ASC Workshop Catalogue Brochure CSIRO ASC Version 1.0 August 2, 2013

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "ASC Workshop Catalogue Brochure CSIRO ASC Version 1.0 August 2, 2013"

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 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 w Advanced Scientific Computing CSIRO Information Management and Technology Sam Moskwa t e w Advanced Scientific Computing

HPC Wales Skills Academy Course Catalogue 2015

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 information

Part I Courses Syllabus

Part 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 information

Programming 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 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 information

Introduction to GPU Programming Languages

Introduction 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 information

HIGH PERFORMANCE CONSULTING COURSE OFFERINGS

HIGH 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 information

Unleashing the Performance Potential of GPUs for Atmospheric Dynamic Solvers

Unleashing 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 information

GPU Hardware and Programming Models. Jeremy Appleyard, September 2015

GPU 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 information

Tamás Budavári / The Johns Hopkins University

Tamás Budavári / The Johns Hopkins University PRACTICAL SCIENTIFIC ANALYSIS OF BIG DATA RUNNING IN PARALLEL / The Johns Hopkins University 2 Parallelism Data parallel Same processing on different pieces of data Task parallel Simultaneous processing

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

GPUs for Scientific Computing

GPUs 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 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

The Intel Parallel Computing Center at the University of Bristol. Simon McIntosh-Smith Department of Computer Science

The Intel Parallel Computing Center at the University of Bristol. Simon McIntosh-Smith Department of Computer Science The Intel Parallel Computing Center at the University of Bristol Simon McIntosh-Smith Department of Computer Science 1 ! Bristol's rich heritage in HPC The University of Bristol is one of the top HPC institutes

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

Overview on Modern Accelerators and Programming Paradigms Ivan Giro7o igiro7o@ictp.it

Overview 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 information

Integrated Communication Systems

Integrated 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 information

22S:295 Seminar in Applied Statistics High Performance Computing in Statistics

22S: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 information

Accelerating CST MWS Performance with GPU and MPI Computing. CST workshop series

Accelerating CST MWS Performance with GPU and MPI Computing.  CST workshop series Accelerating CST MWS Performance with GPU and MPI Computing www.cst.com CST workshop series 2010 1 Hardware Based Acceleration Techniques - Overview - Multithreading GPU Computing Distributed Computing

More information

BIG CPU, BIG DATA. Solving the World s Toughest Computational Problems with Parallel Computing. Alan Kaminsky

BIG 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 information

BIG CPU, BIG DATA. Solving the World s Toughest Computational Problems with Parallel Computing. Alan Kaminsky

BIG 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 information

Introduction to OpenACC Directives. Duncan Poole, NVIDIA Thomas Bradley, NVIDIA

Introduction to OpenACC Directives. Duncan Poole, NVIDIA Thomas Bradley, NVIDIA Introduction to OpenACC Directives Duncan Poole, NVIDIA Thomas Bradley, NVIDIA GPUs Reaching Broader Set of Developers 1,000,000 s 100,000 s Early Adopters Research Universities Supercomputing Centers

More information

Debugging 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 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 information

Overview. Lecture 1: an introduction to CUDA. Hardware view. Hardware view. hardware view software view CUDA programming

Overview. 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 information

BLM 413E - Parallel Programming Lecture 3

BLM 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 information

Wisecracker A high performance distributed cryptanalysis framework

Wisecracker A high performance distributed cryptanalysis framework Wisecracker A high performance distributed cryptanalysis framework A Technical White Paper October 30 2012 Written by Vikas N Kumar Introduction Cryptanalysis can be performed in various ways such as by

More information

CUDA programming on NVIDIA GPUs

CUDA 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 information

Motivation and Goal. Introduction to HPC content and definitions. Learning Outcomes. Organization

Motivation and Goal. Introduction to HPC content and definitions. Learning Outcomes. Organization Motivation and Goal Introduction to HPC content and definitions Jan Thorbecke, Section of Applied Geophysics Get familiar with hardware building blocks, how they operate, and how to make use of them in

More information

Accelerating Simulation & Analysis with Hybrid GPU Parallelization and Cloud Computing

Accelerating 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 information

Introduction to High Performance Computing

Introduction to High Performance Computing Introduction to High Performance Computing Gregory G. Howes Department of Physics and Astronomy University of Iowa Iowa High Performance Computing Summer School University of Iowa Iowa City, Iowa 6-8 June

More information

Program Grid and HPC5+ workshop

Program 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 information

Next Generation GPU Architecture Code-named Fermi

Next 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 information

Using Microsoft Visual Studio 2005 / 2008

Using Microsoft Visual Studio 2005 / 2008 Using Visual Studio 2005 / 2008 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 o The

More information

NVIDIA CUDA GETTING STARTED GUIDE FOR MAC OS X

NVIDIA 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 information

Optimizing Performance of Parallel Programs on

Optimizing Performance of Parallel Programs on C-DAC & IIT Madras Five-Day Technology Workshop Programme ON Optimizing Performance of Parallel Programs on Emerging Multi-Core Processors and & GPUs OPECG-2009 Venue : Indian Institute of Technology Madras

