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Programming on Parallel Machines: GPU, Multicore, Clusters and More
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  • Title: Programming on Parallel Machines: GPU, Multicore, Clusters and More
  • Author(s) Norm Matloff
  • Publisher: University of California (July 17, 2012); eBook (Creative Commons Licensed)
  • License(s): CC BY-ND 3.0 US
  • Paperback: N/A
  • eBook: PDF (410 page, 2.55 MB), ePUB, Kindle, Text, etc.
  • Language: English
  • ISBN-10: N/A
  • ISBN-13: N/A
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Book Description

Parallel machines provide a wonderful opportunity for applications with large computational requirements. Effeective use of these machines, though, requires a keen understanding of how they work. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing.

The main goal of the book is to present parallel programming techniques that can be used in many situations for many application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques

The main programming language used is C (C++ if you prefer), but some of the code is in R, the dominant language is the statistics/data mining worlds. The reasons for including R are given at the beginning of Chapter 10, and a quick introduction to the language is provided. Some material on parallel Python is introduced as well.

About the Authors
  • Norm Matloff is an American professor of computer science at the University of California, Davis. He was formerly a statistics professor at that university, and thus approaches the subject matter here as both a statistician and computer scientist.
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