Note: Supplemental materials are not guaranteed with Rental purchases.


You may extend rentals at any time.

CUDA by Example An Introduction to General-Purpose GPU Programming

ISBN: 9780131387683 | 0131387685
Edition: 1st
Format: Paperback
Publisher: Addison-Wesley Professional
Pub. Date: 7/19/2010

Why Rent from Knetbooks?

Because Knetbooks knows college students. Our rental program is designed to save you time and money. Whether you need a textbook for a semester, quarter or even a summer session, we have an option for you. Simply select a rental period, enter your information and your book will be on its way!

Top 5 reasons to order all your textbooks from Knetbooks:

  • We have the lowest prices on thousands of popular textbooks
  • Free shipping both ways on ALL orders
  • Most orders ship within 48 hours
  • Need your book longer than expected? Extending your rental is simple
  • Our customer support team is always here to help
"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 Using NVIDIArs"s breakthrough CUDA software platform, you can harness the immense power of NVIDIA graphics processors to build high-performance, non-graphics software in fields ranging from science and engineering to finance. InCUDA by Example,two senior members of NVIDIArs"s CUDA development team show C/C++ programmers exactly how to make the most of this extraordinary new technology, even if they have absolutely no graphics or parallel programming experience. The only CUDA book created with NVIDIArs"s direct involvement,CUDA by Exampleintroduces every area of CUDA development through working, compilable examples. After concisely introducing the platform and architecture, the authors present a quick-start guide to CUDA C, the C-based language for programming massively parallel NVIDIA GPUs. Next, they systematically detail the techniques and tradeoffs associated with each key CUDA feature. Yours"ll discover when to use each CUDA C extensionand 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

Please wait while this item is added to your cart...