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Parallel Algorithms (Chapman & Hall/CRC Numerical Analysis and Scientific Computing Series) [Hardcover]

Henri Casanova , Arnaud Legrand , Yves Robert
5.0 out of 5 stars  See all reviews (1 customer review)
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Book Description

1 Aug 2008 1584889454 978-1584889458
Focusing on algorithms for distributed-memory parallel architectures, Parallel Algorithms presents a rigorous yet accessible treatment of theoretical models of parallel computation, parallel algorithm design for homogeneous and heterogeneous platforms, complexity and performance analysis, and essential notions of scheduling. The book extracts fundamental ideas and algorithmic principles from the mass of parallel algorithm expertise and practical implementations developed over the last few decades.

In the first section of the text, the authors cover two classical theoretical models of parallel computation (PRAMs and sorting networks), describe network models for topology and performance, and define several classical communication primitives. The next part deals with parallel algorithms on ring and grid logical topologies as well as the issue of load balancing on heterogeneous computing platforms. The final section presents basic results and approaches for common scheduling problems that arise when developing parallel algorithms. It also discusses advanced scheduling topics, such as divisible load scheduling and steady-state scheduling.

With numerous examples and exercises in each chapter, this text encompasses both the theoretical foundations of parallel algorithms and practical parallel algorithm design.

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Product details

  • Hardcover: 360 pages
  • Publisher: Chapman and Hall/CRC (1 Aug 2008)
  • Language: English
  • ISBN-10: 1584889454
  • ISBN-13: 978-1584889458
  • Product Dimensions: 2.3 x 16 x 23.2 cm
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Bestsellers Rank: 2,352,730 in Books (See Top 100 in Books)
  • See Complete Table of Contents

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"…The authors of the present book, who have extensive credentials in both research and instruction in the area of parallelism, present a sound, principled treatment of parallel algorithms. … This book is very well written and extremely well designed from an instructional point of view. … The authors have created an instructive and fascinating text. The book will serve researchers as well as instructors who need a solid, readable text for a course on parallelism in computing. Indeed, for anyone who wants an understandable text from which to acquire a current, rigorous, and broad view of parallel algorithms, including the principles for their design, development, and analysis, this book is highly recommended."
SIAM Review, Vol. 52, No. 1, 2010

"… It extracts the main ideas and principles of parallel algorithms developed over the last few decades. … the authors perfectly explain not only homogeneous models (which are everyday problems on clusters of identical nodes) but also load balancing on heterogeneous platforms (connecting different clusters or many different workstations). This book can serve as a very good teaching book or a source of useful material for graduate students and researchers in parallel distributed memory architectures. It contains many schemes, diagrams, and pictures for better understanding, including many practical examples, case studies, and exercises."
EMS Newsletter, June 2009

"Parallel Algorithms is a text meant for those with a desire to understand the theoretical underpinnings of parallelism from a computer science perspective. … [it provides] the tools you need to continue on a rigorous research track into the computer science aspects of parallel computing. … those motivated to work through the text will be rewarded with a solid foundation for the study of parallel algorithms."
—John West, HPCwire, April 2009

About the Author

University of Hawaii, Honolulu, Hawaii, USA CNRS, LIG Laboratory, University of Grenoble, France Ecole Normale Superieure de Lyon, France

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Most Helpful Customer Reviews
5.0 out of 5 stars Excellent overview of a huge topic. 1 Feb 2011
I think this book is brilliant. It is short: not a huge tome, but it has absolutely no fat. As such it requires a high level of knowledge, a post-grad text in my opinion. But it covers some exceptionally useful algorithms for general-purpose parallel programming, and the theoretical results are very insightful. I've even managed to use soem of these results in my own code, so it does that most exceptional of tasks: gives theeoretical results that are applicable and usable in the real world in a manner that is not impossibly obscure. Well done to the authors.
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Amazon.com: 4.0 out of 5 stars  2 reviews
1 of 1 people found the following review helpful
3.0 out of 5 stars Has some value 28 April 2010
By wiredweird - Published on Amazon.com
Format:Hardcover|Verified Purchase
The title covers so many possibilities, from the level of processor architecture to grid computing, that no book could possibly cover the whole range. The selections found here surprised me, though: just a few topics, but remarkable depth in at least one of them.

The authors begin with a classic model of computing, the parallel RAM. This conceptual family includes shared-memory systems of many kinds, possibly with restrictions on concurrent reading and/or writing. Here, the emphasis is on data structures that optimize concurrent computation on linked structures. The next chapter covers 'sorting networks.' These consist of two-input, two-output devices that compute the min and max of the input, generally configured with fixed topology. Although classics of the computing canon (see Knuth), they still represent a potentially useful structure, e.g. when creating a fixed-latency median filter in hardware. These chapters seem to tie only loosely to the main substance of the book, which begins in chapter 3.

That begins with a few classic communication topologies, including rings, stars, meshes, and hypercubes. The authors present performance models of graduated sophistication, as well as some low-level operations on specific architectures (e.g., broadcast on a simple ring). Chapters 4 and 5 get to the kinds of algorithms that highly parallel processors are typically called on to handle: matrix operations, stencil algorithms, and solving systems of linear equations. These chapters stand out for their close coupling between problem decomposition and the communication topology involved. Chapters 6-8 discuss load balancing and task scheduling, both static and dynamic. Algorithms like LU decomposition on non-sparse systems have reasonably predictable performance and communication characteristics over the course of one computation, so static and dynamic algorithms are both mentioned.

Task scheduling receives especially thorough treatment, especially when different processors run at predictably different rates. I found the material clearly laid out, but baffling in one respect. Heterogeneous processors typically arise in irregular communication networks such at the Internet, i.e. networks quite unlike the ones discussed in ch. 3-5.

I can give only conditional recommendation of this book, depending on the reader's interests. It discussion of topology-dependent communication and problem partitioning contains good material, task scheduling is exceptional, and the problems in each chapter seem well designed for reinforcing the content of each chapter. The book's idiosyncratic choices of subjects limit the audiences to whom this will be helpful, but, if you're in the target audience for one of the book's strong points, you're likely to find it very rewarding.

-- wiredweird
0 of 2 people found the following review helpful
5.0 out of 5 stars Great book. It's a must 20 Sep 2012
By Andres Meseguer Rojas - Published on Amazon.com
Format:Hardcover|Verified Purchase
As I said its a must. The service was quick and the book got intact, not even a single scratch
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