Is Parallel Programming Hard, And, If So, What Can You Do About It?
by Paul E. McKenney
Number of pages: 413
The purpose of this book is to help you understand how to program shared-memory parallel machines without risking your sanity. By describing the algorithms and designs that have worked well in the past, we hope to help you avoid at least some of the pitfalls that have beset parallel projects.
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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 Pawel Pawlewski (ed.) - InTech
The present monograph focuses on Petri Nets applications in two main areas: manufacturing and computer science. The theory of Petri Nets is still developing: some directions of investigations are presented in this volume.
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In the near future every programmer will need to understand parallelism, a powerful way to run programs fast. The authors of this straightforward tutorial provide the instruction that will transform ordinary programmers into parallel programmers.
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The book gives an overview of the developments, applications and future trends in high performance computing for all platforms. It addresses all aspects of parallel computing, including applications, hardware and software technologies.