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Characterizing the genetic programming environment for fifth (GPE5) on a high performance computing cluster

Published:08 July 2009Publication History

ABSTRACT

Solving complex, real-world problems with genetic programming (GP) can require extensive computing resources. However, the highly parallel nature of GP facilitates using a large number of resources simultaneously, which can significantly reduce the elapsed wall clock time per GP run. This paper explores the performance characteristics of an MPI version of the Genetic Programming Environment for FIFTH (GPE5) on a high performance computing cluster. The implementation is based on the island model with each node running the GP algorithm asynchronously. In particular, we examine the effect of several configurable properties of the system including the ratio of migration to crossover, the migration cycle of programs between nodes, and the number of processors used. The problems employed in the study were selected from the fields of symbolic regression, finite algebra, and digital signal processing.

References

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  • Published in

    cover image ACM Conferences
    GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
    July 2009
    2036 pages
    ISBN:9781605583259
    DOI:10.1145/1569901

    Copyright © 2009 ACM

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    Publication History

    • Published: 8 July 2009

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