RWTH GPU Cluster. Sandra Wienke November Rechen- und Kommunikationszentrum (RZ) Fotos: Christian Iwainsky
|
|
- Jayson Stevenson
- 8 years ago
- Views:
Transcription
1 RWTH GPU Cluster Fotos: Christian Iwainsky Sandra Wienke November 2012 Rechen- und Kommunikationszentrum (RZ)
2 The RWTH GPU Cluster GPU Cluster: 57 Nvidia Quadro 6000 (Fermi) innovative computer architecture High utilization of resources Daytime VR: new CAVE (49 GPUs) HPC: interactive software development (8 GPUs) Nighttime aixcave, VR, RWTH Aachen, since June 2012 HPC: Processing of GPGPU compute jobs (55-57 GPUs) 2
3 Hardware stack 4 dialogue nodes 24 rendering nodes 1 head node Name linuxgpud[1-4] linuxgpus[01-24] linuxgpum1 Devices # 2 1 details/gpu NVIDIA Quadro 6000 (Fermi) 448 cores 1.15 GHz 6 GB RAM ECC on max. GFlops: (SP), (DP) Host processor 2 x Intel Xeon X5650 EP (Westmere) (12-core 2.67GHz Network RAM 24 GB 48 GB QDR InfiniBand 3
4 Software stack Environment as on compute cluster (modules, ) CUDA Toolkit: 5.0 (4.1, 4.0, 3.2) CUDA OpenCL (1.0) PGI Compiler module load cuda directory: $CUDA_ROOT CUDA Fortran PGI Accelerator Model module load pgi (module switch intel pgi) PGI OpenACC CUDA Debugging TotalView module load totalview Eclipse 4
5 How to use? Interactive mode Short runs/tests only, debugging 1 dialogue node (linuxgpud1): 24/7 2 dialogue nodes (linuxgpud[2,3]): Mon Fri, 8am 8pm Batch mode No interaction, commands are queued + scheduled For performance tests, long runs 24+1 rendering nodes 2 dialogue nodes Mon Fri, 8pm 8am; Sat + Son, whole day 1 dialogue node (linuxgpud4): Mon Fri, 8am 8pm for short test runs during daytime Note: reboot at switch from interactive to batch mode 5
6 How to use: Interactive mode You must be in group gpu to get access to GPU Cluster ( ) Jump from frontend cluster node to GPU dialogue node: ssh Y linuxgpud[1-3] GPUs are set to exclusive mode (per process) Only one person can access GPU If occupied, e.g. message all CUDA-capable devices are busy or unavailable If not set a certain device in (CUDA) code, automatically scheduled to other GPU within node (if available) Debugging Be aware: debugger run usually on GPU with ID 0 (fails if GPU is occupied) 6
7 See what is running: nvidia-smi linuxgpud1$> nvidia-smi Mon Oct 17 12:41: NVIDIA-SMI Driver Version: GPU ID + type nvidia-smi q Lists GPU details display mode Nb. Name Bus Id Disp. Volatile ECC SB / DB Fan Temp Power Usage /Cap Memory Usage GPU Util. Compute M. ===============================+======================+====================== 0. Quadro :02:00.0 Off % 80 C P0 Off / Off 4% 208MB / 5375MB 99% E. Process Quadro :85:00.0 On % 84 C P8 Off / Off 0% 22MB / 5375MB 0% E. Process Compute processes: GPU Memory GPU PID Process name Usage ============================================================================= process running on GPU ECC (SB: single bit, DB: double bit) compute mode: 1 person (1 process) nbody 196MB
8 How to use: Batch mode Create batch compute job for LSF Select appropriate queue to get scheduled on GPU-cluster q gpu Exclusive nodes Nodes are allocated exclusively at least 2 GPUs for one job Please use resources reasonably! Submit your job bsub < mygpuscript.sh Starts running as soon as: batch mode starts and job is scheduled Display pending reason: bjobs p During daytime: Dispatch windows closed More documentation Reminder: Only one node in batch mode on daytime (for testing): -a gpu (instead of -g gpu) (-q is given priority to -a) 8 RWTH Compute Cluster User s Guide Unix-Cluster Documentation
