ASC Workshop Catalogue Brochure CSIRO ASC Version 1.0 August 2, 2013
|
|
- Christal Patrick
- 7 years ago
- Views:
Transcription
1 INFORMATION MANAGEMENT AND TECHNOLOGY ASC Workshop Catalogue Brochure CSIRO ASC Version 1.0 August 2, 2013 Commercial In Confidence
2 CSIRO Advanced Scientific Computing GPO Box 1289, Melbourne, Victoria 3001, Australia Telephone : Fax : Copyright and disclaimer 2013, CSIRO CSIRO To the extent permitted by law, all rights are reserved and no part of this publication covered by copyright may be reproduced or copied in any form or by any means except with the written permission of CSIRO. Important disclaimer CSIRO advises that the information contained in this publication comprises general statements based on scientific research. The reader is advised and needs to be aware that such information may be incomplete or unable to be used in any specific situation. No reliance or actions must therefore be made on that information without seeking prior expert professional, scientific and technical advice. To the extent permitted by law, CSIRO (including its employees and consultants) excludes all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this publication (in part or in whole) and any information or material contained in it.
3 CONTENTS 1 ASC Workshops 2 2 Introductory Courses Audience Introduction to CSIRO s Advanced Scientific Computing Facilities Intermediate and Language Specific Courses Audience High Performance Computing in C/C++ & Fortran High Performance Computing in Python High Performance Computing in R Accelerator Programming with OpenACC Advanced Courses Audience Advanced Topics in Program Optimisation and Parallelisation Heterogeneous Programming with CUDA & OpenCL i
4 ii
5 ASC Workshop Catalogue Brochure, Release 1.0 This document lists the HPC training courses provided by IM&T s Advanced Scientific Computing group. CONTENTS 1
6 CHAPTER ONE ASC WORKSHOPS Do you want your scientific computing to run hundreds of times faster? Do you have a shelf full of external hard drives to manage your data and no tools for management or protection of your data? Are you interested in parallel programming but don t know where to start? If you answered yes, then one of our free workshops is for you. At eresearch Accelerated Computing Workshops you will meet members of IM&T s Advanced Scientific Computing team, learn about the CSIRO high performance scientific computing services on offer, and how to take advantage of vast compute resources and virtually unlimited storage. ASC s multi-day hands-on workshops cover a number of topics in High Performance Computing (HPC) including: CSIRO s high performance computing capabilities Data management Profiling and optimising your applications Parallel programming theory and tools Code debugging Accelerator theory and programming We also provide programming language specific coverage of these HPC topics in: C/C++ & Fortran R statistical package Python CUDA OpenCL OpenACC For further information see the ASC workshop website. 2
7 CHAPTER TWO INTRODUCTORY COURSES 2.1 Audience These workshops provide fairly low-level, tutorial style, exposure to topics of HPC, computational science, and the use of ASC systems. They are targeted at researchers and others who may need to: 1. Run scientific or numerical software in a HPC environment 2. Manage data on HPC systems 3. Develop or modify scripts to launch jobs in a batch system These workshops are not intended as a high level overview of high performance or scientific computing for managers, decision makers, or others with such interests, nor are they intended to be a conference style workshop consisting of science project presentations. If you are interested in HPC workshops and conferences you should consider the CSIRO CSS/eResearch annual conference and the eresearch Australasia conference. 2.2 Introduction to CSIRO s Advanced Scientific Computing Facilities Skills Acquired Basic understanding of modern Supercomputers Logging into remote Linux systems using commandline and VNC desktops Running jobs through Supercomputer batch systems Basic data management and software access on CSIRO Supercomputers Running simple parallel workflows using a batch system Course Content What is a Supercomputer Introduction to IM&T Advanced Scientific Computing The HPC Environment 3
