CUDA by Example

An Introduction to General-Purpose GPU Programming

Jason Sanders, Edward Kandrot

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English

Addison-Wesley Educational Publishers Inc
17 September 2010

Computing & IT; Programming & scripting languages: general; Computer architecture & logic design; Parallel processing

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

By: Jason Sanders, Edward Kandrot
Imprint: Addison-Wesley Educational Publishers Inc
Country of Publication: United States
Dimensions: Height: 229mm, Width: 190mm, Spine: 14mm
Weight: 500g
ISBN: 9780131387683
ISBN 10: 0131387685
Pages: 312
Publication Date: 17 September 2010
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Chapter 1: Why CUDA? Why Now? Chapter 2: Getting Started Chapter 3: Introduction to CUDA C Chapter 4: Parallel Programming in CUDA C Chapter 5: Thread Cooperation Chapter 6: Constant Memory and Events Chapter 7: Texture Memory Chapter 8: Graphics Interoperability Chapter 9: Atomics Chapter 10: Streams Chapter 11: CUDA C on Multiple GPUs Chapter 12: The Final Countdown Appendix A: Advanced Atomics Index

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.