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High Performance Parallelism Pearls Volume Two: Multicore and Many-Core...

by Jeffers, Jim; Reinders, James | PB | LikeNew
Condition:
Like New
“Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, ”... Read moreabout condition
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US $6.84
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Last updated on Jun 19, 2024 18:58:16 MYTView all revisionsView all revisions

Item specifics

Condition
Like New
A book in excellent condition. Cover is shiny and undamaged, and the dust jacket is included for hard covers. No missing or damaged pages, no creases or tears, and no underlining/highlighting of text or writing in the margins. May be very minimal identifying marks on the inside cover. Very minimal wear and tear. See all condition definitionsopens in a new window or tab
Seller Notes
“Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, ...
Binding
Paperback
Weight
2 lbs
Product Group
Book
IsTextBook
No
ISBN
9780128038192
Publication Year
2015
Type
Textbook
Format
Trade Paperback
Language
English
Subject Area
Computers
Publication Name
High Performance Parallelism Pearls Volume Two Vol. 2 : Multicore and Many-Core Programming Approaches
Author
James Reinders, Jim Jeffers
Publisher
Elsevier Science & Technology
Item Length
9.2 in
Subject
Programming / General, Systems Architecture / General, Microprocessors, Programming / Parallel
Item Width
7.5 in
Number of Pages
592 Pages

About this product

Product Information

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.

Product Identifiers

Publisher
Elsevier Science & Technology
ISBN-10
0128038195
ISBN-13
9780128038192
eBay Product ID (ePID)
215350317

Product Key Features

Number of Pages
592 Pages
Language
English
Publication Name
High Performance Parallelism Pearls Volume Two Vol. 2 : Multicore and Many-Core Programming Approaches
Publication Year
2015
Subject
Programming / General, Systems Architecture / General, Microprocessors, Programming / Parallel
Type
Textbook
Subject Area
Computers
Author
James Reinders, Jim Jeffers
Format
Trade Paperback

Dimensions

Item Length
9.2 in
Item Width
7.5 in

Additional Product Features

Intended Audience
Scholarly & Professional
Dewey Edition
23
Dewey Decimal
004.35
Lc Classification Number
Qa76.58
Table of Content
Introduction Numerical Weather Prediction Optimization WRF Goddard Microphysics Scheme Optimization Pairwise DNA Sequence Alignment Optimization Accelerated Structural Bioinformatics for Drug Discovery Amber PME Molecular Dynamics Optimization Low-Latency Solutions for Financial Services Applications Parallel Numerical Methods in Finance Wilson Dslash Kernel from Lattice QCD Optimization Cosmic Microwave Background Analysis: Nested Parallelism Visual Search Optimization Radio Frequency Ray Tracing Exploring Use of the Reserved Core High Performance Python Offloading Fast Matrix Computations on Heterogeneous Streams MPI-3 Shared Memory Programming Introduction Coarse-Grained OpenMP for Scalable Hybrid Parallelism Exploiting Multilevel Parallelism in Quantum Simulations OpenCL: There and Back Again OpenMP Versus OpenCL: Difference in Performance? Prefetch Tuning Optimizations SIMD Functions Via OpenMP Vectorization Advice Portable Explicit Vectorization Intrinsics Power Analysis for Applications and Data Centers
Copyright Date
2016

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