8 ASC Workshop Catalogue Brochure, Release 1.0 Accessing Linux systems using Secure Shell (ssh/putty) Accessing Linux systems using Virtual Network Computing (VNC) The batch system Running jobs through the Portable Batch System (PBS) Data management Accessing software and tools Compiling & debugging programs Simple parallel batch execution and parametric sweeps Other ASC services 2.2. Introduction to CSIRO s Advanced Scientific Computing Facilities 4
9 CHAPTER THREE INTERMEDIATE AND LANGUAGE SPECIFIC COURSES 3.1 Audience These workshops provide fairly low-level, tutorial style, exposure to topics of HPC, computational science, parallel programming, and the use of ASC systems. They are targeted at researchers and other individuals who may need to: 1. Develop or modify programs that are computationally or data intensive 2. Use or modify scientific / numerical software written by another party 3. Develop or modify scripts to control workflows on a cluster These workshops are not intended as a high level overview of high performance or scientific computing for managers, decision makers, or others with such interests, nor are they intended to be a conference style workshop consisting of science project presentations. If you are interested in HPC workshops and conferences you should consider the CSIRO CSS/eResearch annual conference and the eresearch Australasia conference. 3.2 High Performance Computing in C/C++ & Fortran Prerequisites Introduction to CSIRO s Advanced Scientific Computing Facilities (co-requisite) This course is most often presented in conjunction with the C/C++ and Fortran course Skills Acquired Basic principals of performance tuning and parallel processing Program Debugging Performance profiling Multi-core parallel programming using OpenMP Multi-node (Supercomputer) parallel programming using MPI 5
10 ASC Workshop Catalogue Brochure, Release 1.0 Launching parallel jobs through Supercomputer batch systems Course Content Entire Introduction to CSIRO s Advanced Scientific Computing Facilities Course Introduction to profiling Parallel programming principals 101 What is parallel/concurrent programming Job parallelism Shared memory parallelism Distributed memory parallelism Problem decomposition Implicit parallelism using third party libraries Explicit parallel programming in C/C++ & Fortran Job parallel programming using the batch system Shared memory parallel programming using OpenMP Distributed memory parallel programming using MPI 3.3 High Performance Computing in Python Prerequisites Introduction to CSIRO s Advanced Scientific Computing Facilities (co-requisite) This course is most often presented in conjunction with the Python course Skills Acquired Basic principals of performance tuning and parallel processing Performance profiling in Python Accessing accelerated support libraries from Python Multi-core parallel programming using Python Multi-node (Supercomputer) parallel programming using Python Launching parallel Python jobs through Supercomputer batch systems Course Content Entire Introduction to CSIRO s Advanced Scientific Computing Facilities Course Introduction to profiling Parallel programming principals 101 What is parallel/concurrent programming 3.3. High Performance Computing in Python 6
11 ASC Workshop Catalogue Brochure, Release 1.0 Job parallelism Shared memory parallelism Distributed memory parallelism Problem decomposition Implicit parallelism using third party libraries Explicit parallel programming in Python Job parallel programming using the batch system Shared memory parallel programming Distributed memory parallel programming 3.4 High Performance Computing in R Prerequisites Introduction to CSIRO s Advanced Scientific Computing Facilities (co-requisite) This course is most often presented in conjunction with the R course Skills Acquired Basic principals of performance tuning and parallel processing Performance profiling in R Accessing accelerated support libraries from R Multi-core parallel programming in R Multi-node (Supercomputer) parallel programming in R R to C++ offloading using Rcpp Launching parallel R jobs through supercomputer batch systems Course Content Entire Introduction to CSIRO s Advanced Scientific Computing Facilities Course Introduction to profiling Parallel programming principals 101 What is parallel/concurrent programming Job parallelism Shared memory parallelism Distributed memory parallelism Problem decomposition Implicit parallelism using third party libraries Explicit parallel programming in R 3.4. High Performance Computing in R 7