More information

Introduction to GPU hardware and to CUDA

Introduction 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 information

Overview of HPC Resources at Vanderbilt

Overview 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 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

Parallel Computing with MATLAB

Parallel 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 information

The Top Six Advantages of CUDA-Ready Clusters. Ian Lumb Bright Evangelist

The 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 information

A Pattern-Based Comparison of OpenACC & OpenMP for Accelerators

A 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 information

Applications to Computational Financial and GPU Computing. May 16th. Dr. Daniel Egloff +41 44 520 01 17 +41 79 430 03 61

Applications 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 information

Using WestGrid. Patrick Mann, Manager, Technical Operations Jan.15, 2014

Using 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 information

David Rioja Redondo Telecommunication Engineer Englobe Technologies and Systems

David 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 information

Using the Intel Xeon Phi (with the Stampede Supercomputer) ISC 13 Tutorial

Using 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 information

The Fastest Way to Parallel Programming for Multicore, Clusters, Supercomputers and the Cloud.

The 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 information

Shattering the 1U Server Performance Record. Figure 1: Supermicro Product and Market Opportunity Growth

Shattering the 1U Server Performance Record. Figure 1: Supermicro Product and Market Opportunity Growth Shattering the 1U Server Performance Record Supermicro and NVIDIA recently announced a new class of servers that combines massively parallel GPUs with multi-core CPUs in a single server system. This unique

More information

OpenACC Programming and Best Practices Guide

OpenACC 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 information

Recent and Future Activities in HPC and Scientific Data Management Siegfried Benkner

Recent 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 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

Denis Caromel, CEO Ac.veEon. Orchestrate and Accelerate Applica.ons. Open Source Cloud Solu.ons Hybrid Cloud: Private with Burst Capacity

Denis 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 information

The impact on superannuation fund balances from the new compulsory superannuation rate

The 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 information

Programming Models for Intel Xeon processors and Intel Many Integrated Core (Intel MIC) Architecture

Programming Models for Intel Xeon processors and Intel Many Integrated Core (Intel MIC) Architecture Programming Models for Intel processors and Intel Many Integrated Core (Intel ) Architecture Scott McMillan Senior Software Engineer Software & Services Group April 11, 2012 TACC-Intel Highly Parallel

More information

ROGUE WAVE TOOLS AND LIBRARIES FOR FINANCIAL SERVICES

ROGUE WAVE TOOLS AND LIBRARIES FOR FINANCIAL SERVICES ROGUE WAVE TOOLS AND LIBRARIES FOR FINANCIAL SERVICES Michael Feldman White paper March 2015 MARKET DYNAMICS Financial services is the second largest vertical market in the commercial area of high performance

More information

NVIDIA CUDA GETTING STARTED GUIDE FOR MAC OS X

NVIDIA 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 information

Introduction to Hybrid Programming

Introduction 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 information

2011 European HyperWorks Technology Conference. Vladi Nosenzo, Roberto Vadori

2011 European HyperWorks Technology Conference. Vladi Nosenzo, Roberto Vadori 2011 European HyperWorks Technology Conference Vladi Nosenzo, Roberto Vadori 20 Novembre, 2010 2011 ABSTRACT The work described below starts from an idea of a previous experience of Reply, developed in

More information

Introducing PgOpenCL A New PostgreSQL Procedural Language Unlocking the Power of the GPU! By Tim Child

Introducing 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 information

A PORTABLE BENCHMARK SUITE FOR HIGHLY PARALLEL DATA INTENSIVE QUERY PROCESSING

A PORTABLE BENCHMARK SUITE FOR HIGHLY PARALLEL DATA INTENSIVE QUERY PROCESSING A PORTABLE BENCHMARK SUITE FOR HIGHLY PARALLEL DATA INTENSIVE QUERY PROCESSING Ifrah Saeed, Sudhakar Yalamanchili, School of ECE Jeff Young, School of Computer Science February 8, 2015 The Need for Accelerated

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

Three Paths to Faster Simulations Using ANSYS Mechanical 16.0 and Intel Architecture

Three 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 information

Debugging with TotalView

Debugging with TotalView Tim Cramer cramer@rz.rwth-aachen.de Rechen- und Kommunikationszentrum (RZ) Why to use a Debugger? If your program goes haywire, you may... ( wand (... buy a magic... read the source code again and again

More information

Product Training Services. Training Options and Procedures for JobScheduler and YADE

Product 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 information

Debugging with TotalView

Debugging 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 information

5x in 5 hours Porting SEISMIC_CPML using the PGI Accelerator Model

5x 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 information

Introduction 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 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 information

An introduction to Fyrkat

An 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 information

Oracle Developer Studio 12.5

Oracle Developer Studio 12.5 Oracle Developer Studio 12.5 Oracle Developer Studio is the #1 development environment for building C, C++, Fortran and Java applications for Oracle Solaris and Linux operating systems. Oracle Developer

