Parallel Computing on Heterogeneous Networks

A timely reference on new approaches to parallel computing

Traditional software for parallel computing typically spreads computations evenly over a set of linked processors. This, however, may not always be the best way of maximizing the performance of a given network or cluster of computers. By taking account of the actual performance of individual processors and the links between them, parallel computing on heterogeneous networks offers significant improvements in parallel computation. Alexey Lastovetsky’s Parallel Computing on Heterogeneous Networks provides a timely resource on this innovative technology.

This forward-looking text begins with a general introduction to parallel computing, then progresses to the specifics of parallel computing with heterogeneous networks. Practically oriented, the book includes illustrative algorithms in the mpC programming language, a unique high-level software tool designed by the author specifically for programming heterogeneous parallel algorithms. All concepts and algorithms are illustrated with working programs that can be compiled or executed on any cluster.

Some of the practical applications of these algorithms include:

• The N-body problem
• The parallel testing of distributed software
• The modeling of oil extraction

All of the contents are also illustrated by carefully tested source code, allowing readers to play with the presented software tools and algorithms–particularly with the mpC programming language–while reading the book. Appendices provide both the complete source code and user’s guide for the principal applications used to illustrate the book’s material. Parallel Computing on Heterogeneous Networks proves a superior reference for researchers and graduate students in computer science.

Table of Contents

Acknowledgments.

Introduction.

PART I. EVOLUTION OF PARALLEL COMPUTING.

Serial Scalar Processor.

Vector and Superscalar Processors.

Shared Memory Multiprocessors.

Distributed Memory Multiprocessors.

Networks of Computers: Architecture and Programming Challenges.

PART II. PARALLEL PROGRAMMING FOR NETWORKS OF COMPUTERS WITH MPC AND HMPI.

Introduction to mpC.

Advanced Heterogeneous Parallel Programming in mpC.

Toward a Message-Passing Library for Heterogeneous Networks of Computers.

PART III. APPLICATIONS OF HETEROGENEOUS PARALLEL COMPUTING.

Scientific Applications.

Business and Software Engineering Applications.

Appendix A: The mpC N-Body Application. 

Appendix B: The Block Cyclic Matrix Multiplication Routine for Heterogeneneous Platforms.

Appendix C: The Parallel Adaptive Quadrature Routine.

Appendix D: The mpC User's Guide.

Bibliography.

Index.

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一本關於新型並行計算方法的及時參考資料
傳統的並行計算軟體通常將計算均勻地分散在一組連接的處理器上。然而，這並不一定是最大化給定網絡或計算機集群性能的最佳方法。通過考慮個別處理器的實際性能和它們之間的連接，異構網絡上的並行計算提供了顯著的改進。Alexey Lastovetsky的《異構網絡上的並行計算》提供了一個及時的資源，介紹了這項創新技術。
這本前瞻性的書籍首先介紹了並行計算的一般概念，然後深入探討了異構網絡上的並行計算的具體內容。這本實用導向的書籍包括了mpC編程語言中的示例算法，這是作者專門為編寫異構並行算法而設計的獨特高級軟體工具。所有的概念和算法都有工作中的程式示例，可以在任何集群上編譯或執行。
這些算法的一些實際應用包括：
- N體問題
- 分佈式軟體的並行測試
- 油田開采模擬
所有內容都有經過仔細測試的源代碼作為示例，讓讀者在閱讀書籍的同時可以使用所呈現的軟體工具和算法，特別是mpC編程語言。附錄提供了用於說明書籍內容的主要應用程式的完整源代碼和使用者指南。《異構網絡上的並行計算》是計算機科學研究人員和研究生的優秀參考資料。