12 ASC Workshop Catalogue Brochure, Release 1.0 Job parallel programming using the batch system Shared memory parallel programming Distributed memory parallel programming using Rmpi/SNOW Accelerating R programs using C++ offloading and Rcpp package 3.5 Accelerator Programming with OpenACC Prerequisites High Performance Computing in C/C++ & Fortran (recommended prerequisite) Completion of this course is HIGHLY recommended prior to attending the OpenACC course. It will likely include the follow co-requisite in its content Introduction to CSIRO s Advanced Scientific Computing Facilities (co-requisite) For those that opt not to attend the above prerequisite, this course is recommended. It might be presented in conjunction with the OpenACC course on rare occasions Skills Acquired Basic understanding of accelerator architecture and threading model Understanding of directive based acceleration and parallel programming Writing simple OpenACC code to offloading work to an accelerator Managing data movement and placement to and on accelerators in OpenACC Compiling OpenACC code Understanding of compiler actions and the cause/solution to unexpected behaviour Course Content Introduction to accelerators and massively multi-core architectures Directive based parallel programming OpenACC vs OpenMP Writing OpenACC programs Parallel and Kernel regions Variable and Region control clauses * Shared and non-shared variables * Avoiding race conditions * Efficient data movement in accelerator programming Compiling and running OpenACC code * * * Selection of target architecture Displaying and understanding compiler actions Simple OpenACC timing 3.5. Accelerator Programming with OpenACC 8
13 ASC Workshop Catalogue Brochure, Release 1.0 Reductions 3.5. Accelerator Programming with OpenACC 9
14 CHAPTER FOUR ADVANCED COURSES Advanced courses can be provided on request and if demand is sufficient. Given these courses are delivered less often, we can customise their content to specific needs given sufficient audience size. 4.1 Audience These workshops provide fairly low-level, tutorial style, exposure to topics of HPC, computational science, parallel programming, and the use of ASC systems. They are targeted at researchers and other individuals who may need to: 1. Develop or modify programs that are computationally or data intensive 2. Use or modify scientific / numerical software written by another party 3. Develop or modify scripts to control workflows on a cluster These workshops are not intended as a high level overview of high performance or scientific computing for managers, decision makers, or others with such interests, nor are they intended to be a conference style workshop consisting of science project presentations. If you are interested in HPC workshops and conferences you should consider the CSIRO CSS/eResearch annual conference and the eresearch Australasia conference. 4.2 Advanced Topics in Program Optimisation and Parallelisation Prerequisites High Performance Computing in C/C++ & Fortran (prerequisite) Completion of this course is MANDITORY prior to attending the OpenACC course. It will likely include the follow co-requisite in its content Introduction to CSIRO s Advanced Scientific Computing Facilities (co-requisite) This co-requisite will likely be included in the above prerequisite. Otherwise contact ASC staff. 10
15 ASC Workshop Catalogue Brochure, Release Course Content Content is flexible and customisable. Topics may include: Scheduling principles in parallel programming Advanced functionalities of OpenMP and OpenMPI Performance profiling of single and multi-node parallel programs Profiling of MPI communications Debugging of parallel programs CPU code optimisation Efficient cache and memory access Code/Instruction path optimisations 4.3 Heterogeneous Programming with CUDA & OpenCL Prerequisites High Performance Computing in C/C++ & Fortran (prerequisite) Completion of this course is MANDITORY prior to attending the OpenACC course. It will likely include the follow co-requisite in its content Introduction to CSIRO s Advanced Scientific Computing Facilities (co-requisite) This co-requisite will likely be included in the above prerequisite. Otherwise contact ASC staff Skills Acquired Understanding of GPU achitecture and threading model Programming kernels in CUDA and OpenCL Achieving efficient data movement and placement with GPU devices Compiling CUDA and OpenCL programs Profiling and debugging CUDA and OpenCL programs Writing parallel programs over heterogeneous processor by mixing CPU & GPU parallel programing technologies Course Content Content is flexible and customisable. Topics may include: Introduction to NVIDIA GPU architectures Considerations in SIMD execution models Existing GPU enabled libraries CUDA and OpenCL threading models Appropriate problems and decomposition 4.3. Heterogeneous Programming with CUDA & OpenCL 11
