Efficient Parallel Algorithms by Alan Gibbons

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Summary

An introduction to the field of efficient parallel algorithms and to the techniques for efficient parallelization. It is self-contained and presumes no special knowledge of parallel computers or particular mathematics.

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Efficient Parallel Algorithms by Alan Gibbons

This is an introduction to the field of efficient parallel algorithms and to the techniques for efficient parallelisation. It is self-contained and presumes no special knowledge of parallel computers or particular mathematics. The book emphasises designing algorithms within the timeless and abstracted context of a high-level programming language rather than within highly specific computer architectures. This is an approach which concentrates on the essence of algorithmic theory, determining and taking advantage of the inherently parallel nature of certain types of problem. The authors present regularly-used techniques and a range of algorithms which includes some of the more celebrated and well-known. Efficient Parallel Algorithms is targeted at non-specialists who are considering entering the field of parallel algorithms. It will be particularly useful for courses aimed at advanced undergraduate or new postgraduate students of computer science and mathematics.
"..a coherent introduction for all those who wish to enter this new field of research....a valuable contribution to the expository literature and will certainly become a favoured introduction to the field of parallel algorithms." Mathematical Reviews
"Highly recommended." Choice
"...a successful introduction to the area of parallel algorithms and to methods for parallelisation." N. I. Yanev, Mathematical Reviews
SKU Unavailable
ISBN 13 9780521388412
ISBN 10 0521388414
Title Efficient Parallel Algorithms
Author Alan Gibbons
Condition Unavailable
Binding Type Paperback
Publisher Cambridge University Press
Year published 1989-11-24
Number of pages 268
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.