Parallel Computer Architectures

Duncan, Ralph

doi:10.1016/s0065-2458(08)60325-3

Cited by 7 publications

(1 citation statement)

References 63 publications

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“…This capability that is very desirable in solving many multimodal, multidimensional optimization problems. With the rapid development of various parallel processing systems [4,5,6,7,9,14], researchers are enabled to take up very large optimization problems and solve them in parallel [1,3,10,11]. While many traditional optimization algorithms are sequential in nature, genetic algorithm lends itself very nicely to parallelization.…”

Section: Introductionmentioning

confidence: 99%

Problem independent parallel genetic algorithm for design optimization

Atiqullah

2002

Proceedings 16th International Parallel and Distributed Processing Symposium

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Genetic Algorithms, originally inspired by the nature, have come a long a way in the past decade to establish itself as a numerical optimization tool of choice. The simplicity of its structure, robustness of its operation, global view of its search technique, efficiency of its sorting though the unknown, all contribute to the excellence of genetic algorithm as an engineering design optimization tool. With the advent of modern parallel and distributed supercomputer systems, there is a renewed enthusiasm about fast genetic algorithms that efficiently solves very large numerical optimization problems utilizing these machines. The working of genetic algorithms is analyzed to extract parallelism in its functionality. The effects of various parallelization proposals and details of a parallel implementation are provided. Several representative problem solutions are presented to demonstrate the utility of the implementation. These indicate a strong future for parallel genetic algorithms for solving a large variety of scientific, engineering, and design problems.

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Section: Introductionmentioning

confidence: 99%

Problem independent parallel genetic algorithm for design optimization

Atiqullah

2002

Proceedings 16th International Parallel and Distributed Processing Symposium

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Study on Parallel Computing

Chen

2009

Lecture Notes in Computer Science

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Abstract. In this talk, we present a general survey on parallel computing. The main contents include parallel computer system which is the hardware platform of parallel computing, parallel algorithm which is the theoretical base of parallel computing, parallel programming which is the software support of parallel programming, parallel application which is the development impetus of parallel computing. Specially, we also introduce some enabling technologies of parallel application. We argue that the parallel computing research should form an integrated methodology of "architecture-algorithm-programming-application". Only in this way, parallel computing research becomes continuous development and more realistic.

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The Cubemat: A parallel interconnection model consisting of hypercube and global bus connections

Shibusawa

1992

Future Generation Computer Systems

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Parallel Computer Architectures

Cited by 7 publications

References 63 publications

Problem independent parallel genetic algorithm for design optimization

Problem independent parallel genetic algorithm for design optimization

Study on Parallel Computing

The Cubemat: A parallel interconnection model consisting of hypercube and global bus connections

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