Parallel Computing Works!
by G.C. Fox, R.D. Williams, P.C. Messina
Publisher: Morgan Kaufmann Publishers 1994
A clear illustration of how parallel computers can be successfully applied to large-scale scientific computations. This book demonstrates how a variety of applications in physics, biology, mathematics and other sciences were implemented on real parallel computers to produce new scientific results. It investigates issues of fine-grained parallelism relevant for future supercomputers with particular emphasis on hypercube architecture.
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by Guy Blelloch - The MIT Press
Vector Models for Data-Parallel Computing describes a model of parallelism that extends and formalizes the Data-Parallel model on which the Connection Machine and other supercomputers are based. It presents many algorithms based on the model.
by Dimitri P. Bertsekas, John Tsitsiklis - Athena Scientific
This is a comprehensive and theoretically sound treatment of parallel and distributed numerical methods. It focuses on algorithms that are naturally suited for massive parallelization, and it explores the issues associated with such algorithms.
by Paul E. McKenney
The purpose of this book is to help you understand how to program shared-memory parallel machines. By describing the algorithms that have worked well in the past, we hope to help you avoid some of the pitfalls that have beset parallel projects.
by Ian Parberry - Prentice Hall
The rapid growth of parallel complexity theory has led to a proliferation of parallel machine models. This book presents a unified theory of parallel computation based on a network model. It is the first such synthesis in book form.