More information

3DES ECB Optimized for Massively Parallel CUDA GPU Architecture

3DES ECB Optimized for Massively Parallel CUDA GPU Architecture 3DES ECB Optimized for Massively Parallel CUDA GPU Architecture Lukasz Swierczewski Computer Science and Automation Institute College of Computer Science and Business Administration in Łomża Lomza, Poland

More information

Kalray MPPA Massively Parallel Processing Array

Kalray 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 information

Trends in High-Performance Computing for Power Grid Applications

Trends 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 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

Introduction to Parallel and Heterogeneous Computing. Benedict R. Gaster October, 2010

Introduction to Parallel and Heterogeneous Computing. Benedict R. Gaster October, 2010 Introduction to Parallel and Heterogeneous Computing Benedict R. Gaster October, 2010 Agenda Motivation A little terminology Hardware in a heterogeneous world Software in a heterogeneous world 2 Introduction

More information

Oracle Developer Studio Performance Analyzer

Oracle Developer Studio Performance Analyzer Oracle Developer Studio Performance Analyzer The Oracle Developer Studio Performance Analyzer provides unparalleled insight into the behavior of your application, allowing you to identify bottlenecks and

More information

Le langage OCaml et la programmation des GPU

Le 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 information

Turbomachinery CFD on many-core platforms experiences and strategies

Turbomachinery 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 information

The 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 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 information

Introduction to Linux and Cluster Basics for the CCR General Computing Cluster

Introduction 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 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

A 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 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 information

Evaluation of CUDA Fortran for the CFD code Strukti

Evaluation 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 information

The GPU Accelerated Data Center. Marc Hamilton, August 27, 2015

The 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 information

GPUs: Doing More Than Just Games. Mark Gahagan CSE 141 November 29, 2012

GPUs: Doing More Than Just Games. Mark Gahagan CSE 141 November 29, 2012 GPUs: Doing More Than Just Games Mark Gahagan CSE 141 November 29, 2012 Outline Introduction: Why multicore at all? Background: What is a GPU? Quick Look: Warps and Threads (SIMD) NVIDIA Tesla: The First

More information

Keeneland 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 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 information

ST810 Advanced Computing

ST810 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 information

CARMA CUDA on ARM Architecture. Developing Accelerated Applications on ARM

CARMA CUDA on ARM Architecture. Developing Accelerated Applications on ARM CARMA CUDA on ARM Architecture Developing Accelerated Applications on ARM CARMA is an architectural prototype for high performance, energy efficient hybrid computing Schedule Motivation System Overview

More information

Performance Analysis for GPU Accelerated Applications

Performance 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 information

MANUFACTURING WEATHER FORECASTING SIMULATIONS ON HPC INFRASTRUCTURES

MANUFACTURING WEATHER FORECASTING SIMULATIONS ON HPC INFRASTRUCTURES MANUFACTURING WEATHER FORECASTING SIMULATIONS ON HPC INFRASTRUCTURES LADISLAV HLUCHÝ V. ŠIPKOVÁ, M. DOBRUCKÝ, J. BARTOK, B.M. NGUYEN INSTITUTE OF INFORMATICS, SLOVAK ACADEMY OF SCIENCES ECW 2016 - ENVIRONMENTAL

More information

HPC Programming Framework Research Team

HPC 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 information

SLURM Workload Manager

SLURM 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 information

The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming

The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming Kamran Karimi Neak Solutions Calgary, Alberta, Canada kamran@neak-solutions.com Abstract OpenCL, along with CUDA, is one of

More information

Productivity 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. 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 information

MIKE by DHI 2014 e sviluppi futuri

MIKE 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 information

PROGRAMMING MODEL EXAMPLES

PROGRAMMING MODEL EXAMPLES ( Cray Inc 2016) PROGRAMMING MODEL EXAMPLES DEMONSTRATION EXAMPLES OF VARIOUS PROGRAMMING MODELS OVERVIEW Building an application to use multiple processors (cores, cpus, nodes) can be done in various

More information

Overview. Introduction to Pacman. Login Node Usage. Tom Logan. PACMAN Penguin Computing Opteron Cluster

Overview. Introduction to Pacman. Login Node Usage. Tom Logan. PACMAN Penguin Computing Opteron Cluster Overview Introduction to Pacman Tom Logan Hardware Programming Environment Compilers Queueing System PACMAN Penguin Computing Opteron Cluster 12 Login Nodes: 2- Six core 2.2 GHz AMD Opteron Processors;

More information

Introduction to HPC Workshop. Center for e-research (eresearch@nesi.org.nz)

Introduction 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 information

Microsoft Technical Computing The Advancement of Parallelism. Tom Quinn, Technical Computing Partner Manager

Microsoft 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 information

Introduction 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 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 information

Multi-core Programming System Overview

Multi-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 information

Design and Optimization of a Portable Lattice Boltzmann Code for Heterogeneous Architectures

Design 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 information

Big Data Visualization on the MIC

Big 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 information