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- Title: Parallel Computing Works!
- Author(s) Geoffrey C. Fox, Roy D. Williams, Paul C. Messina
- Publisher: Morgan Kaufmann; 1 edition (May 15, 1994)
- Hardcover: 977 pages
- eBook: HTML
- Language: English
- ISBN-10: 1558602534
- ISBN-13: 978-1558602533
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A clear illustration of how parallel computers can be successfully applied to large-scale scientific computations. This book demonstrates how a variety of applications in physics, biology, mathematics and other sciences were implemented on real parallel computers to produce new scientific results.
It investigates issues of fine-grained parallelism relevant for future supercomputers with particular emphasis on hypercube architecture.
About the Authors- Geoffrey Fox is Professor of Computer Science, Informatics, and Physics at Indiana University, where he is also the Director of the Grid. He is currently focussing on earthquake science, and GRID technology to build electronic communities linking resources and people.
- Parallel Computing and Programming
- Algorithms and Data Structures
- Computational Complexity
- Computational and Algorithmic Mathematics
- Parallel Computing Works! (Geoffrey C. Fox, et al.)
- The Mirror Site (1) - HTML
- The Mirror Site (1) - PDF
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Introduction to Parallel Computing (Blaise Barney)
This book explains how to design, debug, and evaluate the performance of distributed and shared-memory programs. It teaches students how to compile, run and modify example programs. It is a complete end-to-end source of information on all aspects.
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Is Parallel Programming Hard? If So, What Can You Do About It?
It examines what makes parallel programming hard, and describes design techniques that can help you avoid many parallel-programming pitfalls. It is primarily intended for low-level C/C++ code, but offers valuable lessons for other environments as well.
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The Practice of Parallel Programming (Sergey A. Babkin)
This book provides an advanced guide to the issues of the parallel and multithreaded programming. It goes beyond the high-level design of the applications, into the details that are often overlooked but vital to make the programs work.
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Programming on Parallel Machines: GPU, Multicore, Clusters, etc.
The main goal of the book is to present parallel programming techniques that can be used in many situations for many application areas and which enable the reader to develop correct and efficient parallel programs.
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Parallel Algorithms (Henri Casanova, et al)
Focusing on algorithms for distributed-memory parallel architectures, the book extracts fundamental ideas and algorithmic principles from the mass of parallel algorithm expertise and practical implementations developed over the last few decades.
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