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BIG CPU, BIG DATA: Solving the World's Toughest Problems with Parallel Computing
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  • Title: BIG CPU, BIG DATA: Solving the World's Toughest Problems with Parallel Computing
  • Author(s) Alan Kaminsky
  • Publisher: CreateSpace, 1 edition (July 30, 2016); eBook (Creative Commons Edition, 2015)
  • License(s): CC BY-NC-ND 3.0
  • Note: Pre-publication versions of the book dated August 2015 or earlier were free, Creative Commons licensed.
  • Paperback 504 pages
  • eBook PDF (424 pages, 12.01 MB)
  • Language: English
  • ISBN-10: 1534872280
  • ISBN-13: 978-1534872288
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Book Description

This book teaches you how to write parallel programs for multicore machines, compute clusters, GPU accelerators, and big data map-reduce jobs, in the Java language, with the free, easy-to-use, object-oriented Parallel Java 2 Library. The book also covers how to measure the performance of parallel programs and how to design the programs to run as fast as possible.

The goal of this book is to teach you how to write parallel programs that take full advantage of the vast processing power of modern multicore computers, compute clusters, and graphics processing unit (GPU) accelerators.

To study parallel programming with this book, you'll need the following prerequisite knowledge: Java programming; C programming (for GPU pro grams); computer organization concepts (CPU, memory, cache, and so on); operating system concepts (threads, thread synchronization).

About the Authors
  • Alan Kaminsky is a Professor at Department of Computer Science, Rochester Institute of Technology. With 31 years of computing experience spanning industry and academia, he has developed telephone switching system software at Bell Laboratories, developed real-time embedded control software and fuzzy genetic algorithms at Harris Corporation, and worked on printer system architectures at Xerox Corporation.
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