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 Sabu M. Thampi - arXiv
An overview of distributed computing systems. The definition, architecture, characteristics of distributed systems and the various fallacies are discussed. Finally, discusses client/server computing, World Wide Web and types of distributed systems.
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.
by Hank Dietz - The Aggregate
This document discusses the basic approaches to parallel processing available to Linux users: SMP Linux systems, clusters of networked Linux systems, parallel execution using multimedia instructions, and attached processors hosted by a Linux system.
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.