark Results. 2006/10/03
Benchmark Results cychou@nchc.org.tw 2006/10/03 Outline Motivation HPC Challenge Benchmark Suite Software Installation guide Fine Tune Results Analysis Summary 2 Motivation Evaluate, Compare, Characterize
The Red Storm System: Architecture, System Update and Performance Analysis
The Red Storm System: Architecture, System Update and Performance Analysis Douglas Doerfler, Jim Tomkins Sandia National Laboratories Center for Computation, Computers, Information and Mathematics LACSI
Computer Comparisons Using HPCC. Nathan Wichmann Benchmark Engineer
Computer Comparisons Using HPCC Nathan Wichmann Benchmark Engineer Outline Comparisons using HPCC HPCC test used Methods used to compare machines using HPCC Normalize scores Weighted averages Comparing
Unified Model Performance on the NEC SX-6
Unified Model Performance on the NEC SX-6 Paul Selwood Crown copyright 2004 Page 1 Introduction The Met Office National Weather Service Global and Local Area Climate Prediction (Hadley Centre) Operational
A PCIe Congestion-Aware Performance Model for Densely Populated Accelerator Servers
A PCIe Congestion-Aware Performance Model for Densely Populated Accelerator Servers Maxime Martinasso, Grzegorz Kwasniewski, Sadaf R. Alam, Thomas C. Schulthess, Torsten Hoefler Swiss National Supercomputing
Pre-announcement of upcoming procurement, NWP18, at National Supercomputing Centre at Linköping University
Pre-announcement of upcoming procurement, NWP18, at National Supercomputing Centre at Linköping University 2017-06-14 Abstract Linköpings universitet hereby announces the opportunity to participate in
GROMACS Performance Benchmark and Profiling. September 2012
GROMACS Performance Benchmark and Profiling September 2012 Note The following research was performed under the HPC Advisory Council activities Participating vendors: AMD, Dell, Mellanox Compute resource
The Architecture and the Application Performance of the Earth Simulator
The Architecture and the Application Performance of the Earth Simulator Ken ichi Itakura (JAMSTEC) http://www.jamstec.go.jp 15 Dec., 2011 ICTS-TIFR Discussion Meeting-2011 1 Location of Earth Simulator
HPC projects. Grischa Bolls
HPC projects Grischa Bolls Outline Why projects? 7th Framework Programme Infrastructure stack IDataCool, CoolMuc Mont-Blanc Poject Deep Project Exa2Green Project 2 Why projects? Pave the way for exascale
Application Performance on an e-server Blue Gene: Early Experiences. Lorna Smith EPCC, The University of Edinburgh
Application Performance on an e-server Blue Gene: Early Experiences Lorna Smith EPCC, The University of Edinburgh l.smith@epcc.ed.ac.uk 3-Jun-05 ScicomP 11 - Edinburgh 2 Overview Acknowledgements / contributors
Exascale Challenges and Applications Initiatives for Earth System Modeling
Exascale Challenges and Applications Initiatives for Earth System Modeling Workshop on Weather and Climate Prediction on Next Generation Supercomputers 22-25 October 2012 Tom Edwards tedwards@cray.com
DISP: Optimizations Towards Scalable MPI Startup
DISP: Optimizations Towards Scalable MPI Startup Huansong Fu, Swaroop Pophale*, Manjunath Gorentla Venkata*, Weikuan Yu Florida State University *Oak Ridge National Laboratory Outline Background and motivation
Uncertainty Analysis: Parameter Estimation. Jackie P. Hallberg Coastal and Hydraulics Laboratory Engineer Research and Development Center
Uncertainty Analysis: Parameter Estimation Jackie P. Hallberg Coastal and Hydraulics Laboratory Engineer Research and Development Center Outline ADH Optimization Techniques Parameter space Observation
CP2K Performance Benchmark and Profiling. April 2011
CP2K Performance Benchmark and Profiling April 2011 Note The following research was performed under the HPC Advisory Council HPC works working group activities Participating vendors: HP, Intel, Mellanox
NAMD Performance Benchmark and Profiling. November 2010
NAMD Performance Benchmark and Profiling November 2010 Note The following research was performed under the HPC Advisory Council activities Participating vendors: HP, Mellanox Compute resource - HPC Advisory
Performance of Variant Memory Configurations for Cray XT Systems
Performance of Variant Memory Configurations for Cray XT Systems Wayne Joubert, Oak Ridge National Laboratory ABSTRACT: In late 29 NICS will upgrade its 832 socket Cray XT from Barcelona (4 cores/socket)
