On The Efficiency of Multi-core Grammatical Evolution (MCGE) Evolving Multi-Core Parallel Programs

Created by W.Langdon from gp-bibliography.bib Revision:1.3949

@InProceedings{Chennupati:2014:NaBIC,
  author =       "Gopinath Chennupati and Jeannie Fitzgerald and 
                 Conor Ryan",
  title =        "On The Efficiency of Multi-core Grammatical Evolution
                 (MCGE) Evolving Multi-Core Parallel Programs",
  booktitle =    "Sixth World Congress on Nature and Biologically
                 Inspired Computing",
  year =         "2014",
  editor =       "Ana Maria Madureira and Ajith Abraham and 
                 Emilio Corchado and Leonilde Varela and Azah Kamilah Muda and 
                 Choo yun Huoy",
  pages =        "238--243",
  address =      "Porto, Portugal",
  month =        "30 " # jul # " - 1 " # jul,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, Grammatical
                 Evolution, OpenMP, Parallel programming, GPU",
  isbn13 =       "978-1-4799-5937-2/14",
  DOI =          "doi:10.1109/NaBIC.2014.6921885",
  size =         "6 pages",
  abstract =     "In this paper we investigate a novel technique that
                 optimises the execution time of Grammatical Evolution
                 through the usage of on-chip multiple processors. This
                 technique, Multi-core 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
                 multi-core architectures. We further discuss that, on
                 these problems, the system evolves longer individuals
                 while they are evaluated quicker than their serial
                 implementation.",
  notes =        "cites \cite{williams98} NaBIC 2014
                 http://www.mirlabs.net/nabic14/",
}

Genetic Programming entries for Gopinath Chennupati Jeannie Fitzgerald Conor Ryan

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