Synthesis of parallel iterative sorts with Multi-core Grammatical Evolution

Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan

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

Abstract

Writing parallel programs is a challenging but unavoidable proposition to take true advantage of multi-core processors. In this paper, we extend Multi-core Grammatical Evolution for Parallel Sorting (MCGE-PS) to evolve parallel iterative sorting algorithms while also optimizing their degree of parallelism. We use evolution to optimize the performance of these parallel programs in terms of their execution time, and our results demonstrate a significant optimization of 11:03 in performance when compared with various MCGE-PS variations as well as the GNU GCC compiler optimizations that reduce the execution time through code minimization. We then analyse the evolutionary (code growth) and nonevolutionary (thread scheduling) factors that cause performance implications. We address them to further optimize the performance and report it as 12:52.

Original languageEnglish
Title of host publicationGECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference
EditorsSara Silva
PublisherAssociation for Computing Machinery, Inc
Pages1059-1066
Number of pages8
ISBN (Electronic)9781450334884
DOIs
Publication statusPublished - 11 Jul 2015
Event17th Genetic and Evolutionary Computation Conference, GECCO 2015 - Madrid, Spain
Duration: 11 Jul 201515 Jul 2015

Publication series

NameGECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference

Conference

Conference17th Genetic and Evolutionary Computation Conference, GECCO 2015
Country/TerritorySpain
CityMadrid
Period11/07/1515/07/15

Keywords

  • Automatic parallelization
  • Grammatical evolution
  • Multi-cores
  • OpenMP
  • Performance optimization
  • Sorting

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