9 Batch script for single GPU (node) usage #!/usr/bin/env zsh ### Job name #BSUB -J GPUTest-Cuda ### File / path where STDOUT & STDERR will be written to #BSUB -o gputest-cuda.o%j ### Request GPU Queue #BSUB -q gpu ### Request the time you need for execution in [hour:]minute #BSUB -W 15 ### Request virtual memory (in MB) #BSUB -M 512 module load cuda/40 CUDA code needs the whole virtual address space of the node Currently, we disabled the memory limit for the gpu queue cd $HOME/NVIDIA_GPU_Computing_SDK_4.0.17/C/bin/linux/release devicequery -noprompt 9
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 informationThe RWTH Compute Cluster Environment
The RWTH Compute Cluster Environment Tim Cramer 11.03.2013 Source: D. Both, Bull GmbH Rechen- und Kommunikationszentrum (RZ) How to login Frontends cluster.rz.rwth-aachen.de cluster-x.rz.rwth-aachen.de
More informationGPU Tools Sandra Wienke
Sandra Wienke Center for Computing and Communication, RWTH Aachen University MATSE HPC Battle 2012/13 Rechen- und Kommunikationszentrum (RZ) Agenda IDE Eclipse Debugging (CUDA) TotalView Profiling (CUDA
More informationThe Asterope compute cluster
The Asterope compute cluster ÅA has a small cluster named asterope.abo.fi with 8 compute nodes Each node has 2 Intel Xeon X5650 processors (6-core) with a total of 24 GB RAM 2 NVIDIA Tesla M2050 GPGPU
More informationIntroduction to Hybrid Programming
Introduction to Hybrid Programming Hristo Iliev Rechen- und Kommunikationszentrum aixcelerate 2012 / Aachen 10. Oktober 2012 Version: 1.1 Rechen- und Kommunikationszentrum (RZ) Motivation for hybrid programming
More informationAdvanced MPI. Hybrid programming, profiling and debugging of MPI applications. Hristo Iliev RZ. Rechen- und Kommunikationszentrum (RZ)
Advanced MPI Hybrid programming, profiling and debugging of MPI applications Hristo Iliev RZ Rechen- und Kommunikationszentrum (RZ) Agenda Halos (ghost cells) Hybrid programming Profiling of MPI applications
More informationCUDA Debugging. GPGPU Workshop, August 2012. Sandra Wienke Center for Computing and Communication, RWTH Aachen University
CUDA Debugging GPGPU Workshop, August 2012 Sandra Wienke Center for Computing and Communication, RWTH Aachen University Nikolay Piskun, Chris Gottbrath Rogue Wave Software Rechen- und Kommunikationszentrum
More informationGPU 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 informationHPC-Nutzer Informationsaustausch. The Workload Management System LSF
HPC-Nutzer Informationsaustausch The Workload Management System LSF Content Cluster facts Job submission esub messages Scheduling strategies Tools and security Future plans 2 von 10 Some facts about the
More informationParallel Processing using the LOTUS cluster
Parallel Processing using the LOTUS cluster Alison Pamment / Cristina del Cano Novales JASMIN/CEMS Workshop February 2015 Overview Parallelising data analysis LOTUS HPC Cluster Job submission on LOTUS
More informationA quick tutorial on Intel's Xeon Phi Coprocessor
A quick tutorial on Intel's Xeon Phi Coprocessor www.cism.ucl.ac.be damien.francois@uclouvain.be Architecture Setup Programming The beginning of wisdom is the definition of terms. * Name Is a... As opposed
More informationParallel 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 informationOverview of HPC systems and software available within
Overview of HPC systems and software available within Overview Available HPC Systems Ba Cy-Tera Available Visualization Facilities Software Environments HPC System at Bibliotheca Alexandrina SUN cluster
More informationDebugging with TotalView
Tim Cramer 17.03.2015 IT Center der RWTH Aachen University Why to use a Debugger? If your program goes haywire, you may... ( wand (... buy a magic... read the source code again and again and...... enrich
