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A timely reference on new approaches to parallel computing Traditional software for parallel computing typically spreads computations evenly over a set of linked processors. This, however, may not always be the best way of maximizing the performance of a given network or cluster of computers. By taking account of the actual performance of individual processors and the links between them, parallel computing on heterogeneous networks offers significant improvements in parallel computation. Alexey Lastovetsky s Parallel Computing on Heterogeneous Networks provides a timely resource on this innovative technology. This forward-looking text begins with a general introduction to parallel computing, then progresses to the specifics of parallel computing with heterogeneous networks. Practically oriented, the book includes illustrative algorithms in the mpC programming language, a unique high-level software tool designed by the author specifically for programming heterogeneous parallel algorithms. All concepts and algorithms are illustrated with working programs that can be compiled or executed on any cluster. Some of the practical applications of these algorithms include: The N-body problem The parallel testing of distributed software The modeling of oil extraction All of the contents are also illustrated by carefully tested source code, allowing readers to play with the presented software tools and algorithms particularly with the mpC programming language while reading the book. Appendices provide both the complete source code and user s guide for the principal applications used to illustrate the book s material. Parallel Computing on Heterogeneous Networks proves a superior reference for researchers and graduate students in computer science.

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