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High Performance Parallelism Pearls: Multicore and Many-core Programming Approaches

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by James Reinders & James Jeffers
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High Performance Parallelism Pearls: Multicore and Many-core Programming Approaches by James Reinders & James Jeffers

High Performance Parallelism Pearls shows how to leverage parallelism on processors and coprocessors with the same programming - illustrating the most effective ways to better tap the computational potential of systems with Intel Xeon Phi coprocessors and Intel Xeon processors or other multicore processors. The book includes examples of successful programming efforts, drawn from across industries and domains such as chemistry, engineering, and environmental science. Each chapter in this edited work includes detailed explanations of the programming techniques used, while showing high performance results on both Intel Xeon Phi coprocessors and multicore processors. Learn from dozens of new examples and case studies illustrating "success stories" demonstrating not just the features of these powerful systems, but also how to leverage parallelism across these heterogeneous systems.

  • Promotes consistent standards-based programming, showing in detail how to code for high performance on multicore processors and Intel Xeon Phiâ„¢
  • Examples from multiple vertical domains illustrating parallel optimizations to modernize real-world codes
  • Source code available for download to facilitate further exploration
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    Ebook Details
    Pages: 600
    Size: 58.6 MB
    Publisher: Morgan Kaufmann
    Date published:   2014
    ISBN: 2370006314875 (DRM-EPUB)
    9780128021996 (DRM-PDF)

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This product is listed in the following categories:

Nonfiction > Computers > Data Processing > Parallel Processing
Nonfiction > Computers > Programming > Parallel Programming

These authors have products in the following categories:

Nonfiction > Computers > Programming > Software Development
Nonfiction > Computers > Computer Architecture
Nonfiction > Computers > Programming > Algorithms
Nonfiction > Computers > Data Processing > Parallel Processing
Nonfiction > Computers > Programming > Parallel Programming

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05/29/2017
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