16 ASC Workshop Catalogue Brochure, Release 1.0 Profiling GPU programs Debugging GPU programs Exploiting GPU memory hierarchy Advanced optimisations on NVIDIA GPUs Heterogeneous parallel programs Hybrib MPI+GPU for distributed memory clusters Hybrid OpenMP+GPU for heterogeneous workstations 4.3. Heterogeneous Programming with CUDA & OpenCL 12
17
18 CONTACT US t e enquiries@csiro.au w YOUR CSIRO Australia is founding its future on science and innovation. Its national science agency, CSIRO, is a powerhouse of ideas, technologies and skills for building prosperity, growth, health and sustainability. It serves governments, industries, business and communities across the nation. FOR FURTHER INFORMATION CSIRO Information Management and Technology Luke Domanski t e luke.domanski@csiro.au w Advanced Scientific Computing CSIRO Information Management and Technology Sam Moskwa t e sam.moskwa@csiro.au w Advanced Scientific Computing
HPC 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 informationPart I Courses Syllabus
Part I Courses Syllabus This document provides detailed information about the basic courses of the MHPC first part activities. The list of courses is the following 1.1 Scientific Programming Environment
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 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 informationHIGH PERFORMANCE CONSULTING COURSE OFFERINGS
Performance 1(6) HIGH PERFORMANCE CONSULTING COURSE OFFERINGS LEARN TO TAKE ADVANTAGE OF POWERFUL GPU BASED ACCELERATOR TECHNOLOGY TODAY 2006 2013 Nvidia GPUs Intel CPUs CONTENTS Acronyms and Terminology...
More informationGPU Hardware and Programming Models. Jeremy Appleyard, September 2015
GPU Hardware and Programming Models Jeremy Appleyard, September 2015 A brief history of GPUs In this talk Hardware Overview Programming Models Ask questions at any point! 2 A Brief History of GPUs 3 Once
More informationGPUs for Scientific Computing
GPUs for Scientific Computing p. 1/16 GPUs for Scientific Computing Mike Giles mike.giles@maths.ox.ac.uk Oxford-Man Institute of Quantitative Finance Oxford University Mathematical Institute Oxford e-research
More informationUnleashing the Performance Potential of GPUs for Atmospheric Dynamic Solvers
Unleashing the Performance Potential of GPUs for Atmospheric Dynamic Solvers Haohuan Fu haohuan@tsinghua.edu.cn High Performance Geo-Computing (HPGC) Group Center for Earth System Science Tsinghua University
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 informationCase 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 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 information22S:295 Seminar in Applied Statistics High Performance Computing in Statistics
22S:295 Seminar in Applied Statistics High Performance Computing in Statistics Luke Tierney Department of Statistics & Actuarial Science University of Iowa August 30, 2007 Luke Tierney (U. of Iowa) HPC
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 informationBIG CPU, BIG DATA. Solving the World s Toughest Computational Problems with Parallel Computing. Alan Kaminsky
Solving the World s Toughest Computational Problems with Parallel Computing Solving the World s Toughest Computational Problems with Parallel Computing Department of Computer Science B. Thomas Golisano
More informationBIG CPU, BIG DATA. Solving the World s Toughest Computational Problems with Parallel Computing. Alan Kaminsky
Solving the World s Toughest Computational Problems with Parallel Computing Alan Kaminsky Solving the World s Toughest Computational Problems with Parallel Computing Alan Kaminsky Department of Computer
More informationIntegrated Communication Systems
Integrated Communication Systems Courses, Research, and Thesis Topics Prof. Paul Müller University of Kaiserslautern Department of Computer Science Integrated Communication Systems ICSY http://www.icsy.de
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 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 informationCUDA programming on NVIDIA GPUs
p. 1/21 on NVIDIA GPUs Mike Giles mike.giles@maths.ox.ac.uk Oxford University Mathematical Institute Oxford-Man Institute for Quantitative Finance Oxford eresearch Centre p. 2/21 Overview hardware view
