CUDA by Example by Jason Sanders

CUDA by Example

An Introduction to General-purpose GPU Programming

Jason Sanders, Edward Kandrot

Pearson Education · Print & ebook · July 19, 2010

“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.

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Who it’s for
C programmers seeking an introduction to general-purpose GPU programming
Themes
GPU programming, Parallel programming, High-performance computing
Genres
Parallel Programming, C Programming, Systems Architecture

About this book

“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.

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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

Who it’s for

  • C programmers seeking an introduction to general-purpose GPU programming
  • Programmers exploring parallel computing for science, engineering, or finance

Where it sits

Parallel Programming90%
Systems Architecture47%
C Programming46%

Percentages are BookFrontier’s reading of the book.

Publisher categories

  • Programming Languages
  • Parallel Programming
Authors
Jason Sanders, Edward Kandrot
Publisher
Pearson Education
Published
July 19, 2010
Format
Print & ebook
Theme
GPU programming · Parallel programming · High-performance computing
Reading lane
Programming Languages