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Professional CUDA C Programming
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Professional CUDA C Programming Paperback - 2014

by John Cheng

From the rear cover

Break into the powerful world of parallel computing

Focused on the essential aspects of CUDA, Professional CUDA C Programming offers down-to-earth coverage of parallel computing. Packed with examples and exercises that help you see code, real-world applications, and try out new skills, this resource makes the complex concepts of parallel computing accessible and easy to understand. Each chapter is organized around one central topic, and includes workable examples that demonstrate the development process, allowing you to measure significant performance gains while exploring all aspects of GPU programming.

Professional CUDA C Programming:

  • Focuses on GPU programming skills and best practices that deliver outstanding performance
  • Shows you how to think in parallel
  • Turns complex subjects into easy-to-understand concepts
  • Makes information accessible across multiple industrial sectors
  • Features helpful examples and exercises in each chapter
  • Covers the essentials for those who are not experts in C programming

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Details

  • Title Professional CUDA C Programming
  • Author John Cheng
  • Binding Paperback
  • Edition International Ed
  • Pages 528
  • Volumes 1
  • Language ENG
  • Publisher Wrox Press, Ind.
  • Date 2014-09-15
  • Features Bibliography, Index
  • ISBN 9781118739327 / 1118739329
  • Weight 1.95 lbs (0.88 kg)
  • Dimensions 9.2 x 7.3 x 1.1 in (23.37 x 18.54 x 2.79 cm)
  • Library of Congress subjects Parallel programming (Computer science)
  • Dewey Decimal Code 005.275

About the author

John Cheng, PHD, is a Research Scientist at BGP International in Houston. He has developed seismic imaging products with GPU technology and many high-performance parallel production applications on heterogeneous computing-platforms.

Max Grossman is an expert in GPU computing with experience applying CUDA to problems in medical imaging, machine learning, geophysics, and more.

Ty McKercher has been helping customers adopt GPU acceleration technologies while he has been employed at NVIDIA since 2008.

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