Although there has been a tremendous growth of interest in parallel architecture and parallel processing in recent years, comparatively little work has been done on the problem of characterizing parallelism in programs and algorithms. This book, a collection of original papers, specifically addresses that topic.
The editors and two dozen other contributors have produced a work that cuts across numerical analysis, artificial intelligence, and database management, speaking to questions that lie at the heart of current research in these and many other fields of knowledge: How much commonality in algorithm structure is there across problem domains? What attributes of algorithms are the most important in dictating the structure of a parallel algorithm? How can algorithms be matched with languages and architectures? Their book provides an important starting place for a comprehensive taxonomy of parallel algorithms.
The authors are all in the Department of Electrical Engineering at Purdue University. Leah H. Jamieson is a professor, Dennis Gannon an associate professor, and Robert Douglass head of Machine Intelligence. The Characteristics of Parallel Algorithms is included in the Scientific Computation Series, edited by Dennis Gannon.
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