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Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation) | 
 enlarge | Authors: Barbara Chapman, Gabriele Jost, Ruud Van Der Pas
Creator: David J. Kuck
Publisher: The MIT Press
Category: Book
List Price: $35.00
Buy New: $25.01
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Rating:  1 reviews
Sales Rank: 93172
Media: Paperback
Pages: 353
Number Of Items: 1
Shipping Weight (lbs): 1.5
Dimensions (in): 8.9 x 8 x 0.8
ISBN: 0262533022
Dewey Decimal Number: 005.275
EAN: 9780262533027
Publication Date: October 31, 2007
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Condition: Brand new item. Over 3.5 million customers served. Order now. Selling online since 1995. Few left in stock - order soon. Code: M20080813113714T
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| Editorial Reviews:
Product Description
"I hope that readers will learn to use the full expressibility and power of OpenMP. This book should provide an excellent introduction to beginners, and the performance section should help those with some experience who want to push OpenMP to its limits."
--from the foreword by David J. Kuck, Intel Fellow, Software and Solutions Group, and Director, Parallel and Distributed Solutions, Intel Corporation
OpenMP, a portable programming interface for shared memory parallel computers, was adopted as an informal standard in 1997 by computer scientists who wanted a unified model on which to base programs for shared memory systems. OpenMP is now used by many software developers; it offers significant advantages over both hand-threading and MPI. Using OpenMP offers a comprehensive introduction to parallel programming concepts and a detailed overview of OpenMP.
Using OpenMP discusses hardware developments, describes where OpenMP is applicable, and compares OpenMP to other programming interfaces for shared and distributed memory parallel architectures. It introduces the individual features of OpenMP, provides many source code examples that demonstrate the use and functionality of the language constructs, and offers tips on writing an efficient OpenMP program. It describes how to use OpenMP in full-scale applications to achieve high performance on large-scale architectures, discussing several case studies in detail, and offers in-depth troubleshooting advice. It explains how OpenMP is translated into explicitly multithreaded code, providing a valuable behind-the-scenes account of OpenMP program performance. Finally, Using OpenMP considers trends likely to influence OpenMP development, offering a glimpse of the possibilities of a future OpenMP 3.0 from the vantage point of the current OpenMP 2.5.
With multicore computer use increasing, the need for a comprehensive introduction and overview of the standard interface is clear. Using OpenMP provides an essential reference not only for students at both undergraduate and graduate levels but also for professionals who intend to parallelize existing codes or develop new parallel programs for shared memory computer architectures.
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| Customer Reviews:
Good Performance on a Multicore Machine - Try OpenMP? May 5, 2008
NumericalMethodsGuy
9 out of 10 found this review helpful
I have most of the parallel computing books out there so I am sort of a collector of sorts. Most focus on either the basics of parallel programming, MPI, OpenMP, both, or some other less popular (yet) paradigm e.g. PFortran, TBB, etc. With every parallel-computing wanna be buying a multicore machine dual, quad, dual-quad, etc., the parallel computing software "industry" is in flux. No longer will MPI on a cluster be enough. It still remains to be seen whether the slower memory bus on quad core machines will allow for speedups without major code overhaul or a new paradigm. Anyway, this book is a welcome addition to my collection. For one, it is current e.g. 2008 and also it is focussed on OpenMP (but does treat dual MPI/OpenMP programming). It is well written (I am about 100 pages in since I just got my copy last week) and has one tantalizing chapter entitled "How to get good performance by using OpenMP" - which is really timely since my new 72 core machine (9 dual Intel quad cores) seems to give slower performance for a major commercial CFD code than the equivalent number of dual-core nodes). I hope it helps me. Based on the rapid growth of multicore machines and the lack of a simple programming solution, I recommend this book to all those wanting to try and get their codes running fast on multicore machines. The only downsides in this book so far is the lack of downloadable code (you have to type it in yourself) and it is hard to test the code fragments because they are just that - fragments. A nice feature of the book is the 50/50 emphasis on Fortran/C codes - which are the still the mainstay in large-scale scientific computing.
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