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CUDA by Example: An Introduction to General-Purpose GPU Programming [Paperback]

Jason Sanders , Edward Kandrot
3.8 out of 5 stars  See all reviews (10 customer reviews)
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Book Description

19 July 2010 0131387685 978-0131387683 1

“This book is required reading for anyone working with accelerator-based computing systems.”

–From the Foreword by Jack Dongarra, University of Tennessee and Oak Ridge National Laboratory

CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required–just the ability to program in a modestly extended version of C.

 

CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance.

 

Major topics covered include

  • Parallel programming
  • Thread cooperation
  • Constant memory and events
  • Texture memory
  • Graphics interoperability
  • Atomics
  • Streams
  • CUDA C on multiple GPUs
  • Advanced atomics
  • Additional CUDA resources

All the CUDA software tools you’ll need are freely available for download from NVIDIA.

http://developer.nvidia.com/object/cuda-by-example.html

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CUDA by Example: An Introduction to General-Purpose GPU Programming + CUDA Programming (Applications of GPU Computing Series) + The CUDA Handbook: A Comprehensive Guide to GPU Programming
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Product details

  • Paperback: 312 pages
  • Publisher: Addison Wesley; 1 edition (19 July 2010)
  • Language: English
  • ISBN-10: 0131387685
  • ISBN-13: 978-0131387683
  • Product Dimensions: 22.9 x 19 x 1.7 cm
  • Average Customer Review: 3.8 out of 5 stars  See all reviews (10 customer reviews)
  • Amazon Bestsellers Rank: 162,183 in Books (See Top 100 in Books)
  • See Complete Table of Contents

More About the Authors

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Product Description

From the Back Cover

“This book is required reading for anyone working with accelerator-based computing systems.”

–From the Foreword by Jack Dongarra, University of Tennessee and Oak Ridge National Laboratory

CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required–just the ability to program in a modestly extended version of C.

 

CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance.

 

Major topics covered include

  • Parallel programming
  • Thread cooperation
  • Constant memory and events
  • Texture memory
  • Graphics interoperability
  • Atomics
  • Streams
  • CUDA C on multiple GPUs
  • Advanced atomics
  • Additional CUDA resources

All the CUDA software tools you’ll need are freely available for download from NVIDIA.

http://developer.nvidia.com/object/cuda-by-example.html

About the Author

Jason Sanders is a senior software engineer in the CUDA Platform group at NVIDIA. While at NVIDIA, he helped develop early releases of CUDA system software and contributed to the OpenCL 1.0 Specification, an industry standard for heterogeneous computing. Jason received his master’s degree in computer science from the University of California Berkeley where he published research in GPU computing, and he holds a bachelor’s degree in electrical engineering from Princeton University. Prior to joining NVIDIA, he previously held positions at ATI Technologies, Apple, and Novell. When he’s not writing books, Jason is typically working out, playing soccer, or shooting photos.

 

Edward Kandrot is a senior software engineer on the CUDA Algorithms team at NVIDIA. He has more than twenty years of industry experience focused on optimizing code and improving performance, including for Photoshop and Mozilla. Kandrot has worked for Adobe, Microsoft, and Google, and he has been a consultant at many companies, including Apple and Autodesk. When not coding, he can be found playing World of Warcraft or visiting Las Vegas for the amazing food.


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Customer Reviews

Most Helpful Customer Reviews
5 of 5 people found the following review helpful
Format:Paperback
This was my first book on GPU computing and a really pleasant surprise: well written, up to date and extremely easy to read.

The author introduces the basic tools of the trade, adding more constructs and techniques as the book progresses, including not-so-basic topics as "texture memory", "CUDA-OpenGL integration", "Streams" and "atomic operations" (and going as far as to deal with mutexes in the appendix).

The style is witty, clear and informative and the examples appealing: on each chapter at least a simple program is presented bottom up, they show some interesting graphics and give an immediate idea of what GPU computing can actually deliver, without relying on the "usual" plain number crunching examples.

Being an introductory text however, this book doesn't provide all the content required for serious GPU developing and should be complemented with other resources (by the way, suggested in the last chapter): for instance, it doesn't cover the GPU hardware capabilities and limitations, and the ways to work around them (you can find more about this in "Programming massively parallel processors" which I have also reviewed).

All in one, a great introductory book which is both informative and a pleasure to read.
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3 of 3 people found the following review helpful
3.0 out of 5 stars Still not a starter book 13 Dec 2010
Format:Kindle Edition|Verified Purchase
Maybe I bought the wrong book, but this is the only one I found that looked like it was going to easily explain how to start with CUDA. The first chapter explains the awesomeness of CUDA and gets the reader all excited. Chapter 2 is all about getting set up and is way too short and does not provide enough detail. I get the impression from the book that you can just download the right applications and just start programming with the examples. Maybe for some people this is the case, but not for me. I have the right hardware/software (nvidia CUDA card, the nvidia SDK, and Microsoft Visual Studio C++ 2008 and have got the CUDA examples form the site to run, but not build) and am still trying to get Hello World Part two to compile. At the moment I am messing around with custom build steps for now trying to get it to compile. Would be nice if the book explains whether the HelloWorld file is supposed to be a .cu file and if it would mention all the other details like how to set up the IDE to work with CUDA. Once I get set up, Im sure the book will be useful, but until then I'm stuck reading forums.
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4.0 out of 5 stars Real fine introduction 28 Feb 2014
By 7oakim
Format:Paperback|Verified Purchase
It explains what CUDA programming is, with easy to follow examples. The similaritư with C language is also exposed clairly.
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5.0 out of 5 stars Great Start with CUDA 16 Dec 2013
Format:Kindle Edition|Verified Purchase
While this book does assume a familiarity with C/C++ and object-oriented programming, it's a straightforward and easy book to follow. The provided code is explained well and without unnecessary jargon. CUDA and GPGPU programming is, in itself, remarkably straightforward, but unlike many of the online material I found before buying this book, it actually takes the time to explain what's going on, rather than forcing the reader to decipher someone else's uncommented code. A worthwhile purchase for anyone looking to get started with CUDA.

This is also my first programming book bought on Kindle; the format works brilliantly and it's more manageable to have my Nexus 7 propped next to my laptop while I'm working rather than having to wrestle with a lump of dead tree that moves of its own accord far more than a dead thing should!
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4.0 out of 5 stars CUDA by example 14 Mar 2013
By ratfink
Format:Paperback|Verified Purchase
This is a good basic book on CUDA. CUDA can be quite difficult to pick up from reading web articles but this starts with basics and provides some of the low-end, simple stuff you need when you're starting out, so it fills in the gaps left by web resources which tend to be either high level and non-specific, or far too technical.
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