OpenCL Parallel Programming Development Cookbook: Accelerate your applications and understand high-performance computing with over 50 OpenCL recipes

303 Pages·2013·3.14 MB·English

by  Raymond Tay

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OpenCL Parallel
Programming
Development
Cookbook
Accelerate your applications and understand
high-performance computing with over
50 OpenCL recipes
Raymond Tay
BIRMINGHAM - MUMBAI
www.it-ebooks.info
OpenCL Parallel Programming Development
Cookbook
Copyright © 2013 Packt Publishing
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First published: August 2013
Production Reference: 1210813
Published by Packt Publishing Ltd.
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ISBN 978-1-84969-452-0
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Cover Image by Suresh Mogre ([email protected])
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Credits
Author Project Coordinator
Raymond Tay Shiksha Chaturvedi
Reviewers Proofreader
Nitesh Bhatia Faye Coulman
Darryl Gove Lesley Harrison
Seyed Hadi Hosseini Paul Hindle
Kyle Lutz
Viraj Paropkari Indexer
Tejal R. Soni
Acquisition Editors
Saleem Ahmed Graphics
Sheetal Aute
Erol Staveley
Ronak Druv
Valentina D'silva
Lead Technical Editor
Ankita Shashi Disha Haria
Abhinash Sahu
Technical Editors
Veena Pagare
Production Coordinator
Krishnaveni Nair Melwyn D'sa
Ruchita Bhansali
Shali Sashidharan Cover Work
Melwyn D'sa
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About the Author
Raymond Tay has been a software developer for the past decade and his favorite
programming languages include Scala, Haskell, C, and C++. He started playing with GPGPU
technology since 2008, first with the CUDA toolkit by NVIDIA and OpenCL toolkit by AMD,
and then Intel. In 2009, he decided to submit a GPGPU project on which he was working to
the editorial committee working on the "GPU Computing Gems" to be published by Morgan
Kauffmann. And though his work didn't make it to the final published work, he was very
happy to have been short-listed for candidacy. Since then, he's worked on projects that
use GPGPU technology and techniques in CUDA and OpenCL. He's also passionate about
functional programming paradigms and their applications in cloud computing which has led
him investigating on various paths to accelerate applications in the cloud through the use
of GPGPU technology and the functional programming paradigm. He is a strong believer of
continuous learning and hopes to be able to continue to do so for as long as he possibly can.
This book could not have been possible without the support of foremost,
my wife and my family, as I spent numerous weekends and evenings away
from them so that I could get this book done and I would make it up to them
soon. Packt Publishing for giving me the opportunity to be able to work on
this project and I've received much help from the editorial team and lastly to
the reviewing team, and I would also like to thank Darryl Gove – The senior
principal software engineer at Oracle and Oleg Strikov – the CPU Architect
at NVIDIA, who had rendered much help for getting this stuff right with their
sublime and gentle intellect, and lastly to my manager, Sau Sheong, who
inspired me to start this. Thanks guys.
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About the Reviewers
Nitesh Bhatia is a tech geek with a background in information and communication
technology (ICT) with an emphasis on computing and design research. He worked with
Infosys Design as a user experience designer, and is currently a doctoral scholar at the Indian
Institute of Science, Bangalore. His research interests include visual computing, digital human
modeling, and applied ergonomics. He delights in exploring different programming languages,
computing platforms, embedded systems and so on. He is a founder of several social media
startups. In his leisure time, he is an avid photographer and an art enthusiast, maintaining
a compendium of his creative works through his blog Dangling-Thoughts (http://www.
dangling-thoughts.com).
Darryl Gove is a senior principal software engineer in the Oracle Solaris Studio team, working
on optimizing applications and benchmarks for current and future processors. He is also the
author of the books, Multicore Application Programming, Solaris Application Programming,
and The Developer's Edge. He writes his blog at http://www.darrylgove.com.
Seyed Hadi Hosseini is a software developer and network specialist, who started his