More informationCluster Monitoring and Management Tools RAJAT PHULL, NVIDIA SOFTWARE ENGINEER ROB TODD, NVIDIA SOFTWARE ENGINEER
Cluster Monitoring and Management Tools RAJAT PHULL, NVIDIA SOFTWARE ENGINEER ROB TODD, NVIDIA SOFTWARE ENGINEER MANAGE GPUS IN THE CLUSTER Administrators, End users Middleware Engineers Monitoring/Management
More informationUsing NeSI HPC Resources. NeSI Computational Science Team (support@nesi.org.nz)
NeSI Computational Science Team (support@nesi.org.nz) Outline 1 About Us About NeSI Our Facilities 2 Using the Cluster Suitable Work What to expect Parallel speedup Data Getting to the Login Node 3 Submitting
More informationThe RWTH HPC-Cluster User's Guide Version 8.2.2
The RWTH HPC-Cluster User's Guide Version 8.2.2 Release: May 2012 Build: May 22, 2012 Dieter an Mey, Christian Terboven, Paul Kapinos, Dirk Schmidl, Sandra Wienke, Tim Cramer Michael Wirtz Rechen- und
More informationAccelerating Simulation & Analysis with Hybrid GPU Parallelization and Cloud Computing
Accelerating Simulation & Analysis with Hybrid GPU Parallelization and Cloud Computing Innovation Intelligence Devin Jensen August 2012 Altair Knows HPC Altair is the only company that: makes HPC tools
More informationIntroduction to Linux and Cluster Basics for the CCR General Computing Cluster
Introduction to Linux and Cluster Basics for the CCR General Computing Cluster Cynthia Cornelius Center for Computational Research University at Buffalo, SUNY 701 Ellicott St Buffalo, NY 14203 Phone: 716-881-8959
More informationOpenMP 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 informationA GPU COMPUTING PLATFORM (SAGA) AND A CFD CODE ON GPU FOR AEROSPACE APPLICATIONS
A GPU COMPUTING PLATFORM (SAGA) AND A CFD CODE ON GPU FOR AEROSPACE APPLICATIONS SUDHAKARAN.G APCF, AERO, VSSC, ISRO 914712564742 g_suhakaran@vssc.gov.in THOMAS.C.BABU APCF, AERO, VSSC, ISRO 914712565833
More informationGRID VGPU FOR VMWARE VSPHERE
GRID VGPU FOR VMWARE VSPHERE DU-07354-001 March 2015 Quick Start Guide DOCUMENT CHANGE HISTORY DU-07354-001 Version Date Authors Description of Change 0.1 7/1/2014 AC Initial draft for vgpu early access
More informationInformationsaustausch für Nutzer des Aachener HPC Clusters
Informationsaustausch für Nutzer des Aachener HPC Clusters Paul Kapinos, Marcus Wagner - 21.05.2015 Informationsaustausch für Nutzer des Aachener HPC Clusters Agenda (The RWTH Compute cluster) Project-based
More informationArcGIS Pro: Virtualizing in Citrix XenApp and XenDesktop. Emily Apsey Performance Engineer
ArcGIS Pro: Virtualizing in Citrix XenApp and XenDesktop Emily Apsey Performance Engineer Presentation Overview What it takes to successfully virtualize ArcGIS Pro in Citrix XenApp and XenDesktop - Shareable
More informationIntroduction to GPU Computing
Matthis Hauschild Universität Hamburg Fakultät für Mathematik, Informatik und Naturwissenschaften Technische Aspekte Multimodaler Systeme December 4, 2014 M. Hauschild - 1 Table of Contents 1. Architecture
More informationThe Top Six Advantages of CUDA-Ready Clusters. Ian Lumb Bright Evangelist
The Top Six Advantages of CUDA-Ready Clusters Ian Lumb Bright Evangelist GTC Express Webinar January 21, 2015 We scientists are time-constrained, said Dr. Yamanaka. Our priority is our research, not managing
More informationAccelerating CFD using OpenFOAM with GPUs
Accelerating CFD using OpenFOAM with GPUs Authors: Saeed Iqbal and Kevin Tubbs The OpenFOAM CFD Toolbox is a free, open source CFD software package produced by OpenCFD Ltd. Its user base represents a wide
More informationPurchase of High Performance Computing (HPC) Central Compute Resources by Northwestern Researchers
