Programming Massively Parallel Processors, Second Edition: A Hands-on Approach by David B. Kirk, Wen-mei W. Hwu

Programming Massively Parallel Processors, Second Edition: A Hands-on Approach Author: David B. Kirk, Wen-mei W. Hwu
eBook Title: Programming Massively Parallel Processors, Second Edition: A Hands-on Approach
ISBN10: 0124159923
ISBN13: 978-0124159921
Language: English
Publisher: Morgan Kaufmann; 2 edition (December 28, 2012)
Category: Computers & Technology
Subcategory: Hardware & DIY
Size ePub vers.: 1642 kb
Size PDF vers.: 1677 kb
Other formats: cb7, odf, pdf, azw, ibooks, mobi
Rating: 3.7
Votes: 495
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Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs.

This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing.

This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers.

  • New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more
  • Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism
  • Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing

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