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 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 informationBLM 413E - Parallel Programming Lecture 3
BLM 413E - Parallel Programming Lecture 3 FSMVU Bilgisayar Mühendisliği Öğr. Gör. Musa AYDIN 14.10.2015 2015-2016 M.A. 1 Parallel Programming Models Parallel Programming Models Overview There are several
More informationA Pattern-Based Comparison of OpenACC & OpenMP for Accelerators
A Pattern-Based Comparison of OpenACC & OpenMP for Accelerators Sandra Wienke 1,2, Christian Terboven 1,2, James C. Beyer 3, Matthias S. Müller 1,2 1 IT Center, RWTH Aachen University 2 JARA-HPC, Aachen
More informationUsing the Intel Xeon Phi (with the Stampede Supercomputer) ISC 13 Tutorial
Using the Intel Xeon Phi (with the Stampede Supercomputer) ISC 13 Tutorial Bill Barth, Kent Milfeld, Dan Stanzione Tommy Minyard Texas Advanced Computing Center Jim Jeffers, Intel June 2013, Leipzig, Germany
More informationOverview of HPC Resources at Vanderbilt
Overview of HPC Resources at Vanderbilt Will French Senior Application Developer and Research Computing Liaison Advanced Computing Center for Research and Education June 10, 2015 2 Computing Resources
More informationProgram Grid and HPC5+ workshop
Program Grid and HPC5+ workshop 24-30, Bahman 1391 Tuesday Wednesday 9.00-9.45 9.45-10.30 Break 11.00-11.45 11.45-12.30 Lunch 14.00-17.00 Workshop Rouhani Karimi MosalmanTabar Karimi G+MMT+K Opening IPM_Grid
More informationNext Generation GPU Architecture Code-named Fermi
Next Generation GPU Architecture Code-named Fermi The Soul of a Supercomputer in the Body of a GPU Why is NVIDIA at Super Computing? Graphics is a throughput problem paint every pixel within frame time
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 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 informationOpenACC Programming and Best Practices Guide
OpenACC Programming and Best Practices Guide June 2015 2015 openacc-standard.org. All Rights Reserved. Contents 1 Introduction 3 Writing Portable Code........................................... 3 What
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 informationMaximize 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 informationRecent and Future Activities in HPC and Scientific Data Management Siegfried Benkner
Recent and Future Activities in HPC and Scientific Data Management Siegfried Benkner Research Group Scientific Computing Faculty of Computer Science University of Vienna AUSTRIA http://www.par.univie.ac.at
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 informationThe Fastest Way to Parallel Programming for Multicore, Clusters, Supercomputers and the Cloud.
White Paper 021313-3 Page 1 : A Software Framework for Parallel Programming* The Fastest Way to Parallel Programming for Multicore, Clusters, Supercomputers and the Cloud. ABSTRACT Programming for Multicore,
More informationIntroduction to GPU hardware and to CUDA
Introduction to GPU hardware and to CUDA Philip Blakely Laboratory for Scientific Computing, University of Cambridge Philip Blakely (LSC) GPU introduction 1 / 37 Course outline Introduction to GPU hardware
More informationDavid Rioja Redondo Telecommunication Engineer Englobe Technologies and Systems
David Rioja Redondo Telecommunication Engineer Englobe Technologies and Systems About me David Rioja Redondo Telecommunication Engineer - Universidad de Alcalá >2 years building and managing clusters UPM
More informationMulticore 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 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 informationHigh 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 informationPerformance Analysis for GPU Accelerated Applications
Center for Information Services and High Performance Computing (ZIH) Performance Analysis for GPU Accelerated Applications Working Together for more Insight Willersbau, Room A218 Tel. +49 351-463 - 39871
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 informationDenis Caromel, CEO Ac.veEon. Orchestrate and Accelerate Applica.ons. Open Source Cloud Solu.ons Hybrid Cloud: Private with Burst Capacity
Cloud computing et Virtualisation : applications au domaine de la Finance Denis Caromel, CEO Ac.veEon Orchestrate and Accelerate Applica.ons Open Source Cloud Solu.ons Hybrid Cloud: Private with Burst
More informationThree Paths to Faster Simulations Using ANSYS Mechanical 16.0 and Intel Architecture