Information Technology Purchase of High Performance Computing (HPC) Central Compute Resources by Northwestern Researchers Effective for FY2016 Purpose This document summarizes High Performance Computing
More informationIntroduction to Running Computations on the High Performance Clusters at the Center for Computational Research
! Introduction to Running Computations on the High Performance Clusters at the Center for Computational Research! Cynthia Cornelius! Center for Computational Research University at Buffalo, SUNY! cdc at
More informationUsing 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 informationThe High Performance Internet of Things: using GVirtuS for gluing cloud computing and ubiquitous connected devices
WS on Models, Algorithms and Methodologies for Hierarchical Parallelism in new HPC Systems The High Performance Internet of Things: using GVirtuS for gluing cloud computing and ubiquitous connected devices
More informationNVIDIA CUDA GETTING STARTED GUIDE FOR MAC OS X
NVIDIA CUDA GETTING STARTED GUIDE FOR MAC OS X DU-05348-001_v5.5 July 2013 Installation and Verification on Mac OS X TABLE OF CONTENTS Chapter 1. Introduction...1 1.1. System Requirements... 1 1.2. About
More informationNVIDIA CUDA GETTING STARTED GUIDE FOR MICROSOFT WINDOWS
NVIDIA CUDA GETTING STARTED GUIDE FOR MICROSOFT WINDOWS DU-05349-001_v6.0 February 2014 Installation and Verification on TABLE OF CONTENTS Chapter 1. Introduction...1 1.1. System Requirements... 1 1.2.
More informationOpenACC Basics Directive-based GPGPU Programming
OpenACC Basics Directive-based GPGPU Programming Sandra Wienke, M.Sc. wienke@rz.rwth-aachen.de Center for Computing and Communication RWTH Aachen University Rechen- und Kommunikationszentrum (RZ) PPCES,
More informationKeeneland Enabling Heterogeneous Computing for the Open Science Community Philip C. Roth Oak Ridge National Laboratory
Keeneland Enabling Heterogeneous Computing for the Open Science Community Philip C. Roth Oak Ridge National Laboratory with contributions from the Keeneland project team and partners 2 NSF Office of Cyber
More informationOverview. Lecture 1: an introduction to CUDA. Hardware view. Hardware view. hardware view software view CUDA programming
Overview Lecture 1: an introduction to CUDA Mike Giles mike.giles@maths.ox.ac.uk hardware view software view Oxford University Mathematical Institute Oxford e-research Centre Lecture 1 p. 1 Lecture 1 p.
More informationVisualization Cluster Getting Started
Visualization Cluster Getting Started Contents 1 Introduction to the Visualization Cluster... 1 2 Visualization Cluster hardware and software... 2 3 Remote visualization session through VNC... 2 4 Starting
More informationResource Scheduling Best Practice in Hybrid Clusters
Available online at www.prace-ri.eu Partnership for Advanced Computing in Europe Resource Scheduling Best Practice in Hybrid Clusters C. Cavazzoni a, A. Federico b, D. Galetti a, G. Morelli b, A. Pieretti
More informationIntroduction to GPU Programming Languages
CSC 391/691: GPU Programming Fall 2011 Introduction to GPU Programming Languages Copyright 2011 Samuel S. Cho http://www.umiacs.umd.edu/ research/gpu/facilities.html Maryland CPU/GPU Cluster Infrastructure
More informationCORRIGENDUM 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 informationProgramming models for heterogeneous computing. Manuel Ujaldón Nvidia CUDA Fellow and A/Prof. Computer Architecture Department University of Malaga
Programming models for heterogeneous computing Manuel Ujaldón Nvidia CUDA Fellow and A/Prof. Computer Architecture Department University of Malaga Talk outline [30 slides] 1. Introduction [5 slides] 2.
