* New approaches to parallel computing are being developed that
make better use of the heterogeneous cluster architecture
* Provides a detailed introduction to parallel computing on
heterogenous clusters
* All concepts and algorithms are illustrated with working
programs that can be compiled and executed on any cluster
* The algorithms discussed have practical applications in a range
of real-life parallel computing problems, such as the N-body
problem, portfolio management, and the modeling of oil
extraction
Autorentext
ALEXEY L. LASTOVETSKY, PhD, is a lecturer in the Department of Computer Science at University College, Dublin. Previously, he was a senior member of the technical staff at Iona Technologies, Ireland, and has also held appointments at the Russian Academy of Sciences and the Moscow State University.
Klappentext
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.
Zusammenfassung
- New approaches to parallel computing are being developed that make better use of the heterogeneous cluster architecture
- Provides a detailed introduction to parallel computing on heterogenous clusters
- All concepts and algorithms are illustrated with working programs that can be compiled and executed on any cluster
- The algorithms discussed have practical applications in a range of real-life parallel computing problems, such as the N-body problem, portfolio management, and the modeling of oil extraction
Inhalt
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.