The Characteristics of parallel algorithms
Leah H Jamieson, Dennis Gannon, Robert J Douglass
Mit Press, 1987 - Parallel programming (Computer science) - 440 pages
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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Programming Paradigms for Nonshared Memory Parallel Computers
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algorithm characteristics application array Bandwidth basic BLAS broadcast cache CAPP column communication graph complexity Computer Science concurrent systems contraction cycle data dependencies data flow data structures datapath distributed dynamic Dynamic Time Warping efficient example execution factorization Fast Fourier Transform Figure Fortran function global granularity hardware hcyc hierarchy IEEE Image Processing implementation input interconnection iteration language large-grain LGDF program linear algebra loop macro mapping matrix methods metrics MIMD module multiprocessor node number of processors operations optimal output parallel algorithms parallel architectures parallel computation Parallel Processing parallel program partition path PDEs performance pipeline pixel Prep-P problem rithm routines SCHEDULE sequence sequential serial shared memory SIMD simulated annealing simulation single solution solving speech recognition speedup subroutine subtrees synchronization systolic systolic arrays task technique tion update values variables vector virtual algorithm VLSI XXX XXX XXX