High Performance MPI on IBM 12x InfiniBand Architecture
High Performance MPI on IBM 12x InfiniBand Architecture Abhinav Vishnu, Brad Benton 1 and Dhabaleswar K. Panda {vishnu, panda} @ cse.ohio-state.edu {brad.benton}@us.ibm.com 1 1 Presentation Road-Map Introduction
Multigrid Solvers in CFD. David Emerson. Scientific Computing Department STFC Daresbury Laboratory Daresbury, Warrington, WA4 4AD, UK
Multigrid Solvers in CFD David Emerson Scientific Computing Department STFC Daresbury Laboratory Daresbury, Warrington, WA4 4AD, UK david.emerson@stfc.ac.uk 1 Outline Multigrid: general comments Incompressible
Why Parallel Architecture
Why Parallel Architecture and Programming? Todd C. Mowry 15-418 January 11, 2011 What is Parallel Programming? Software with multiple threads? Multiple threads for: convenience: concurrent programming
High Performance Computing : Code_Saturne in the PRACE project
High Performance Computing : Code_Saturne in the PRACE project Andy SUNDERLAND Charles MOULINEC STFC Daresbury Laboratory, UK Code_Saturne User Meeting Chatou 1st-2nd Dec 28 STFC Daresbury Laboratory HPC
Výpočetní zdroje IT4Innovations a PRACE pro využití ve vědě a výzkumu
Výpočetní zdroje IT4Innovations a PRACE pro využití ve vědě a výzkumu Filip Staněk Seminář gridového počítání 2011, MetaCentrum, Brno, 7. 11. 2011 Introduction I Project objectives: to establish a centre
Red Storm / Cray XT4: A Superior Architecture for Scalability
Red Storm / Cray XT4: A Superior Architecture for Scalability Mahesh Rajan, Doug Doerfler, Courtenay Vaughan Sandia National Laboratories, Albuquerque, NM Cray User Group Atlanta, GA; May 4-9, 2009 Sandia
IFS migrates from IBM to Cray CPU, Comms and I/O
IFS migrates from IBM to Cray CPU, Comms and I/O Deborah Salmond & Peter Towers Research Department Computing Department Thanks to Sylvie Malardel, Philippe Marguinaud, Alan Geer & John Hague and many
Operational Robustness of Accelerator Aware MPI
Operational Robustness of Accelerator Aware MPI Sadaf Alam Swiss National Supercomputing Centre (CSSC) Switzerland 2nd Annual MVAPICH User Group (MUG) Meeting, 2014 Computing Systems @ CSCS http://www.cscs.ch/computers
Efficient Tridiagonal Solvers for ADI methods and Fluid Simulation
Efficient Tridiagonal Solvers for ADI methods and Fluid Simulation Nikolai Sakharnykh - NVIDIA San Jose Convention Center, San Jose, CA September 21, 2010 Introduction Tridiagonal solvers very popular
CHAO YANG. Early Experience on Optimizations of Application Codes on the Sunway TaihuLight Supercomputer
CHAO YANG Dr. Chao Yang is a full professor at the Laboratory of Parallel Software and Computational Sciences, Institute of Software, Chinese Academy Sciences. His research interests include numerical
Japan s post K Computer Yutaka Ishikawa Project Leader RIKEN AICS
Japan s post K Computer Yutaka Ishikawa Project Leader RIKEN AICS HPC User Forum, 7 th September, 2016 Outline of Talk Introduction of FLAGSHIP2020 project An Overview of post K system Concluding Remarks
3D ADI Method for Fluid Simulation on Multiple GPUs. Nikolai Sakharnykh, NVIDIA Nikolay Markovskiy, NVIDIA
3D ADI Method for Fluid Simulation on Multiple GPUs Nikolai Sakharnykh, NVIDIA Nikolay Markovskiy, NVIDIA Introduction Fluid simulation using direct numerical methods Gives the most accurate result Requires
Massively Parallel Computing for Incompressible Smoothed Particle Hydrodynamics
Massively Parallel Computing for Incompressible Smoothed Particle Hydrodynamics Xiaohu Guo a, Benedict D. Rogers b, Peter. K. Stansby b, Mike Ashworth a a Application Performance Engineering Group, Scientific
Transactions on Information and Communications Technologies vol 9, 1995 WIT Press, ISSN
Parallelization of software for coastal hydraulic simulations for distributed memory parallel computers using FORGE 90 Z.W. Song, D. Roose, C.S. Yu, J. Berlamont B-3001 Heverlee, Belgium 2, Abstract Due
Performance Analysis for Large Scale Simulation Codes with Periscope
Performance Analysis for Large Scale Simulation Codes with Periscope M. Gerndt, Y. Oleynik, C. Pospiech, D. Gudu Technische Universität München IBM Deutschland GmbH May 2011 Outline Motivation Periscope
Supercomputing with Commodity CPUs: Are Mobile SoCs Ready for HPC?