More informationHPC Cluster Decisions and ANSYS Configuration Best Practices. Diana Collier Lead Systems Support Specialist Houston UGM May 2014
HPC Cluster Decisions and ANSYS Configuration Best Practices Diana Collier Lead Systems Support Specialist Houston UGM May 2014 1 Agenda Introduction Lead Systems Support Specialist Cluster Decisions Job
More informationIntroduction to HPC Workshop. Center for e-research (eresearch@nesi.org.nz)
Center for e-research (eresearch@nesi.org.nz) Outline 1 About Us About CER and NeSI The CS Team Our Facilities 2 Key Concepts What is a Cluster Parallel Programming Shared Memory Distributed Memory 3 Using
More informationParallel Computing using MATLAB Distributed Compute Server ZORRO HPC
Parallel Computing using MATLAB Distributed Compute Server ZORRO HPC Goals of the session Overview of parallel MATLAB Why parallel MATLAB? Multiprocessing in MATLAB Parallel MATLAB using the Parallel Computing
More informationNVIDIA CUDA GETTING STARTED GUIDE FOR MAC OS X
NVIDIA CUDA GETTING STARTED GUIDE FOR MAC OS X DU-05348-001_v6.5 August 2014 Installation and Verification on Mac OS X TABLE OF CONTENTS Chapter 1. Introduction...1 1.1. System Requirements... 1 1.2. About
More informationHigh Performance Computing in CST STUDIO SUITE
High Performance Computing in CST STUDIO SUITE Felix Wolfheimer GPU Computing Performance Speedup 18 16 14 12 10 8 6 4 2 0 Promo offer for EUC participants: 25% discount for K40 cards Speedup of Solver
More informationClusters with GPUs under Linux and Windows HPC
Clusters with GPUs under Linux and Windows HPC Massimiliano Fatica (NVIDIA), Calvin Clark (Microsoft) Hillsborough Room Oct 2 2009 Agenda Overview Requirements for GPU Computing Linux clusters Windows
More informationHETEROGENEOUS HPC, ARCHITECTURE OPTIMIZATION, AND NVLINK
HETEROGENEOUS HPC, ARCHITECTURE OPTIMIZATION, AND NVLINK Steve Oberlin CTO, Accelerated Computing US to Build Two Flagship Supercomputers SUMMIT SIERRA Partnership for Science 100-300 PFLOPS Peak Performance
More informationApplications to Computational Financial and GPU Computing. May 16th. Dr. Daniel Egloff +41 44 520 01 17 +41 79 430 03 61
F# Applications to Computational Financial and GPU Computing May 16th Dr. Daniel Egloff +41 44 520 01 17 +41 79 430 03 61 Today! Why care about F#? Just another fashion?! Three success stories! How Alea.cuBase
More informationOpenPOWER Outlook AXEL KOEHLER SR. SOLUTION ARCHITECT HPC
OpenPOWER Outlook AXEL KOEHLER SR. SOLUTION ARCHITECT HPC Driving industry innovation The goal of the OpenPOWER Foundation is to create an open ecosystem, using the POWER Architecture to share expertise,
More informationStreamline Computing Linux Cluster User Training. ( Nottingham University)
1 Streamline Computing Linux Cluster User Training ( Nottingham University) 3 User Training Agenda System Overview System Access Description of Cluster Environment Code Development Job Schedulers Running
More informationXID ERRORS. vr352 May 2015. XID Errors
ID ERRORS vr352 May 2015 ID Errors Introduction... 1 1.1. What Is an id Message... 1 1.2. How to Use id Messages... 1 Working with id Errors... 2 2.1. Viewing id Error Messages... 2 2.2. Tools That Provide
More informationRetargeting PLAPACK to Clusters with Hardware Accelerators
Retargeting PLAPACK to Clusters with Hardware Accelerators Manuel Fogué 1 Francisco Igual 1 Enrique S. Quintana-Ortí 1 Robert van de Geijn 2 1 Departamento de Ingeniería y Ciencia de los Computadores.
More informationHow To Build A Supermicro Computer With A 32 Core Power Core (Powerpc) And A 32-Core (Powerpc) (Powerpowerpter) (I386) (Amd) (Microcore) (Supermicro) (
TECHNICAL GUIDELINES FOR APPLICANTS TO PRACE 7 th CALL (Tier-0) Contributing sites and the corresponding computer systems for this call are: GCS@Jülich, Germany IBM Blue Gene/Q GENCI@CEA, France Bull Bullx
More informationUsing WestGrid. Patrick Mann, Manager, Technical Operations Jan.15, 2014
Using WestGrid Patrick Mann, Manager, Technical Operations Jan.15, 2014 Winter 2014 Seminar Series Date Speaker Topic 5 February Gino DiLabio Molecular Modelling Using HPC and Gaussian 26 February Jonathan
More informationOverview on Modern Accelerators and Programming Paradigms Ivan Giro7o igiro7o@ictp.it
Overview on Modern Accelerators and Programming Paradigms Ivan Giro7o igiro7o@ictp.it Informa(on & Communica(on Technology Sec(on (ICTS) Interna(onal Centre for Theore(cal Physics (ICTP) Mul(ple Socket
More informationST810 Advanced Computing
ST810 Advanced Computing Lecture 17: Parallel computing part I Eric B. Laber Hua Zhou Department of Statistics North Carolina State University Mar 13, 2013 Outline computing Hardware computing overview
More information1 DCSC/AU: HUGE. DeIC Sekretariat 2013-03-12/RB. Bilag 1. DeIC (DCSC) Scientific Computing Installations
Bilag 1 2013-03-12/RB DeIC (DCSC) Scientific Computing Installations DeIC, previously DCSC, currently has a number of scientific computing installations, distributed at five regional operating centres.
More informationHP 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 informationPerformance 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 informationHigh Productivity Computing With Windows
High Productivity Computing With Windows Windows HPC Server 2008 Justin Alderson 16-April-2009 Agenda The purpose of computing is... The purpose of computing is insight not numbers. Richard Hamming Why
More information5x in 5 hours Porting SEISMIC_CPML using the PGI Accelerator Model
5x in 5 hours Porting SEISMIC_CPML using the PGI Accelerator Model C99, C++, F2003 Compilers Optimizing Vectorizing Parallelizing Graphical parallel tools PGDBG debugger PGPROF profiler Intel, AMD, NVIDIA
More informationHybrid Cluster Management: Reducing Stress, increasing productivity and preparing for the future
Hybrid Cluster Management: Reducing Stress, increasing productivity and preparing for the future Clement Lau, Ph. D. Sales Director, APJ Bright Computing Agenda 1.Reduce 2.IncRease 3.PrepaRe Reduce System
More informationCluster performance, how to get the most out of Abel. Ole W. Saastad, Dr.Scient USIT / UAV / FI April 18 th 2013
Cluster performance, how to get the most out of Abel Ole W. Saastad, Dr.Scient USIT / UAV / FI April 18 th 2013 Introduction Architecture x86-64 and NVIDIA Compilers MPI Interconnect Storage Batch queue
More informationMartinos Center Compute Clusters
Intro What are the compute clusters How to gain access Housekeeping Usage Log In Submitting Jobs Queues Request CPUs/vmem Email Status I/O Interactive Dependencies Daisy Chain Wrapper Script In Progress
More informationTOOLS AND TIPS FOR MANAGING A GPU CLUSTER. Adam DeConinck HPC Systems Engineer, NVIDIA
TOOLS AND TIPS FOR MANAGING A GPU CLUSTER Adam DeConinck HPC Systems Engineer, NVIDIA Steps for configuring a GPU cluster Select compute node hardware Configure your compute nodes Set up your cluster for
More informationTurbomachinery CFD on many-core platforms experiences and strategies
Turbomachinery CFD on many-core platforms experiences and strategies Graham Pullan Whittle Laboratory, Department of Engineering, University of Cambridge MUSAF Colloquium, CERFACS, Toulouse September 27-29
More informationHodor and Bran - Job Scheduling and PBS Scripts
Hodor and Bran - Job Scheduling and PBS Scripts UND Computational Research Center Now that you have your program compiled and your input file ready for processing, it s time to run your job on the cluster.
