Product Description

Focusing on grid computing and asynchronism, Parallel Iterative Algorithms explores the theoretical and practical aspects of parallel numerical algorithms. Each chapter contains a theoretical discussion of the topic, an algorithmic section that fully details implementation examples and specific algorithms, and an evaluation of the advantages and drawbacks of the algorithms. Several exercises also appear at the end of most chapters.

The first two chapters introduce the general features of sequential iterative algorithms and their applications to numerical problems. The book then describes different kinds of parallel systems and parallel iterative algorithms. It goes on to address both linear and nonlinear parallel synchronous and asynchronous iterative algorithms for numerical computation, with an emphasis on the multisplitting approach. The final chapter discusses the features required for efficient implementation of asynchronous iterative algorithms.

Providing the theoretical and practical knowledge needed to design and implement efficient parallel iterative algorithms, this book illustrates how to apply these algorithms to solve linear and nonlinear numerical problems in parallel environments, including local, distant, homogeneous, and heterogeneous clusters.

Product Details

• Amazon Sales Rank: #1633932 in Books
• Published on: 2007-11-28
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 240 pages

Review
In Parallel Iterative Algorithms: From Sequential to Grid Computing, Bahi, Contassot-Vivier, and Couturier bring mathematical formalism to the study of parallel iterative solution techniques, creating a book that will be useful to those with a strong maths background who are making the transition into parallel scientific computing. … a great fit as a part of a graduate-level course on scientific computing in the math department, or for those already in scientific computing seeking to understand the key mathematical foundations of the analysis of iterative techniques. … The authors execute their mission well, making sure that they treat the mathematical theory of each method in just enough detail to be complete. … The combination of the theory and the implementation is valuable, and I found it illuminating to revisit algorithms I only knew at an implementation level from the mathematical perspective and to understand the reasons behind behaviors I had always taken as given. … a nice addition to your HPC bookshelf in that it brings a strong focus on mathematical formalism, which is often lacking in more computing-oriented approaches to numerical methods. … the book is loaded with citations, and readers looking for a different point of view or for more in depth material on a particular point will find a wealth of pointers to the literature.
—John West, HPCwire, February 2009

About the Author
University of Franche-Comte, Belfort cedex, France University of Franche-Comte, Belfort cedex, France University of Franche-Comte, Belfort cedex, France

Customer Reviews

Important far beyond its stated goals
This book addresses a kind of computing that has become common, in terms of physical resources, but that has been difficult to exploit properly. It's not cluster computing, where processors tend to be homogeneous and communications have low latency. It's not the "SETI at home" model, with extreme heterogeneity and long latencies. Instead, it's the Grid model: long latencies between heterogeneous subnets, but cluster-like speeds within the subnet. This creates unique demands, but also addresses a number of other two-level systems beyond those the authors discuss.

Synchronous algorithms work well within clusters, where communication latency lies below the computation time of one step on each node, and where each node can be expected to run at roughly the same speed as each other. Such algorithms have a fair literature of their own, and are addressed only in the prepratory chapters. Grid communication is different. Processor speeds lie in the nanosecond range these days. Intra-cluster communications range up many microseconds, and intercluster latencies range from milliseconds to seconds. The network of networks is a different beast, and this book addresses that strange creature.

These authors address algorithms that expect to iterate repeatedly and an unpredictable number of times between communication with neighboring sub-problems. In particular, the authors address iterative solution of sparse linear systems - perhaps a loss of generality, but not a loss of practical value. They present their approaches methodically and rigorously - expect to go through this book slowly, and maybe even go back to Strang once in a while. They also address the fact that distributed determination of convergence is at least as demanding as distributed agreements of many other kinds. As an interesting bonus, the asynchronous algorithms also grant some degree of fault tolerance in the presence of intermittent communication failure, such as packet loss due to network congestion.

This book's strengths, for me at least, lie in two areas. The first is its emphasis on pseudocode for critical algorithms - not cut&paste material, but clearly illustrative. The second lies in its progression from cluster-scale synchronous algorithms to Grid-scale asynchronous ones. This can also describe hardware-accelerated nodes within a cluster: fast communication with the accelerator, but orders of magnitude slower and less predictable communication betwee accelerated nodes. The absolute time scales and distances differ, but the ratios of local to non-local communication time and computation time hold up well.

Only the most dedicated readers will invest the time and effort needed to extract this book's value. Those readers, however, will be richly rewarded.

-- wiredweird