Supercomputing with Commodity CPUs: Are Mobile SoCs Ready for HPC? Nikola Rajovic, Paul M. Carpenter, Isaac Gelado, Nikola Puzovic, Alex Ramirez, Mateo Valero SC 13, November 19 th 2013, Denver, CO, USA
Turbostream: A CFD solver for manycore
Turbostream: A CFD solver for manycore processors Tobias Brandvik Whittle Laboratory University of Cambridge Aim To produce an order of magnitude reduction in the run-time of CFD solvers for the same hardware
Evaluation of the Cray XT3 at ORNL: a Status Report
Evaluation of the Cray XT3 at ORNL: a Status Report Sadaf R. Alam Richard F. Barrett Mark R. Fahey O. E. Bronson Messer Richard T. Mills Philip C. Roth Jeffrey S. Vetter Patrick H. Worley Oak Ridge National
Extension of NHWAVE to Couple LAMMPS for Modeling Wave Interactions with Arctic Ice Floes
DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Extension of NHWAVE to Couple LAMMPS for Modeling Wave Interactions with Arctic Ice Floes Fengyan Shi and James T. Kirby
Enhancing scalability of the gyrokinetic code GS2 by using MPI Shared Memory for FFTs
Enhancing scalability of the gyrokinetic code GS2 by using MPI Shared Memory for FFTs Lucian Anton 1, Ferdinand van Wyk 2,4, Edmund Highcock 2, Colin Roach 3, Joseph T. Parker 5 1 Cray UK, 2 University
Performance of HPC Applications over InfiniBand, 10 Gb and 1 Gb Ethernet. Swamy N. Kandadai and Xinghong He and
Performance of HPC Applications over InfiniBand, 10 Gb and 1 Gb Ethernet Swamy N. Kandadai and Xinghong He swamy@us.ibm.com and xinghong@us.ibm.com ABSTRACT: We compare the performance of several applications
SPEC MPI2007 Benchmarks for HPC Systems
SPEC MPI2007 Benchmarks for HPC Systems Ron Lieberman Chair, SPEC HPG HP-MPI Performance Hewlett-Packard Company Dr. Tom Elken Manager, Performance Engineering QLogic Corporation Dr William Brantley Manager
PERFORMANCE PORTABILITY WITH OPENACC. Jeff Larkin, NVIDIA, November 2015
PERFORMANCE PORTABILITY WITH OPENACC Jeff Larkin, NVIDIA, November 2015 TWO TYPES OF PORTABILITY FUNCTIONAL PORTABILITY PERFORMANCE PORTABILITY The ability for a single code to run anywhere. The ability
Composite Metrics for System Throughput in HPC
Composite Metrics for System Throughput in HPC John D. McCalpin, Ph.D. IBM Corporation Austin, TX SuperComputing 2003 Phoenix, AZ November 18, 2003 Overview The HPC Challenge Benchmark was announced last
GROMACS Performance Benchmark and Profiling. August 2011
GROMACS Performance Benchmark and Profiling August 2011 Note The following research was performed under the HPC Advisory Council activities Participating vendors: Intel, Dell, Mellanox Compute resource
Cray XC Scalability and the Aries Network Tony Ford
Cray XC Scalability and the Aries Network Tony Ford June 29, 2017 Exascale Scalability Which scalability metrics are important for Exascale? Performance (obviously!) What are the contributing factors?
Flux Vector Splitting Methods for the Euler Equations on 3D Unstructured Meshes for CPU/GPU Clusters
Flux Vector Splitting Methods for the Euler Equations on 3D Unstructured Meshes for CPU/GPU Clusters Manfred Liebmann Technische Universität München Chair of Optimal Control Center for Mathematical Sciences,
An evaluation of the Performance and Scalability of a Yellowstone Test-System in 5 Benchmarks
An evaluation of the Performance and Scalability of a Yellowstone Test-System in 5 Benchmarks WRF Model NASA Parallel Benchmark Intel MPI Bench My own personal benchmark HPC Challenge Benchmark Abstract
Early Experiences Writing Performance Portable OpenMP 4 Codes
Early Experiences Writing Performance Portable OpenMP 4 Codes Verónica G. Vergara Larrea Wayne Joubert M. Graham Lopez Oscar Hernandez Oak Ridge National Laboratory Problem statement APU FPGA neuromorphic
Mesh reordering in Fluidity using Hilbert space-filling curves
Mesh reordering in Fluidity using Hilbert space-filling curves Mark Filipiak EPCC, University of Edinburgh March 2013 Abstract Fluidity is open-source, multi-scale, general purpose CFD model. It is a finite
Cray events. ! Cray User Group (CUG): ! Cray Technical Workshop Europe:
Cray events! Cray User Group (CUG):! When: May 16-19, 2005! Where: Albuquerque, New Mexico - USA! Registration: reserved to CUG members! Web site: http://www.cug.org! Cray Technical Workshop Europe:! When: