Performance Characteristics of Large SMP Machines

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Performance Characteristics of Large SMP Machines"

Transcription

1 Performance Characteristics of Large SMP Machines Dirk Schmidl, Dieter an Mey, Matthias S. Müller Rechen- und Kommunikationszentrum (RZ)

2 Agenda Investigated Hardware Kernel Benchmark Results Memory Bandwidth NUMA Distances Synchronizations Applications NestedCP TrajSearch Conclusion 2

3 Hardware HP ProLiant DL98 G7 8 x Intel Xeon 2 GHz 256 GB main memory internally several boards SGI Altix Ultraviolet 14 x Intel Xeon 2.4 GHz about 2 TB main memory 2 Socket Boards connected with NUMALink network Bull Coherence Switch System 16 x Intel Xeon 2 GHz 256 GB main memory 3 4-socket boards externally connected with the Bull Coherence Switch (BCS)

4 Hardware ScaleMP System 64 x Intel Xeon 2 GHz about 4 TB main memory 4-socket boards connected with Infiniband vsmp foundation software used to create a cache coherent single system Intel Xeon Phi 1 Intel Xeon Phi 1.5 GHz plugged in a PCIe slot 8 GB main memory 4

5 1B 16B 256B 4KB 64KB 1MB 16MB 256MB 4GB 1B 16B 256B 4KB 64KB 1MB 16MB 256MB 4GB Bandwidth in GB/s Bandwidth in GB/s 1B 16B 256B 4KB 64KB 1MB 16MB 256MB 4GB 1B 16B 256B 4KB 64KB 1MB 16MB 256MB 4GB 1B 16B 256B 4KB 64KB 1MB 16MB 256MB 4GB Bandwidth in GB/s Bandwidth in GB/s Bandwidth in GB/s Serial Bandwidth Write Bandwidth HP Write Bandwidth BCS Write Bandwidth AltixUV Write Bandwidth ScaleMP Write Bandwidth Phi local remote 1st level remote 2nd level 5 Standard SW-Prefetching

6 Distance Matrix Measured bandwidth between sockets memory and threads placed with numactl normalized to 1 for socket BCS Socket remote accesses much more expensive on the BCS machine HP machine internally has also several NUMA levels HP Socket

7 Bandwidth in GB/s Parallel Bandwidth Number of Threads HP-read ALTIX-read BCS-read SCALEMP-read Phi-read HP-write ALTIX-write BCS-write SCALEMP-write Phi-write Read and Write Bandwidth on local data 16 MB memory footprint per thread 7

8 mem_go_around Investigate slow-down, when remote accesses ocure Every thread initializes local memory and measures the bandwidth In step n thread t uses the memory of thread (t+n)%nthreads this increases the number of remote accesses in every step 8

9 Memory Bandwidth in GB/s mem_go_around Turn HP Altix BCS ScaleMP Phi 9

10 Synchronization Overhead in microseconds to acquire a lock #threads BCS SCALEMP PHI ALTIX HP / / / Synchronization overhead rises with the number of threads ScaleMP introduces more overhead for large thread counts 1

11 NestedCP: Parallel Critical Point Extraction Virtual Reality Group of RWTH Aachen University: Analysis of large-scale flow simulations Feature extraction from raw data Interactive analysis in virtual environment (e.g. a cave) Critical Point: Point in the vector field with zero velocity Andreas Gerndt, Virtual Reality Center, RWTH Aachen 11

12 /6 128/12 24 Runtime in sec. Speedup NestedCP parallelization done with OpenMP tasks many independent tasks only synchronized at the end Number of Threads BCS SCALEMP PHI ALTIX HP BCS-Speedup SCALEMP-Speedup PHI-Speedup ALTIX-Speedup HP-Speedup 12

13 TrajSearch Direct Numerical Simulation of three dimensional turbulent flow field produces large output arrays ~ ½ year of computation produced 248³ output grid (32GB) Trajectory Analysis (TrajSearch) implemented with OpenMP was optimized for large NUMA machines Here the 124³ grid cells data was used (~4 GB) Institute for Combustion Technology 13

14 Runtime in hours Speedup TrajSearch Optimizations: reduced number of locks NUMA aware data initialization data blocked to 8x8x8 blocks to load nearest data on ScaleMP self-written NUMA aware scheduler Number of Threads ALTIX BCS SCALEMP ALTIX-Speedup BCS-Speedup SCALEMP-Speedup 14

15 Conclusion larger systems provide a larger total memory bandwidth the overhead for a lot of remote accesses is also higher on larger systems as has been seen with the mem_go_around test the caching in the vsmp software can hide the remote latency, even when larger arrays are read or written remotely synchronization is a problem on all systems that increases with the number of cores the Xeon Phi system delivers a good bandwidth and low synchronization overhead for a large number of threads applications can run well on large NUMA machines Remark: A Revised version with newer performance measurements will soon be available on our website under publications: https://sharepoint.campus.rwth-aachen.de/units/rz/hpc/public/default.aspx 15

16 Conclusion larger systems provide a larger total memory bandwidth the overhead for a lot of remote accesses is also higher on larger systems as has been seen with the mem_go_around test the caching in the vsmp software can hide the remote latency, even when larger arrays are read or written remotely Thank you for your attention! synchronization is a problem on all systems that increases with the Questions? number of cores the Xeon Phi system delivers a good bandwidth and low synchronization overhead for a large number of threads applications can run well on large NUMA machines Remark: A Revised version with newer performance measurements will soon be available on our website under publications: https://sharepoint.campus.rwth-aachen.de/units/rz/hpc/public/default.aspx 16

OpenMP Programming on ScaleMP

OpenMP Programming on ScaleMP OpenMP Programming on ScaleMP Dirk Schmidl schmidl@rz.rwth-aachen.de Rechen- und Kommunikationszentrum (RZ) MPI vs. OpenMP MPI distributed address space explicit message passing typically code redesign

More information

Assessing the Performance of OpenMP Programs on the Intel Xeon Phi

Assessing the Performance of OpenMP Programs on the Intel Xeon Phi Assessing the Performance of OpenMP Programs on the Intel Xeon Phi Dirk Schmidl, Tim Cramer, Sandra Wienke, Christian Terboven, and Matthias S. Müller schmidl@rz.rwth-aachen.de Rechen- und Kommunikationszentrum

More information

Parallel Programming Survey

Parallel Programming Survey Christian Terboven 02.09.2014 / Aachen, Germany Stand: 26.08.2014 Version 2.3 IT Center der RWTH Aachen University Agenda Overview: Processor Microarchitecture Shared-Memory

More information

OpenMP and Performance

OpenMP and Performance Dirk Schmidl IT Center, RWTH Aachen University Member of the HPC Group schmidl@itc.rwth-aachen.de IT Center der RWTH Aachen University Tuning Cycle Performance Tuning aims to improve the runtime of an

More information

Parallel Algorithm Engineering

Parallel Algorithm Engineering Parallel Algorithm Engineering Kenneth S. Bøgh PhD Fellow Based on slides by Darius Sidlauskas Outline Background Current multicore architectures UMA vs NUMA The openmp framework Examples Software crisis

More information

Removing Performance Bottlenecks in Databases with Red Hat Enterprise Linux and Violin Memory Flash Storage Arrays. Red Hat Performance Engineering

Removing Performance Bottlenecks in Databases with Red Hat Enterprise Linux and Violin Memory Flash Storage Arrays. Red Hat Performance Engineering Removing Performance Bottlenecks in Databases with Red Hat Enterprise Linux and Violin Memory Flash Storage Arrays Red Hat Performance Engineering Version 1.0 August 2013 1801 Varsity Drive Raleigh NC

More information

September 25, 2007. Maya Gokhale Georgia Institute of Technology

September 25, 2007. Maya Gokhale Georgia Institute of Technology NAND Flash Storage for High Performance Computing Craig Ulmer cdulmer@sandia.gov September 25, 2007 Craig Ulmer Maya Gokhale Greg Diamos Michael Rewak SNL/CA, LLNL Georgia Institute of Technology University

More information

Using the Intel Inspector XE

Using the Intel Inspector XE Using the Dirk Schmidl schmidl@rz.rwth-aachen.de Rechen- und Kommunikationszentrum (RZ) Race Condition Data Race: the typical OpenMP programming error, when: two or more threads access the same memory

More information

Altix Usage and Application Programming. Welcome and Introduction

Altix Usage and Application Programming. Welcome and Introduction Zentrum für Informationsdienste und Hochleistungsrechnen Altix Usage and Application Programming Welcome and Introduction Zellescher Weg 12 Tel. +49 351-463 - 35450 Dresden, November 30th 2005 Wolfgang

More information

SGI High Performance Computing

SGI High Performance Computing SGI High Performance Computing Accelerate time to discovery, innovation, and profitability 2014 SGI SGI Company Proprietary 1 Typical Use Cases for SGI HPC Products Large scale-out, distributed memory

More information

Performance Evaluation of NAS Parallel Benchmarks on Intel Xeon Phi

Performance Evaluation of NAS Parallel Benchmarks on Intel Xeon Phi Performance Evaluation of NAS Parallel Benchmarks on Intel Xeon Phi ICPP 6 th International Workshop on Parallel Programming Models and Systems Software for High-End Computing October 1, 2013 Lyon, France

More information

Multi-Threading Performance on Commodity Multi-Core Processors

Multi-Threading Performance on Commodity Multi-Core Processors Multi-Threading Performance on Commodity Multi-Core Processors Jie Chen and William Watson III Scientific Computing Group Jefferson Lab 12000 Jefferson Ave. Newport News, VA 23606 Organization Introduction

More information

LS DYNA Performance Benchmarks and Profiling. January 2009

LS DYNA Performance Benchmarks and Profiling. January 2009 LS DYNA Performance Benchmarks and Profiling January 2009 Note The following research was performed under the HPC Advisory Council activities AMD, Dell, Mellanox HPC Advisory Council Cluster Center The

More information

SGI UV 300, UV 30EX: Big Brains for No-Limit Computing

SGI UV 300, UV 30EX: Big Brains for No-Limit Computing SGI UV 300, UV 30EX: Big Brains for No-Limit Computing The Most ful In-memory Supercomputers for Data-Intensive Workloads Key Features Scales up to 64 sockets and 64TB of coherent shared memory Extreme

More information

Hybrid parallelism for Weather Research and Forecasting Model on Intel platforms (performance evaluation)

Hybrid parallelism for Weather Research and Forecasting Model on Intel platforms (performance evaluation) Hybrid parallelism for Weather Research and Forecasting Model on Intel platforms (performance evaluation) Roman Dubtsov*, Mark Lubin, Alexander Semenov {roman.s.dubtsov,mark.lubin,alexander.l.semenov}@intel.com

More information

HP ProLiant BL660c Gen9 and Microsoft SQL Server 2014 technical brief

HP ProLiant BL660c Gen9 and Microsoft SQL Server 2014 technical brief Technical white paper HP ProLiant BL660c Gen9 and Microsoft SQL Server 2014 technical brief Scale-up your Microsoft SQL Server environment to new heights Table of contents Executive summary... 2 Introduction...

More information

Tyche: An efficient Ethernet-based protocol for converged networked storage

Tyche: An efficient Ethernet-based protocol for converged networked storage Tyche: An efficient Ethernet-based protocol for converged networked storage Pilar González-Férez and Angelos Bilas 30 th International Conference on Massive Storage Systems and Technology MSST 2014 June

More information

Experiences with HPC on Windows

Experiences with HPC on Windows Experiences with on Christian Terboven terboven@rz.rwth aachen.de Center for Computing and Communication RWTH Aachen University Server Computing Summit 2008 April 7 11, HPI/Potsdam Experiences with on

More information

Cluster Scalability of ANSYS FLUENT 12 for a Large Aerodynamics Case on the Darwin Supercomputer

Cluster Scalability of ANSYS FLUENT 12 for a Large Aerodynamics Case on the Darwin Supercomputer Cluster Scalability of ANSYS FLUENT 12 for a Large Aerodynamics Case on the Darwin Supercomputer Stan Posey, MSc and Bill Loewe, PhD Panasas Inc., Fremont, CA, USA Paul Calleja, PhD University of Cambridge,

More information

High Performance. CAEA elearning Series. Jonathan G. Dudley, Ph.D. 06/09/2015. 2015 CAE Associates

High Performance. CAEA elearning Series. Jonathan G. Dudley, Ph.D. 06/09/2015. 2015 CAE Associates High Performance Computing (HPC) CAEA elearning Series Jonathan G. Dudley, Ph.D. 06/09/2015 2015 CAE Associates Agenda Introduction HPC Background Why HPC SMP vs. DMP Licensing HPC Terminology Types of

More information

Using the Windows Cluster

Using the Windows Cluster Using the Windows Cluster Christian Terboven terboven@rz.rwth aachen.de Center for Computing and Communication RWTH Aachen University Windows HPC 2008 (II) September 17, RWTH Aachen Agenda o Windows Cluster

More information

Introduction to parallel computers and parallel programming. Introduction to parallel computersand parallel programming p. 1

Introduction to parallel computers and parallel programming. Introduction to parallel computersand parallel programming p. 1 Introduction to parallel computers and parallel programming Introduction to parallel computersand parallel programming p. 1 Content A quick overview of morden parallel hardware Parallelism within a chip

More information

An HPC Application Deployment Model on Azure Cloud for SMEs

An HPC Application Deployment Model on Azure Cloud for SMEs An HPC Application Deployment Model on Azure Cloud for SMEs Fan Ding CLOSER 2013, Aachen, Germany, May 9th,2013 Rechen- und Kommunikationszentrum (RZ) Agenda Motivation Windows Azure Relevant Technology

More information

Case Study on Productivity and Performance of GPGPUs

Case Study on Productivity and Performance of GPGPUs Case Study on Productivity and Performance of GPGPUs Sandra Wienke wienke@rz.rwth-aachen.de ZKI Arbeitskreis Supercomputing April 2012 Rechen- und Kommunikationszentrum (RZ) RWTH GPU-Cluster 56 Nvidia

More information

Key-Value Store Acceleration with OpenPower

Key-Value Store Acceleration with OpenPower Key-Value Store Acceleration with OpenPower Michaela Blott, Principal Engineer Xilinx Research #OpenPOWERSummit Join the conversation at #OpenPOWERSummit 1 Agenda Background Acceleration of KVS with FPGAs

More information

Storage I/O Performance on VMware vsphere

Storage I/O Performance on VMware vsphere Storage I/O Performance on VMware vsphere 5.1 over 16 Gigabit Fibre Channel Performance Study TECHNICAL WHITE PAPER Table of Contents Introduction... 3 Executive Summary... 3 Setup... 3 Workload... 4 Results...

More information

Parallel Processing and Software Performance. Lukáš Marek

Parallel Processing and Software Performance. Lukáš Marek Parallel Processing and Software Performance Lukáš Marek DISTRIBUTED SYSTEMS RESEARCH GROUP http://dsrg.mff.cuni.cz CHARLES UNIVERSITY PRAGUE Faculty of Mathematics and Physics Benchmarking in parallel

More information

Achieving Nanosecond Latency Between Applications with IPC Shared Memory Messaging

Achieving Nanosecond Latency Between Applications with IPC Shared Memory Messaging Achieving Nanosecond Latency Between Applications with IPC Shared Memory Messaging In some markets and scenarios where competitive advantage is all about speed, speed is measured in micro- and even nano-seconds.

More information

Correlating Multiple TB of Performance Data to User Jobs

Correlating Multiple TB of Performance Data to User Jobs Michael Kluge, ZIH Correlating Multiple TB of Performance Data to User Jobs Lustre User Group 2015, Denver, Colorado Zellescher Weg 12 Willers-Bau A 208 Tel. +49 351-463 34217 Michael Kluge (michael.kluge@tu-dresden.de)

More information

Stovepipes to Clouds. Rick Reid Principal Engineer SGI Federal. 2013 by SGI Federal. Published by The Aerospace Corporation with permission.

Stovepipes to Clouds. Rick Reid Principal Engineer SGI Federal. 2013 by SGI Federal. Published by The Aerospace Corporation with permission. Stovepipes to Clouds Rick Reid Principal Engineer SGI Federal 2013 by SGI Federal. Published by The Aerospace Corporation with permission. Agenda Stovepipe Characteristics Why we Built Stovepipes Cluster

More information

Scalability evaluation of barrier algorithms for OpenMP

Scalability evaluation of barrier algorithms for OpenMP Scalability evaluation of barrier algorithms for OpenMP Ramachandra Nanjegowda, Oscar Hernandez, Barbara Chapman and Haoqiang H. Jin High Performance Computing and Tools Group (HPCTools) Computer Science

More information

Converged storage architecture for Oracle RAC based on NVMe SSDs and standard x86 servers

Converged storage architecture for Oracle RAC based on NVMe SSDs and standard x86 servers Converged storage architecture for Oracle RAC based on NVMe SSDs and standard x86 servers White Paper rev. 2015-11-27 2015 FlashGrid Inc. 1 www.flashgrid.io Abstract Oracle Real Application Clusters (RAC)

More information

Improving Scalability of OpenMP Applications on Multi-core Systems Using Large Page Support

Improving Scalability of OpenMP Applications on Multi-core Systems Using Large Page Support Improving Scalability of OpenMP Applications on Multi-core Systems Using Large Page Support Ranjit Noronha and Dhabaleswar K. Panda Network Based Computing Laboratory (NBCL) The Ohio State University Outline

More information

HP ProLiant: Taking it to the limit one more time

HP ProLiant: Taking it to the limit one more time HP ProLiant: Taking it to the limit one more time HP ProLiant DL585 G6 prevails with #1 four-processor performance result on two-tier SAP Sales and Distribution Standard Application Benchmark with SAP

More information

High Performance Computing in Aachen

High Performance Computing in Aachen High Performance Computing in Aachen Samuel Sarholz sarholz@rz.rwth aachen.de Center for Computing and Communication RWTH Aachen University HPC unter Linux Sep 15, RWTH Aachen Agenda o Hardware o Development

More information

Virtualization Performance on SGI UV 2000 using Red Hat Enterprise Linux 6.3 KVM

Virtualization Performance on SGI UV 2000 using Red Hat Enterprise Linux 6.3 KVM White Paper Virtualization Performance on SGI UV 2000 using Red Hat Enterprise Linux 6.3 KVM September, 2013 Author Sanhita Sarkar, Director of Engineering, SGI Abstract This paper describes how to implement

More information

RWTH GPU Cluster. Sandra Wienke wienke@rz.rwth-aachen.de November 2012. Rechen- und Kommunikationszentrum (RZ) Fotos: Christian Iwainsky

RWTH GPU Cluster. Sandra Wienke wienke@rz.rwth-aachen.de November 2012. Rechen- und Kommunikationszentrum (RZ) Fotos: Christian Iwainsky RWTH GPU Cluster Fotos: Christian Iwainsky Sandra Wienke wienke@rz.rwth-aachen.de November 2012 Rechen- und Kommunikationszentrum (RZ) The RWTH GPU Cluster GPU Cluster: 57 Nvidia Quadro 6000 (Fermi) innovative

More information

benchmarking Amazon EC2 for high-performance scientific computing

benchmarking Amazon EC2 for high-performance scientific computing Edward Walker benchmarking Amazon EC2 for high-performance scientific computing Edward Walker is a Research Scientist with the Texas Advanced Computing Center at the University of Texas at Austin. He received

More information

Advanced OpenMP Course

Advanced OpenMP Course 1 / 7 Advanced OpenMP Course: Exercises and Handout Advanced OpenMP Course Christian Terboven, Dirk Schmidl IT Center, RWTH Aachen University Seffenter Weg 23, 52074 Aachen, Germany {terboven, schmidl}@itc.rwth-aachen.de

More information

Accelerating Enterprise Applications and Reducing TCO with SanDisk ZetaScale Software

Accelerating Enterprise Applications and Reducing TCO with SanDisk ZetaScale Software WHITEPAPER Accelerating Enterprise Applications and Reducing TCO with SanDisk ZetaScale Software SanDisk ZetaScale software unlocks the full benefits of flash for In-Memory Compute and NoSQL applications

More information

A Fast Inter-Kernel Communication and Synchronization Layer for MetalSVM

A Fast Inter-Kernel Communication and Synchronization Layer for MetalSVM A Fast Inter-Kernel Communication and Synchronization Layer for MetalSVM Pablo Reble, Stefan Lankes, Carsten Clauss, Thomas Bemmerl Chair for Operating Systems, RWTH Aachen University Kopernikusstr. 16,

More information

GPU System Architecture. Alan Gray EPCC The University of Edinburgh

GPU System Architecture. Alan Gray EPCC The University of Edinburgh GPU System Architecture EPCC The University of Edinburgh Outline Why do we want/need accelerators such as GPUs? GPU-CPU comparison Architectural reasons for GPU performance advantages GPU accelerated systems

More information

Maximize Performance and Scalability of RADIOSS* Structural Analysis Software on Intel Xeon Processor E7 v2 Family-Based Platforms

Maximize Performance and Scalability of RADIOSS* Structural Analysis Software on Intel Xeon Processor E7 v2 Family-Based Platforms Maximize Performance and Scalability of RADIOSS* Structural Analysis Software on Family-Based Platforms Executive Summary Complex simulations of structural and systems performance, such as car crash simulations,

More information

Technical Paper. Performance and Tuning Considerations for SAS on Fusion-io ioscale Flash Storage

Technical Paper. Performance and Tuning Considerations for SAS on Fusion-io ioscale Flash Storage Technical Paper Performance and Tuning Considerations for SAS on Fusion-io ioscale Flash Storage Release Information Content Version: 1.0 May 2014. Trademarks and Patents SAS Institute Inc., SAS Campus

More information

ECLIPSE Performance Benchmarks and Profiling. January 2009

ECLIPSE Performance Benchmarks and Profiling. January 2009 ECLIPSE Performance Benchmarks and Profiling January 2009 Note The following research was performed under the HPC Advisory Council activities AMD, Dell, Mellanox, Schlumberger HPC Advisory Council Cluster

More information

Diablo and VMware TM powering SQL Server TM in Virtual SAN TM. A Diablo Technologies Whitepaper. May 2015

Diablo and VMware TM powering SQL Server TM in Virtual SAN TM. A Diablo Technologies Whitepaper. May 2015 A Diablo Technologies Whitepaper Diablo and VMware TM powering SQL Server TM in Virtual SAN TM May 2015 Ricky Trigalo, Director for Virtualization Solutions Architecture, Diablo Technologies Daniel Beveridge,

More information

Clusters: Mainstream Technology for CAE

Clusters: Mainstream Technology for CAE Clusters: Mainstream Technology for CAE Alanna Dwyer HPC Division, HP Linux and Clusters Sparked a Revolution in High Performance Computing! Supercomputing performance now affordable and accessible Linux

More information

Multicore Parallel Computing with OpenMP

Multicore Parallel Computing with OpenMP Multicore Parallel Computing with OpenMP Tan Chee Chiang (SVU/Academic Computing, Computer Centre) 1. OpenMP Programming The death of OpenMP was anticipated when cluster systems rapidly replaced large

More information

COMPUTER ORGANIZATION ARCHITECTURES FOR EMBEDDED COMPUTING

COMPUTER ORGANIZATION ARCHITECTURES FOR EMBEDDED COMPUTING COMPUTER ORGANIZATION ARCHITECTURES FOR EMBEDDED COMPUTING 2013/2014 1 st Semester Sample Exam January 2014 Duration: 2h00 - No extra material allowed. This includes notes, scratch paper, calculator, etc.

More information

IBM System x Enterprise Servers in the New Enterprise Data

IBM System x Enterprise Servers in the New Enterprise Data IBM System x Enterprise Servers in the New Enterprise Data IBM Virtualization and Consolidation solutions beat the competition and save you money! 118% better performance 36% better performance 40% lower

More information

Toward a practical HPC Cloud : Performance tuning of a virtualized HPC cluster

Toward a practical HPC Cloud : Performance tuning of a virtualized HPC cluster Toward a practical HPC Cloud : Performance tuning of a virtualized HPC cluster Ryousei Takano Information Technology Research Institute, National Institute of Advanced Industrial Science and Technology

More information

Suitability of Performance Tools for OpenMP Task-parallel Programs

Suitability of Performance Tools for OpenMP Task-parallel Programs Suitability of Performance Tools for OpenMP Task-parallel Programs Dirk Schmidl et al. schmidl@rz.rwth-aachen.de Rechen- und Kommunikationszentrum (RZ) Agenda The OpenMP Tasking Model Task-Programming

More information

HP ProLiant SL270s Gen8 Server. Evaluation Report

HP ProLiant SL270s Gen8 Server. Evaluation Report HP ProLiant SL270s Gen8 Server Evaluation Report Thomas Schoenemeyer, Hussein Harake and Daniel Peter Swiss National Supercomputing Centre (CSCS), Lugano Institute of Geophysics, ETH Zürich schoenemeyer@cscs.ch

More information

A Topology-Aware Performance Monitoring Tool for Shared Resource Management in Multicore Systems

A Topology-Aware Performance Monitoring Tool for Shared Resource Management in Multicore Systems A Topology-Aware Performance Monitoring Tool for Shared Resource Management in Multicore Systems TADaaM Team - Nicolas Denoyelle - Brice Goglin - Emmanuel Jeannot August 24, 2015 1. Context/Motivations

More information

Building Clusters for Gromacs and other HPC applications

Building Clusters for Gromacs and other HPC applications Building Clusters for Gromacs and other HPC applications Erik Lindahl lindahl@cbr.su.se CBR Outline: Clusters Clusters vs. small networks of machines Why do YOU need a cluster? Computer hardware Network

More information

Rethinking SIMD Vectorization for In-Memory Databases

Rethinking SIMD Vectorization for In-Memory Databases SIGMOD 215, Melbourne, Victoria, Australia Rethinking SIMD Vectorization for In-Memory Databases Orestis Polychroniou Columbia University Arun Raghavan Oracle Labs Kenneth A. Ross Columbia University Latest

More information

Intel Xeon 5500 Memory Performance Ganesh Balakrishnan System x and BladeCenter Performance

Intel Xeon 5500 Memory Performance Ganesh Balakrishnan System x and BladeCenter Performance Intel Memory Performance Ganesh Balakrishnan System x and BladeCenter Performance 1 ABSTRACT...3 1.0 INTRODUCTION...3 2.0 SYSTEM ARCHITECTURE...4 2.1 HS22...4 2.2 X3650 M2, X3550 M2, IDATAPLEX 2.0...5

More information

New to servers. Are you new to servers? Consider these HP ProLiant Essentials servers. Family guide HP ProLiant rack and tower servers

New to servers. Are you new to servers? Consider these HP ProLiant Essentials servers. Family guide HP ProLiant rack and tower servers New to servers Are you new to servers? Consider these HP ProLiant Essentials servers. MicroServer Gen8 Micro-sized server for collaboration, centralization, and command of your business with remote management

More information

CORRIGENDUM TO TENDER FOR HIGH PERFORMANCE SERVER

CORRIGENDUM TO TENDER FOR HIGH PERFORMANCE SERVER CORRIGENDUM TO TENDER FOR HIGH PERFORMANCE SERVER Tender Notice No. 3/2014-15 dated 29.12.2014 (IIT/CE/ENQ/COM/HPC/2014-15/569) Tender Submission Deadline Last date for submission of sealed bids is extended

More information

High Performance Computing in the Multi-core Area

High Performance Computing in the Multi-core Area High Performance Computing in the Multi-core Area Arndt Bode Technische Universität München Technology Trends for Petascale Computing Architectures: Multicore Accelerators Special Purpose Reconfigurable

More information

Michael Kagan. michael@mellanox.com

Michael Kagan. michael@mellanox.com Virtualization in Data Center The Network Perspective Michael Kagan CTO, Mellanox Technologies michael@mellanox.com Outline Data Center Transition Servers S as a Service Network as a Service IO as a Service

More information

Performance Analysis of a Hybrid MPI/OpenMP Application on Multi-core Clusters

Performance Analysis of a Hybrid MPI/OpenMP Application on Multi-core Clusters Performance Analysis of a Hybrid MPI/OpenMP Application on Multi-core Clusters Martin J. Chorley a, David W. Walker a a School of Computer Science and Informatics, Cardiff University, Cardiff, UK Abstract

More information

Lecture 2 Parallel Programming Platforms

Lecture 2 Parallel Programming Platforms Lecture 2 Parallel Programming Platforms Flynn s Taxonomy In 1966, Michael Flynn classified systems according to numbers of instruction streams and the number of data stream. Data stream Single Multiple

More information

4 th Workshop on Big Data Benchmarking

4 th Workshop on Big Data Benchmarking 4 th Workshop on Big Data Benchmarking MPP SQL Engines: architectural choices and their implications on benchmarking 09 Oct 2013 Agenda: Big Data Landscape Market Requirements Benchmark Parameters Benchmark

More information

Abaqus Performance Benchmark and Profiling. March 2015

Abaqus Performance Benchmark and Profiling. March 2015 Abaqus 6.14-2 Performance Benchmark and Profiling March 2015 2 Note The following research was performed under the HPC Advisory Council activities Special thanks for: HP, Mellanox For more information

More information

Application and Micro-benchmark Performance using MVAPICH2-X on SDSC Gordon Cluster

Application and Micro-benchmark Performance using MVAPICH2-X on SDSC Gordon Cluster Application and Micro-benchmark Performance using MVAPICH2-X on SDSC Gordon Cluster Mahidhar Tatineni (mahidhar@sdsc.edu) MVAPICH User Group Meeting August 27, 2014 NSF grants: OCI #0910847 Gordon: A Data

More information

ECLIPSE Best Practices Performance, Productivity, Efficiency. March 2009

ECLIPSE Best Practices Performance, Productivity, Efficiency. March 2009 ECLIPSE Best Practices Performance, Productivity, Efficiency March 29 ECLIPSE Performance, Productivity, Efficiency The following research was performed under the HPC Advisory Council activities HPC Advisory

More information

Module 2: "Parallel Computer Architecture: Today and Tomorrow" Lecture 4: "Shared Memory Multiprocessors" The Lecture Contains: Technology trends

Module 2: Parallel Computer Architecture: Today and Tomorrow Lecture 4: Shared Memory Multiprocessors The Lecture Contains: Technology trends The Lecture Contains: Technology trends Architectural trends Exploiting TLP: NOW Supercomputers Exploiting TLP: Shared memory Shared memory MPs Bus-based MPs Scaling: DSMs On-chip TLP Economics Summary

More information

HP SN1000E 16 Gb Fibre Channel HBA Evaluation

HP SN1000E 16 Gb Fibre Channel HBA Evaluation HP SN1000E 16 Gb Fibre Channel HBA Evaluation Evaluation report prepared under contract with Emulex Executive Summary The computing industry is experiencing an increasing demand for storage performance

More information

Chapter 2 Parallel Architecture, Software And Performance

Chapter 2 Parallel Architecture, Software And Performance Chapter 2 Parallel Architecture, Software And Performance UCSB CS140, T. Yang, 2014 Modified from texbook slides Roadmap Parallel hardware Parallel software Input and output Performance Parallel program

More information

RAID 5 rebuild performance in ProLiant

RAID 5 rebuild performance in ProLiant RAID 5 rebuild performance in ProLiant technology brief Abstract... 2 Overview of the RAID 5 rebuild process... 2 Estimating the mean-time-to-failure (MTTF)... 3 Factors affecting RAID 5 array rebuild

More information

Parallel Large-Scale Visualization

Parallel Large-Scale Visualization Parallel Large-Scale Visualization Aaron Birkland Cornell Center for Advanced Computing Data Analysis on Ranger January 2012 Parallel Visualization Why? Performance Processing may be too slow on one CPU

More information

Oracle Exadata: The World s Fastest Database Machine Exadata Database Machine Architecture

Oracle Exadata: The World s Fastest Database Machine Exadata Database Machine Architecture Oracle Exadata: The World s Fastest Database Machine Exadata Database Machine Architecture Ron Weiss, Exadata Product Management Exadata Database Machine Best Platform to Run the

More information

Exploiting Remote Memory Operations to Design Efficient Reconfiguration for Shared Data-Centers over InfiniBand

Exploiting Remote Memory Operations to Design Efficient Reconfiguration for Shared Data-Centers over InfiniBand Exploiting Remote Memory Operations to Design Efficient Reconfiguration for Shared Data-Centers over InfiniBand P. Balaji, K. Vaidyanathan, S. Narravula, K. Savitha, H. W. Jin D. K. Panda Network Based

More information

HP ProLiant DL580 Gen8 and HP LE PCIe Workload WHITE PAPER Accelerator 90TB Microsoft SQL Server Data Warehouse Fast Track Reference Architecture

HP ProLiant DL580 Gen8 and HP LE PCIe Workload WHITE PAPER Accelerator 90TB Microsoft SQL Server Data Warehouse Fast Track Reference Architecture WHITE PAPER HP ProLiant DL580 Gen8 and HP LE PCIe Workload WHITE PAPER Accelerator 90TB Microsoft SQL Server Data Warehouse Fast Track Reference Architecture Based on Microsoft SQL Server 2014 Data Warehouse

More information

SGI. High Throughput Computing (HTC) Wrapper Program for Bioinformatics on SGI ICE and SGI UV Systems. January, 2012. Abstract. Haruna Cofer*, PhD

SGI. High Throughput Computing (HTC) Wrapper Program for Bioinformatics on SGI ICE and SGI UV Systems. January, 2012. Abstract. Haruna Cofer*, PhD White Paper SGI High Throughput Computing (HTC) Wrapper Program for Bioinformatics on SGI ICE and SGI UV Systems Haruna Cofer*, PhD January, 2012 Abstract The SGI High Throughput Computing (HTC) Wrapper

More information

Multi-core Systems What can we buy today?

Multi-core Systems What can we buy today? Multi-core Systems What can we buy today? Ian Watson & Mikel Lujan Advanced Processor Technologies Group COMP60012 Future Multi-core Computing 1 A Bit of History AMD Opteron introduced in 2003 Hypertransport

More information

Benchmarking Guide. Performance. BlackBerry Enterprise Server for Microsoft Exchange. Version: 5.0 Service Pack: 4

Benchmarking Guide. Performance. BlackBerry Enterprise Server for Microsoft Exchange. Version: 5.0 Service Pack: 4 BlackBerry Enterprise Server for Microsoft Exchange Version: 5.0 Service Pack: 4 Performance Benchmarking Guide Published: 2015-01-13 SWD-20150113132750479 Contents 1 BlackBerry Enterprise Server for Microsoft

More information

How System Settings Impact PCIe SSD Performance

How System Settings Impact PCIe SSD Performance How System Settings Impact PCIe SSD Performance Suzanne Ferreira R&D Engineer Micron Technology, Inc. July, 2012 As solid state drives (SSDs) continue to gain ground in the enterprise server and storage

More information

Hadoop on the Gordon Data Intensive Cluster

Hadoop on the Gordon Data Intensive Cluster Hadoop on the Gordon Data Intensive Cluster Amit Majumdar, Scientific Computing Applications Mahidhar Tatineni, HPC User Services San Diego Supercomputer Center University of California San Diego Dec 18,

More information

A Study on the Scalability of Hybrid LS-DYNA on Multicore Architectures

A Study on the Scalability of Hybrid LS-DYNA on Multicore Architectures 11 th International LS-DYNA Users Conference Computing Technology A Study on the Scalability of Hybrid LS-DYNA on Multicore Architectures Yih-Yih Lin Hewlett-Packard Company Abstract In this paper, the

More information

Big Data Technologies for Ultra-High-Speed Data Transfer and Processing

Big Data Technologies for Ultra-High-Speed Data Transfer and Processing White Paper Intel Xeon Processor E5 Family Big Data Analytics Cloud Computing Solutions Big Data Technologies for Ultra-High-Speed Data Transfer and Processing Using Technologies from Aspera and Intel

More information

Performance Characteristics of VMFS and RDM VMware ESX Server 3.0.1

Performance Characteristics of VMFS and RDM VMware ESX Server 3.0.1 Performance Study Performance Characteristics of and RDM VMware ESX Server 3.0.1 VMware ESX Server offers three choices for managing disk access in a virtual machine VMware Virtual Machine File System

More information

RAMCloud and the Low- Latency Datacenter. John Ousterhout Stanford University

RAMCloud and the Low- Latency Datacenter. John Ousterhout Stanford University RAMCloud and the Low- Latency Datacenter John Ousterhout Stanford University Most important driver for innovation in computer systems: Rise of the datacenter Phase 1: large scale Phase 2: low latency Introduction

More information

Cluster Sanity Checks

Cluster Sanity Checks Cluster Sanity Checks Christian Terboven terboven@rz.rwth aachen.de Center for Computing and Communication RWTH Aachen University Windows HPC Deployment September 19, RWTH Aachen Agenda o Motivation o

More information

The Uintah Framework: A Unified Heterogeneous Task Scheduling and Runtime System

The Uintah Framework: A Unified Heterogeneous Task Scheduling and Runtime System The Uintah Framework: A Unified Heterogeneous Task Scheduling and Runtime System Qingyu Meng, Alan Humphrey, Martin Berzins Thanks to: John Schmidt and J. Davison de St. Germain, SCI Institute Justin Luitjens

More information

Technical Paper. Moving SAS Applications from a Physical to a Virtual VMware Environment

Technical Paper. Moving SAS Applications from a Physical to a Virtual VMware Environment Technical Paper Moving SAS Applications from a Physical to a Virtual VMware Environment Release Information Content Version: April 2015. Trademarks and Patents SAS Institute Inc., SAS Campus Drive, Cary,

More information

Large-Scale Reservoir Simulation and Big Data Visualization

Large-Scale Reservoir Simulation and Big Data Visualization Large-Scale Reservoir Simulation and Big Data Visualization Dr. Zhangxing John Chen NSERC/Alberta Innovates Energy Environment Solutions/Foundation CMG Chair Alberta Innovates Technology Future (icore)

More information

Symmetric Multiprocessing

Symmetric Multiprocessing Multicore Computing A multi-core processor is a processing system composed of two or more independent cores. One can describe it as an integrated circuit to which two or more individual processors (called

More information

Fusion iomemory iodrive PCIe Application Accelerator Performance Testing

Fusion iomemory iodrive PCIe Application Accelerator Performance Testing WHITE PAPER Fusion iomemory iodrive PCIe Application Accelerator Performance Testing SPAWAR Systems Center Atlantic Cary Humphries, Steven Tully and Karl Burkheimer 2/1/2011 Product testing of the Fusion

More information

Clustering Billions of Data Points Using GPUs

Clustering Billions of Data Points Using GPUs Clustering Billions of Data Points Using GPUs Ren Wu ren.wu@hp.com Bin Zhang bin.zhang2@hp.com Meichun Hsu meichun.hsu@hp.com ABSTRACT In this paper, we report our research on using GPUs to accelerate

More information

An Evaluation of OpenMP on Current and Emerging Multithreaded/Multicore Processors

An Evaluation of OpenMP on Current and Emerging Multithreaded/Multicore Processors An Evaluation of OpenMP on Current and Emerging Multithreaded/Multicore Processors Matthew Curtis-Maury, Xiaoning Ding, Christos D. Antonopoulos, and Dimitrios S. Nikolopoulos The College of William &

More information

High Performance Data-Transfers in Grid Environment using GridFTP over InfiniBand

High Performance Data-Transfers in Grid Environment using GridFTP over InfiniBand High Performance Data-Transfers in Grid Environment using GridFTP over InfiniBand Hari Subramoni *, Ping Lai *, Raj Kettimuthu **, Dhabaleswar. K. (DK) Panda * * Computer Science and Engineering Department

More information

Agenda. HPC Software Stack. HPC Post-Processing Visualization. Case Study National Scientific Center. European HPC Benchmark Center Montpellier PSSC

Agenda. HPC Software Stack. HPC Post-Processing Visualization. Case Study National Scientific Center. European HPC Benchmark Center Montpellier PSSC HPC Architecture End to End Alexandre Chauvin Agenda HPC Software Stack Visualization National Scientific Center 2 Agenda HPC Software Stack Alexandre Chauvin Typical HPC Software Stack Externes LAN Typical

More information

Agility Database Scalability Testing

Agility Database Scalability Testing Agility Database Scalability Testing V1.6 November 11, 2012 Prepared by on behalf of Table of Contents 1 Introduction... 4 1.1 Brief... 4 2 Scope... 5 3 Test Approach... 6 4 Test environment setup... 7

More information

COMP 422, Lecture 3: Physical Organization & Communication Costs in Parallel Machines (Sections 2.4 & 2.5 of textbook)

COMP 422, Lecture 3: Physical Organization & Communication Costs in Parallel Machines (Sections 2.4 & 2.5 of textbook) COMP 422, Lecture 3: Physical Organization & Communication Costs in Parallel Machines (Sections 2.4 & 2.5 of textbook) Vivek Sarkar Department of Computer Science Rice University vsarkar@rice.edu COMP

More information

FLOW-3D Performance Benchmark and Profiling. September 2012

FLOW-3D Performance Benchmark and Profiling. September 2012 FLOW-3D Performance Benchmark and Profiling September 2012 Note The following research was performed under the HPC Advisory Council activities Participating vendors: FLOW-3D, Dell, Intel, Mellanox Compute

More information

Unstructured Data Accelerator (UDA) Author: Motti Beck, Mellanox Technologies Date: March 27, 2012

Unstructured Data Accelerator (UDA) Author: Motti Beck, Mellanox Technologies Date: March 27, 2012 Unstructured Data Accelerator (UDA) Author: Motti Beck, Mellanox Technologies Date: March 27, 2012 1 Market Trends Big Data Growing technology deployments are creating an exponential increase in the volume

More information

The Transition to PCI Express* for Client SSDs

The Transition to PCI Express* for Client SSDs The Transition to PCI Express* for Client SSDs Amber Huffman Senior Principal Engineer Intel Santa Clara, CA 1 *Other names and brands may be claimed as the property of others. Legal Notices and Disclaimers

More information