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Pool Evolution: A Parallel Pattern for Evolutionary and Symbolic Computing

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Publié dans:International Journal of Parallel Programming vol. 44, no. 3 (Jun 2016), p. 531
Auteur principal: Aldinucci, Marco
Autres auteurs: Campa, Sonia, Danelutto, Marco, Kilpatrick, Peter, Torquati, Massimo
Publié:
Springer Nature B.V.
Sujets:
Algorithms
Central processing units > CPUs
Parallel processing
Computer programming
Optimization
Analysis
Studies
Population
Computer science
Genetic algorithms
Semantics
Programmers
Accès en ligne:Citation/Abstract
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Résumé:Issue Title: Special Issue on High-Level Parallel Programming and Applications We introduce a new parallel pattern derived from a specific application domain and show how it turns out to have application beyond its domain of origin. The pool evolution pattern models the parallel evolution of a population subject to mutations and evolving in such a way that a given fitness function is optimized. The pattern has been demonstrated to be suitable for capturing and modeling the parallel patterns underpinning various evolutionary algorithms, as well as other parallel patterns typical of symbolic computation. In this paper we introduce the pattern, we discuss its implementation on modern multi/many core architectures and finally present experimental results obtained with FastFlow and Erlang implementations to assess its feasibility and scalability.
ISSN:0885-7458
1573-7640
0091-7036
DOI:10.1007/s10766-015-0358-5
Source:ABI/INFORM Global