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Publication Detail
Reducing energy consumption using genetic improvement
  • Publication Type:
    Conference
  • Authors:
    Bruce BR, Petke J, Harman M
  • Publication date:
    11/07/2015
  • Pagination:
    1327, 1334
  • Published proceedings:
    GECCO 2015 - Proceedings of the 2015 Genetic and Evolutionary Computation Conference
  • ISBN-13:
    9781450334723
  • Status:
    Published
Abstract
© 2015 ACM.Genetic Improvement (GI) is an area of Search Based Software Engineering which seeks to improve software's nonfunctional properties by treating program code as if it were genetic material which is then evolved to produce more optimal solutions. Hitherto, the majority of focus has been on optimising program's execution time which, though important, is only one of many non-functional targets. The growth in mobile computing, cloud computing infrastructure, and ecological concerns are forcing developers to focus on the energy their software consumes. We report on investigations into using GI to automatically find more energy efficient versions of the MiniSAT Boolean satisfiability solver when specialising for three downstream applications. Our results find that GI can successfully be used to reduce energy consumption by up to 25%.
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