White Paper Intel Xeon processor E5 v3 family Intel Xeon Phi coprocessor family Digital Design and Engineering Three Paths to Faster Simulations Using ANSYS Mechanical 16.0 and Intel Architecture Executive
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 informationThe Lattice Project: A Multi-Model Grid Computing System. Center for Bioinformatics and Computational Biology University of Maryland
The Lattice Project: A Multi-Model Grid Computing System Center for Bioinformatics and Computational Biology University of Maryland Parallel Computing PARALLEL COMPUTING a form of computation in which
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 informationKalray MPPA Massively Parallel Processing Array
Kalray MPPA Massively Parallel Processing Array Next-Generation Accelerated Computing February 2015 2015 Kalray, Inc. All Rights Reserved February 2015 1 Accelerated Computing 2015 Kalray, Inc. All Rights
More informationAn introduction to Fyrkat
Cluster Computing May 25, 2011 How to get an account https://fyrkat.grid.aau.dk/useraccount How to get help https://fyrkat.grid.aau.dk/wiki What is a Cluster Anyway It is NOT something that does any of
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 informationTrends in High-Performance Computing for Power Grid Applications
Trends in High-Performance Computing for Power Grid Applications Franz Franchetti ECE, Carnegie Mellon University www.spiral.net Co-Founder, SpiralGen www.spiralgen.com This talk presents my personal views
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 informationLe langage OCaml et la programmation des GPU
Le langage OCaml et la programmation des GPU GPU programming with OCaml Mathias Bourgoin - Emmanuel Chailloux - Jean-Luc Lamotte Le projet OpenGPU : un an plus tard Ecole Polytechnique - 8 juin 2011 Outline
More informationEvaluation of CUDA Fortran for the CFD code Strukti
Evaluation of CUDA Fortran for the CFD code Strukti Practical term report from Stephan Soller High performance computing center Stuttgart 1 Stuttgart Media University 2 High performance computing center
More informationRWTH 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 informationIntroducing PgOpenCL A New PostgreSQL Procedural Language Unlocking the Power of the GPU! By Tim Child
Introducing A New PostgreSQL Procedural Language Unlocking the Power of the GPU! By Tim Child Bio Tim Child 35 years experience of software development Formerly VP Oracle Corporation VP BEA Systems Inc.
More informationThe impact on superannuation fund balances from the new compulsory superannuation rate
DIGITAL PRODUCTIVITY AND SERVICES FLAGSHIP The impact on superannuation fund balances from the new compulsory superannuation rate Zili Zhu and Thomas Sneddon CSIRO Mathematics, Informatics and Statistics
More informationDesign and Optimization of a Portable Lattice Boltzmann Code for Heterogeneous Architectures
Design and Optimization of a Portable Lattice Boltzmann Code for Heterogeneous Architectures E Calore, S F Schifano, R Tripiccione Enrico Calore INFN Ferrara, Italy Perspectives of GPU Computing in Physics
More informationBSC vision on Big Data and extreme scale computing
BSC vision on Big Data and extreme scale computing Jesus Labarta, Eduard Ayguade,, Fabrizio Gagliardi, Rosa M. Badia, Toni Cortes, Jordi Torres, Adrian Cristal, Osman Unsal, David Carrera, Yolanda Becerra,
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 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 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 informationHPC Programming Framework Research Team
HPC Programming Framework Research Team 1. Team Members Naoya Maruyama (Team Leader) Motohiko Matsuda (Research Scientist) Soichiro Suzuki (Technical Staff) Mohamed Wahib (Postdoctoral Researcher) Shinichiro
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 informationThe GPU Accelerated Data Center. Marc Hamilton, August 27, 2015
The GPU Accelerated Data Center Marc Hamilton, August 27, 2015 THE GPU-ACCELERATED DATA CENTER HPC DEEP LEARNING PC VIRTUALIZATION CLOUD GAMING RENDERING 2 Product design FROM ADVANCED RENDERING TO VIRTUAL
More informationMIKE by DHI 2014 e sviluppi futuri
MIKE by DHI 2014 e sviluppi futuri Johan Hartnack Torino, 9-10 Ottobre 2013 Technology drivers/trends Smart devices Cloud computing Services vs. Products Technology drivers/trends Multiprocessor hardware
More informationProductivity and HPC. Erik Hagersten, CTO, Rogue Wave Software AB Developing parallel, data-intensive applications is hard. We make it easier.
