Pool Evolution: A Parallel Pattern for Evolutionary and Symbolic Computing

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Vydáno v:International Journal of Parallel Programming vol. 44, no. 3 (Jun 2016), p. 531
Hlavní autor: Aldinucci, Marco
Další autoři: Campa, Sonia, Danelutto, Marco, Kilpatrick, Peter, Torquati, Massimo
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Springer Nature B.V.
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MARC

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100 1 |a Aldinucci, Marco 
245 1 |a Pool Evolution: A Parallel Pattern for Evolutionary and Symbolic Computing 
260 |b Springer Nature B.V.  |c Jun 2016 
513 |a Feature 
520 3 |a 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. 
653 |a Algorithms 
653 |a Central processing units--CPUs 
653 |a Parallel processing 
653 |a Computer programming 
653 |a Optimization 
653 |a Analysis 
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653 |a Population 
653 |a Computer science 
653 |a Genetic algorithms 
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700 1 |a Campa, Sonia 
700 1 |a Danelutto, Marco 
700 1 |a Kilpatrick, Peter 
700 1 |a Torquati, Massimo 
773 0 |t International Journal of Parallel Programming  |g vol. 44, no. 3 (Jun 2016), p. 531 
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