by Henri Casanova, et al.
Publisher: CRC Press 2008
Number of pages: 348
The aim of this book is to provide a rigorous yet accessible treatment of parallel algorithms, including theoretical models of parallel computation, parallel algorithm design for homogeneous and heterogeneous platforms, complexity and performance analysis, and fundamental notions of scheduling. The focus is on algorithms for distributed-memory parallel architectures in which computing elements communicate by exchanging messages.
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by Alan Kaminsky - Rochester Institute of Technology
With the book BIG CPU, BIG DATA, my goal is to teach you how to write parallel programs that take full advantage of the vast processing power of modern multicore computers, compute clusters, and graphics processing unit (GPU) accelerators.
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 Al Geist, at al. - The MIT Press
Written by the team that developed the software, this tutorial is the definitive resource for scientists, engineers, and other computer users who want to use PVM to increase the flexibility and power of their high-performance computing resources.
by Sergio Barbarossa, Stefania Sardellitti, Paolo Di Lorenzo - arXiv
We consider the problems of distributed detection and estimation in wireless sensor networks. We provide a general framework aimed to show how an efficient design of a sensor network requires a joint organization of in-network communication.