Productivity and HPC Erik Hagersten, CTO, Rogue Wave Software AB Developing parallel, data-intensive applications is hard. We make it easier. Chief architect high-end servers Sun Microsystems 1994 1999
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 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 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 informationHPC with Multicore and GPUs
HPC with Multicore and GPUs Stan Tomov Electrical Engineering and Computer Science Department University of Tennessee, Knoxville CS 594 Lecture Notes March 4, 2015 1/18 Outline! Introduction - Hardware
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 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 informationMicrosoft Technical Computing The Advancement of Parallelism. Tom Quinn, Technical Computing Partner Manager
Presented at the COMSOL Conference 2010 Boston Microsoft Technical Computing The Advancement of Parallelism Tom Quinn, Technical Computing Partner Manager 21 1.2 x 10 New Bytes of Information in 2010 Source:
More informationIntroduction to grid technologies, parallel and cloud computing. Alaa Osama Allam Saida Saad Mohamed Mohamed Ibrahim Gaber
Introduction to grid technologies, parallel and cloud computing Alaa Osama Allam Saida Saad Mohamed Mohamed Ibrahim Gaber OUTLINES Grid Computing Parallel programming technologies (MPI- Open MP-Cuda )
More informationPerformance Tools. Tulin Kaman. tkaman@ams.sunysb.edu. Department of Applied Mathematics and Statistics
Performance Tools Tulin Kaman Department of Applied Mathematics and Statistics Stony Brook/BNL New York Center for Computational Science tkaman@ams.sunysb.edu Aug 24, 2012 Performance Tools Community Tools:
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 informationBig Data Visualization on the MIC
Big Data Visualization on the MIC Tim Dykes School of Creative Technologies University of Portsmouth timothy.dykes@port.ac.uk Many-Core Seminar Series 26/02/14 Splotch Team Tim Dykes, University of Portsmouth
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 informationSoftware Development around a Millisecond
Introduction Software Development around a Millisecond Geoffrey Fox In this column we consider software development methodologies with some emphasis on those relevant for large scale scientific computing.
More informationRecent Advances in HPC for Structural Mechanics Simulations
Recent Advances in HPC for Structural Mechanics Simulations 1 Trends in Engineering Driving Demand for HPC Increase product performance and integrity in less time Consider more design variants Find the
More informationNAS Parallel Benchmarks for GPGPUs using a Directive-based Programming Model
NAS Parallel Benchmarks for GPGPUs using a Directive-based Programming Model Rengan Xu, Xiaonan Tian, Sunita Chandrasekaran, Yonghong Yan, and Barbara Chapman Department of Computer Science, University
More informationMulti-core Programming System Overview
Multi-core Programming System Overview Based on slides from Intel Software College and Multi-Core Programming increasing performance through software multi-threading by Shameem Akhter and Jason Roberts,
More informationNVIDIA Tools For Profiling And Monitoring. David Goodwin
NVIDIA Tools For Profiling And Monitoring David Goodwin Outline CUDA Profiling and Monitoring Libraries Tools Technologies Directions CScADS Summer 2012 Workshop on Performance Tools for Extreme Scale
More informationIntroduction to ACENET Accelerating Discovery with Computational Research May, 2015
Introduction to ACENET Accelerating Discovery with Computational Research May, 2015 What is ACENET? What is ACENET? Shared regional resource for... high-performance computing (HPC) remote collaboration
More informationGPU Parallel Computing Architecture and CUDA Programming Model