career at the age of 16 by earning certifications such as MCSE, CCNA, and Security+. He
decided to pursue his career in Open Source Technology, and for this Perl programming
was the starting point. He concentrated on web technologies and software development for
almost 10 years. He is also an instructor of open source courses. Currently, Hadi is certified
by the Linux Professional Institute, Novell, and CompTIA as a Linux specialist (LPI, LINUX+,
NCLA and DCTS). High Performance Computing is one of his main research areas. His first
published scientific paper was awarded as the best article in the fourth Iranian Bioinformatics
Conference held in 2012. In this article, he developed a super-fast processing algorithm
for SSR in Genome and proteome datasets, by using OpenCL as the GPGPU programming
framework in C language, and benefiting from the massive computing capability of GPUs.
Special thanks to my family and grandma for their invaluable support.
I would also like to express my sincere appreciation to my wife, without
her support and patience, this work would not have been done easily.
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Kyle Lutz is a software engineer and is a part of the Scientific Computing team at Kitware,
Inc, New York. He holds a bachelor's degree in Biological Sciences from the University of
California at Santa Barbara. He has several years of experience writing scientific simulation,
analysis, and visualization software in C++ and OpenCL. He is also the lead developer of the
Boost.Compute library – a C++ GPU/parallel-computing library based on OpenCL.
Viraj Paropkari has done his graduation in computer science from University of Pune,
India, in 2004, and MS in computer science from Georgia Institute of Technology, USA, in
2008. He is currently a senior software engineer at Advanced Micro Devices (AMD), working
on performance optimization of applications on CPUs, GPUs using OpenCL. He also works on
exploring new challenges in big data and High Performance Computing (HPC) applications
running on large scale distributed systems. Previously, he was systems engineer at National
Energy Research Scientific Computing Center (NERSC) for two years, where he worked on one
of the world's largest supercomputers running and optimizing scientific applications. Before that,
he was a visiting scholar in Parallel Programming Lab (PPL) at Computer Science Department
of University of Illinois, Urbana-Champaign, and also a visiting research scholar at Oak Ridge
National Laboratory, one of the premier research labs in U.S.A. He also worked on developing
software for mission critical flight simulators at Indian Institute of technology, Bombay, India, and
Tata institute of Fundamental Research (TIFR), India. He was the main contributor of the team
that was awarded the HPC Innovation Excellence Award to speed up the CFD code and achieve
the first ever simulation of a realistic fuel-spray related application. The ability to simulate this
problem helps reduce design cycles to at least 66 percent and provides new insights into the
physics that can provide sprays with enhanced properties.
I'd like to thank my parents, who have been inspiration to me and also thank
my beloved wife, Anuya, who encouraged me in spite of all the time it took
me away from her.
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Table of Contents
Preface 1
Chapter 1: Using OpenCL 7
Introduction 7
Querying OpenCL platforms 14
Querying OpenCL devices on your platform 18
Querying OpenCL device extensions 22
Querying OpenCL contexts 25
Querying an OpenCL program 29
Creating OpenCL kernels 35
Creating command queues and enqueuing OpenCL kernels 38
Chapter 2: Understanding OpenCL Data Transfer and Partitioning 43
Introduction 43
Creating OpenCL buffer objects 44
Retrieving information about OpenCL buffer objects 50
Creating OpenCL sub-buffer objects 54
Retrieving information about OpenCL sub-buffer objects 58
Understanding events and event synchronization 61
Copying data between memory objects 64
Using work items to partition data 71
Chapter 3: Understanding OpenCL Data Types 79
Introduction 79
Initializing the OpenCL scalar data types 80
Initializing the OpenCL vector data types 82
Using OpenCL scalar types 85
Understanding OpenCL vector types 88
Vector and scalar address spaces 100
Configuring your OpenCL projects to enable the double data type 103
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