More informationParallel Computing with MATLAB
Parallel Computing with MATLAB Scott Benway Senior Account Manager Jiro Doke, Ph.D. Senior Application Engineer 2013 The MathWorks, Inc. 1 Acceleration Strategies Applied in MATLAB Approach Options Best
More informationIntroduction to GPGPU. Tiziano Diamanti t.diamanti@cineca.it
t.diamanti@cineca.it Agenda From GPUs to GPGPUs GPGPU architecture CUDA programming model Perspective projection Vectors that connect the vanishing point to every point of the 3D model will intersecate
More informationDebugging in Heterogeneous Environments with TotalView. ECMWF HPC Workshop 30 th October 2014
Debugging in Heterogeneous Environments with TotalView ECMWF HPC Workshop 30 th October 2014 Agenda Introduction Challenges TotalView overview Advanced features Current work and future plans 2014 Rogue
More informationProgramming the Intel Xeon Phi Coprocessor
Programming the Intel Xeon Phi Coprocessor Tim Cramer cramer@rz.rwth-aachen.de Rechen- und Kommunikationszentrum (RZ) Agenda Motivation Many Integrated Core (MIC) Architecture Programming Models Native
More informationAssessing 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 informationSystem Requirements Table of contents
Table of contents 1 Introduction... 2 2 Knoa Agent... 2 2.1 System Requirements...2 2.2 Environment Requirements...4 3 Knoa Server Architecture...4 3.1 Knoa Server Components... 4 3.2 Server Hardware Setup...5
More informationPedraforca: ARM + GPU prototype
www.bsc.es Pedraforca: ARM + GPU prototype Filippo Mantovani Workshop on exascale and PRACE prototypes Barcelona, 20 May 2014 Overview Goals: Test the performance, scalability, and energy efficiency of
More informationIntroduction to Running Hadoop on the High Performance Clusters at the Center for Computational Research
Introduction to Running Hadoop on the High Performance Clusters at the Center for Computational Research Cynthia Cornelius Center for Computational Research University at Buffalo, SUNY 701 Ellicott St
More informationBiowulf2 Training Session
Biowulf2 Training Session 9 July 2015 Slides at: h,p://hpc.nih.gov/docs/b2training.pdf HPC@NIH website: h,p://hpc.nih.gov System hardware overview What s new/different The batch system & subminng jobs
More informationSLURM Workload Manager
SLURM Workload Manager What is SLURM? SLURM (Simple Linux Utility for Resource Management) is the native scheduler software that runs on ASTI's HPC cluster. Free and open-source job scheduler for the Linux
More informationPerformance Characteristics of Large SMP Machines
Performance Characteristics of Large SMP Machines Dirk Schmidl, Dieter an Mey, Matthias S. Müller schmidl@rz.rwth-aachen.de Rechen- und Kommunikationszentrum (RZ) Agenda Investigated Hardware Kernel Benchmark
More informationParallel Debugging with DDT
Parallel Debugging with DDT Nate Woody 3/10/2009 www.cac.cornell.edu 1 Debugging Debugging is a methodical process of finding and reducing the number of bugs, or defects, in a computer program or a piece
More informationHPC Wales Skills Academy Course Catalogue 2015
HPC Wales Skills Academy Course Catalogue 2015 Overview The HPC Wales Skills Academy provides a variety of courses and workshops aimed at building skills in High Performance Computing (HPC). Our courses
More informationOptimizing GPU-based application performance for the HP for the HP ProLiant SL390s G7 server
Optimizing GPU-based application performance for the HP for the HP ProLiant SL390s G7 server Technology brief Introduction... 2 GPU-based computing... 2 ProLiant SL390s GPU-enabled architecture... 2 Optimizing
More informationA general-purpose virtualization service for HPC on cloud computing: an application to GPUs
A general-purpose virtualization service for HPC on cloud computing: an application to GPUs R.Montella, G.Coviello, G.Giunta* G. Laccetti #, F. Isaila, J. Garcia Blas *Department of Applied Science University
More informationBuilding a Top500-class Supercomputing Cluster at LNS-BUAP
