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

Front Cover
Addison-Wesley Professional, Jul 19, 2010 - Computers - 320 pages

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

 

Selected pages

Contents

Foreword
Acknowledgments
WHY CUDA? WHY NOW?
GETTING STARTED
INTRODUCTION TO CUDA C
PARALLEL PROGRAMMING IN CUDA C
THREAD COOPERATION
CONSTANT MEMORY AND EVENTS
ATOMICS
STREAMS
CUDA C ON MULTIPLE GPUS
THE FINAL COUNTDOWN
GRAPHICS INTEROPERABILITY
A HandsOn Approach
A ADVANCED ATOMICS
Index

Other editions - View all

Cuda by Example: An Introduction to General-purpose Gpu Programming
Jason Sanders,Edward Kandrot
No preview available - 2017
Cuda by Example: An Introduction to General-purpose Gpu Programming
Jason Sanders,edward Kandrot
No preview available - 2017

Common terms and phrases

__syncthreads algorithm allocate memory application array atomic operations bitmap bucket bucket array cache Chapter compiler compute capability constant memory CPU version CUDA Architecture CUDA C kernels CUDA device CUDA runtime CUDA streams CUDA-capable cudaEventCreate cudaHostAlloc cudaMalloc cudaMemcpy cudaMemcpyAsync dev_a device code dim3 DirectX dot product dot product computation entry example float GeForce GTX GPU computing GPU histogram GPU ripple GPU sums GPUAnimBitmap graphics interoperability graphics processing units graphics processors grid HANDLE_ERROR hardware hash function hash table hash table implementation histogram computation increment input buffers int i=0 Julia Set kernel execution launch lock look malloc memory copies multi-GPU multiple GPUs mutex number of threads NVIDIA GPUs OpenGL output buffer pageable parallel blocks parallel computing PCI Express performance pixel pointer portable pinned memory Quadro FX ray tracing routine shared memory simulation synchronization temp texture memory two-dimensional variable vector write-combined zero-copy memory

About the author (2010)

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.

Bibliographic information

Title CUDA by Example: An Introduction to General-Purpose GPU Programming
Authors Jason Sanders, Edward Kandrot
Publisher Addison-Wesley Professional, 2010
ISBN 0132180138, 9780132180139
Length 320 pages
Subjects  ›   › 

Computers / Languages / General
Computers / Programming / Parallel
   
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