GPU Parallel Computing Architecture and CUDA Programming Model John Nickolls Outline Why GPU Computing? GPU Computing Architecture Multithreading and Arrays Data Parallel Problem Decomposition Parallel
More informationOpenACC Parallelization and Optimization of NAS Parallel Benchmarks
OpenACC Parallelization and Optimization of NAS Parallel Benchmarks Presented by Rengan Xu GTC 2014, S4340 03/26/2014 Rengan Xu, Xiaonan Tian, Sunita Chandrasekaran, Yonghong Yan, Barbara Chapman HPC Tools
More informationIntroduction to parallel computing and UPPMAX
Introduction to parallel computing and UPPMAX Intro part of course in Parallel Image Analysis Elias Rudberg elias.rudberg@it.uu.se March 22, 2011 Parallel computing Parallel computing is becoming increasingly
More informationOpenACC 2.0 and the PGI Accelerator Compilers
OpenACC 2.0 and the PGI Accelerator Compilers Michael Wolfe The Portland Group michael.wolfe@pgroup.com This presentation discusses the additions made to the OpenACC API in Version 2.0. I will also present
More informationRetour d expérience : portage d une application haute-performance vers un langage de haut niveau
Retour d expérience : portage d une application haute-performance vers un langage de haut niveau ComPAS/RenPar 2013 Mathias Bourgoin - Emmanuel Chailloux - Jean-Luc Lamotte 16 Janvier 2013 Our Goals Globally
More informationSourcery Overview & Virtual Machine Installation
Sourcery Overview & Virtual Machine Installation Damian Rouson, Ph.D., P.E. Sourcery, Inc. www.sourceryinstitute.org Sourcery, Inc. About Us Sourcery, Inc., is a software consultancy founded by and for
More informationGPU for Scientific Computing. -Ali Saleh
1 GPU for Scientific Computing -Ali Saleh Contents Introduction What is GPU GPU for Scientific Computing K-Means Clustering K-nearest Neighbours When to use GPU and when not Commercial Programming GPU
More informationManjrasoft Market Oriented Cloud Computing Platform
Manjrasoft Market Oriented Cloud Computing Platform Aneka Aneka is a market oriented Cloud development and management platform with rapid application development and workload distribution capabilities.
More informationwww.xenon.com.au STORAGE HIGH SPEED INTERCONNECTS HIGH PERFORMANCE COMPUTING VISUALISATION GPU COMPUTING
www.xenon.com.au STORAGE HIGH SPEED INTERCONNECTS HIGH PERFORMANCE COMPUTING GPU COMPUTING VISUALISATION XENON Accelerating Exploration Mineral, oil and gas exploration is an expensive and challenging
More informationAuto-Tunning of Data Communication on Heterogeneous Systems
1 Auto-Tunning of Data Communication on Heterogeneous Systems Marc Jordà 1, Ivan Tanasic 1, Javier Cabezas 1, Lluís Vilanova 1, Isaac Gelado 1, and Nacho Navarro 1, 2 1 Barcelona Supercomputing Center
More informationProduct Training Services. Training Options and Procedures for JobScheduler and YADE
Product Services Product Services Options and Procedures for JobScheduler and YADE 2 Contents Product Services JobScheduler Levels Level: JobScheduler Operations Level: JobScheduler Installation Level:
More informationParallel Programming for Multi-Core, Distributed Systems, and GPUs Exercises
Parallel Programming for Multi-Core, Distributed Systems, and GPUs Exercises Pierre-Yves Taunay Research Computing and Cyberinfrastructure 224A Computer Building The Pennsylvania State University University
More informationMPI and Hybrid Programming Models. William Gropp www.cs.illinois.edu/~wgropp
MPI and Hybrid Programming Models William Gropp www.cs.illinois.edu/~wgropp 2 What is a Hybrid Model? Combination of several parallel programming models in the same program May be mixed in the same source
More informationSpring 2011 Prof. Hyesoon Kim
Spring 2011 Prof. Hyesoon Kim Today, we will study typical patterns of parallel programming This is just one of the ways. Materials are based on a book by Timothy. Decompose Into tasks Original Problem
More information