On the efficiency of Multi-core Grammatical Evolution (MCGE) evolving multi-core parallel programs

Gopinath Chennupati, Jeannie Fitzgerald, Conor Ryan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper we investigate a novel technique that optimizes the execution time of Grammatical Evolution through the usage of on-chip multiple processors. This technique, Multicore Grammatical Evolution (MCGE) evolves natively parallel programs with the help of OpenMP primitives through the grammars, such that not only can we exploit parallelism while evolving individuals, but the final individuals produced can also be executed on parallel architectures even outside the evolutionary system. We test MCGE on two difficult benchmark GP problems and show its efficiency in exploiting the power of the multicore architectures. We further discuss that, on these problems, the system evolves longer individuals while they are evaluated quicker than their serial implementation.

Original languageEnglish
Title of host publication2014 6th World Congress on Nature and Biologically Inspired Computing, NaBIC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages238-243
Number of pages6
ISBN (Electronic)9781479959372
DOIs
Publication statusPublished - 12 Oct 2014
Event2014 6th World Congress on Nature and Biologically Inspired Computing, NaBIC 2014 - Porto, Portugal
Duration: 30 Jul 20141 Aug 2014

Publication series

Name2014 6th World Congress on Nature and Biologically Inspired Computing, NaBIC 2014

Conference

Conference2014 6th World Congress on Nature and Biologically Inspired Computing, NaBIC 2014
Country/TerritoryPortugal
CityPorto
Period30/07/141/08/14

Keywords

  • Grammatical Evolution
  • Multi-cores
  • OpenMP
  • Parallel Programming
  • Symbolic Regression

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