Building a Top500-class Supercomputing Cluster at LNS-BUAP Dr. José Luis Ricardo Chávez Dr. Humberto Salazar Ibargüen Dr. Enrique Varela Carlos Laboratorio Nacional de Supercómputo Benemérita Universidad
More informationAccelerating From Cluster to Cloud: Overview of RDMA on Windows HPC. Wenhao Wu Program Manager Windows HPC team
Accelerating From Cluster to Cloud: Overview of RDMA on Windows HPC Wenhao Wu Program Manager Windows HPC team Agenda Microsoft s Commitments to HPC RDMA for HPC Server RDMA for Storage in Windows 8 Microsoft
More informationGPU File System Encryption Kartik Kulkarni and Eugene Linkov
GPU File System Encryption Kartik Kulkarni and Eugene Linkov 5/10/2012 SUMMARY. We implemented a file system that encrypts and decrypts files. The implementation uses the AES algorithm computed through
More informationGPGPU accelerated Computational Fluid Dynamics
t e c h n i s c h e u n i v e r s i t ä t b r a u n s c h w e i g Carl-Friedrich Gauß Faculty GPGPU accelerated Computational Fluid Dynamics 5th GACM Colloquium on Computational Mechanics Hamburg Institute
More informationBrainlab Node TM Technical Specifications
Brainlab Node TM Technical Specifications BRAINLAB NODE TM HP ProLiant DL360p Gen 8 CPU: Chipset: RAM: HDD: RAID: Graphics: LAN: HW Monitoring: Height: Width: Length: Weight: Operating System: 2x Intel
More informationHigh Performance Computing Infrastructure at DESY
High Performance Computing Infrastructure at DESY Sven Sternberger & Frank Schlünzen High Performance Computing Infrastructures at DESY DV-Seminar / 04 Feb 2013 Compute Infrastructures at DESY - Outline
More informationHPC Software Requirements to Support an HPC Cluster Supercomputer
HPC Software Requirements to Support an HPC Cluster Supercomputer Susan Kraus, Cray Cluster Solutions Software Product Manager Maria McLaughlin, Cray Cluster Solutions Product Marketing Cray Inc. WP-CCS-Software01-0417
More informationWindows HPC Server 2008 Deployment
Windows HPC Server 2008 Michael Wirtz wirtz@rz.rwth-aachen.de Rechen- und Kommunikationszentrum RWTH Aachen Windows-HPC 2008 19. Sept 08, RWTH Aachen Windows HPC Server 2008 - Agenda o eines 2 Knoten Clusters
More informationExperiences with Tools at NERSC
Experiences with Tools at NERSC Richard Gerber NERSC User Services Programming weather, climate, and earth- system models on heterogeneous mul>- core pla?orms September 7, 2011 at the Na>onal Center for
More informationCaltech Center for Advanced Computing Research System Guide: MRI2 Cluster (zwicky) January 2014
1. How to Get An Account CACR Accounts 2. How to Access the Machine Connect to the front end, zwicky.cacr.caltech.edu: ssh -l username zwicky.cacr.caltech.edu or ssh username@zwicky.cacr.caltech.edu Edits,
More informationHigh 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 informationIntroduction to GP-GPUs. Advanced Computer Architectures, Cristina Silvano, Politecnico di Milano 1
Introduction to GP-GPUs Advanced Computer Architectures, Cristina Silvano, Politecnico di Milano 1 GPU Architectures: How do we reach here? NVIDIA Fermi, 512 Processing Elements (PEs) 2 What Can It Do?
More informationInstallation Guide. (Version 2014.1) Midland Valley Exploration Ltd 144 West George Street Glasgow G2 2HG United Kingdom
Installation Guide (Version 2014.1) Midland Valley Exploration Ltd 144 West George Street Glasgow G2 2HG United Kingdom Tel: +44 (0) 141 3322681 Fax: +44 (0) 141 3326792 www.mve.com Table of Contents 1.
More informationAn 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 informationIBM Platform Computing : infrastructure management for HPC solutions on OpenPOWER Jing Li, Software Development Manager IBM
IBM Platform Computing : infrastructure management for HPC solutions on OpenPOWER Jing Li, Software Development Manager IBM #OpenPOWERSummit Join the conversation at #OpenPOWERSummit 1 Scale-out and Cloud
More informationJUROPA Linux Cluster An Overview. 19 May 2014 Ulrich Detert
Mitglied der Helmholtz-Gemeinschaft JUROPA Linux Cluster An Overview 19 May 2014 Ulrich Detert JuRoPA JuRoPA Jülich Research on Petaflop Architectures Bull, Sun, ParTec, Intel, Mellanox, Novell, FZJ JUROPA
More information