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Programming Massively Parallel Processors: A Hands-on Approach (Applications of GPU Computing Series)

Programming Massively Parallel Processors: A Hands-on Approach (Applications of GPU Computing Series)Authors: David B. Kirk, Wen-mei W. Hwu
Publisher: Morgan Kaufmann
Category: Book

List Price: $69.95
Buy New: $35.39
as of 2/6/2012 00:33 MST details
You Save: $34.56 (49%)

In Stock


New (35) Used (22) from $27.00

Seller: Books In Hand
Sales Rank: 61,868

Languages: English (Unknown), English (Original Language), English (Published)
Media: Paperback
Edition: 1
Pages: 280
Number Of Items: 1
Shipping Weight (lbs): 0
Dimensions (in): 9.2 x 7.4 x 0.8

ISBN: 0123814723
EAN: 9780123814722
ASIN: 0123814723

Publication Date: February 5, 2010
Availability: Usually ships in 1-2 business days

Also Available In:

  • Kindle Edition - Programming Massively Parallel Processors: A Hands-on Approach (Applications of GPU Computing Series)
  • Hardcover - Programming Massively Parallel Processors

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Product Description

Multi-core processors are no longer the future of computing-they are the present day reality. A typical mass-produced CPU features multiple processor cores, while a GPU (Graphics Processing Unit) may have hundreds or even thousands of cores. With the rise of multi-core architectures has come the need to teach advanced programmers a new and essential skill: how to program massively parallel processors.

Programming Massively Parallel Processors: A Hands-on Approach shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs.


  • Teaches computational thinking and problem-solving techniques that facilitate high-performance parallel computing.

  • Utilizes CUDA (Compute Unified Device Architecture), NVIDIA's software development tool created specifically for massively parallel environments.

  • Shows you how to achieve both high-performance and high-reliability using the CUDA programming model as well as OpenCL.



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