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

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

High Performance Parallelism Pearls Volume 2 offers another set of examples that demonstrate how to leverage parallelism. Similar to Volume 1, the techniques included here explain how to use processors and coprocessors with the same programming - illustrating the most effective ways to combine Xeon Phi coprocessors with Xeon and other multicore processors. The book includes examples of successful programming efforts, drawn from across industries and domains such as biomed, genetics, finance, manufacturing, imaging, and more. 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 Xeon-powered systems, but also how to leverage parallelism across these heterogeneous systems.

  • Promotes write-once, run-anywhere coding, showing how to code for high performance on multicore processors and Xeon Phi
  • Examples from multiple vertical domains illustrating real-world use of Xeon Phi coprocessors
  • Source code available for download to facilitate further exploration

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Ebook Details
Pages: 592
Size: 34.0 MB
Publisher: Morgan Kaufmann
Date published:   2015
ISBN: 2370006767213 (DRM-EPUB)
9780128038901 (DRM-PDF)

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This product is listed in the following category:

Nonfiction > Computers > Data Processing > Parallel Processing

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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