Scalability analysis of the asynchronous, master-slave borg multiobjective evolutionary algorithm

David Hadka, Kamesh Madduri, Patrick Reed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

The Borg Multiobjective Evolutionary Algorithm (MOEA) is a new, efficient, and robust optimizer that outperforms competing optimization methods on numerous complex engineering problems. To date, the Borg MOEA has been successfully applied to problems ranging from aerospace applications to water resources engineering. Problems from these domains often involve expensive design evaluations that require large-scale parallel algorithms to produce results in a reasonable amount of time. This study presents the first theoretical and experimental look at parallelizing the Borg MOEA. First, we derive theoretical models for predicting speedup, efficiency, and processor count lower and upper bounds. Second, we validate these models on a simple problem, DTLZ2, and a harder, non-separable problem, UF11. Third, we examine the effects of scaling on convergence speed and solution quality. These experiments are performed on the 62, 976 core Texas Advanced Computing Center (TACC) Ranger system.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 27th International Parallel and Distributed Processing Symposium Workshops and PhD Forum, IPDPSW 2013
PublisherIEEE Computer Society
Pages425-434
Number of pages10
ISBN (Print)9780769549798
DOIs
StatePublished - Jan 1 2013
Event2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013 - Boston, MA, Japan
Duration: Jul 22 2013Jul 26 2013

Publication series

NameProceedings - IEEE 27th International Parallel and Distributed Processing Symposium Workshops and PhD Forum, IPDPSW 2013

Conference

Conference2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013
CountryJapan
CityBoston, MA
Period7/22/137/26/13

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Software
  • Theoretical Computer Science

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