CUDA by Example

CUDA by Example
Author : Jason Sanders
Publisher : Addison-Wesley Professional
Total Pages : 312
Release : 2010-07-19
ISBN 10 : 9780132180139
ISBN 13 : 0132180138
Language : EN, FR, DE, ES & NL

CUDA by Example Book Description:

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


RELATED BOOKS:
CUDA by Example
Language: en
Pages: 312
Authors: Jason Sanders, Edward Kandrot
Categories: Computers
Type: BOOK - Published: 2010-07-19 - Publisher: Addison-Wesley Professional

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
Challenger & 'Cuda
Language: en
Pages: 192
Authors: Robert Genat
Categories: Transportation
Type: BOOK - Published: 2005 - Publisher: Motorbooks International

Chrysler entered the pony-car market with the capable but unlovely Barracuda in the early 1960s. The car was refined over the years, becoming a true muscle car, and a rather handsome one at that, but it wasn’t until the advent of the E-body pony cars from 1970-1974—Barracudas, the Dodge Challenger,
Cuda
Language: en
Pages: 220
Authors: Stacy Wright
Categories: Fiction
Type: BOOK - Published: 2010-03 - Publisher: AuthorHouse

Lieutenant Charlie Steiner is an investigator for the US Navy. He is a decorated officer, having served with the SEAL teams, a loving husband, and soon to be father. His latest case involving a series of top secret munitions hijackings, is about to change his life, forever. Conspiracies, cover up,
CUDA Programming
Language: en
Pages: 576
Authors: Shane Cook
Categories: Computers
Type: BOOK - Published: 2013 - Publisher: Newnes

If you need to learn CUDA but don't have experience with parallel computing, CUDA Programming: A Developer's Introduction offers a detailed guide to CUDA with a grounding in parallel fundamentals. It starts by introducing CUDA and bringing you up to speed on GPU parallelism and hardware, then delving into CUDA
The CUDA Handbook
Language: en
Pages: 528
Authors: Nicholas Wilt
Categories: Computers
Type: BOOK - Published: 2013-06-11 - Publisher: Addison-Wesley

The CUDA Handbook begins where CUDA by Example (Addison-Wesley, 2011) leaves off, discussing CUDA hardware and software in greater detail and covering both CUDA 5.0 and Kepler. Every CUDA developer, from the casual to the most sophisticated, will find something here of interest and immediate usefulness. Newer CUDA developers will