Systemic Computation Using Graphics Processors

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@InProceedings{Rouhipour:2010:ICES,
  author =       "Marjan Rouhipour and Peter J Bentley and 
                 Hooman Shayani",
  title =        "Systemic Computation Using Graphics Processors",
  booktitle =    "Proceedings of the 9th International Conference
                 Evolvable Systems: From Biology to Hardware, ICES
                 2010",
  year =         "2010",
  editor =       "Gianluca Tempesti and Andy M. Tyrrell and 
                 Julian F. Miller",
  series =       "Lecture Notes in Computer Science",
  volume =       "6274",
  pages =        "121--132",
  address =      "York",
  month =        sep # " 6-8",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, GPU",
  isbn13 =       "978-3-642-15322-8",
  DOI =          "doi:10.1007/978-3-642-15323-5_11",
  abstract =     "Previous work created the systemic computer - a model
                 of computation designed to exploit many natural
                 properties observed in biological systems, including
                 parallelism. The approach has been proven through two
                 existing implementations and many biological models and
                 visualisations. However to date the systemic computer
                 implementations have all been sequential simulations
                 that do not exploit the true potential of the model. In
                 this paper the first parallel implementation of
                 systemic computation is introduced. The GPU Systemic
                 Computation Architecture is the first implementation
                 that enables parallel systemic computation by
                 exploiting multiple cores available in graphics
                 processors. Comparisons with the serial implementation
                 when running a genetic algorithm at different scales
                 show that as the number of systems increases, the
                 parallel architecture is several hundred times faster
                 than the existing implementations, making it feasible
                 to investigate systemic models of more complex
                 biological systems.",
  affiliation =  "BIHE University (The Bahai Institute for Higher
                 Education), Iran",
  notes =        "GP?",
}

Genetic Programming entries for Marjan Rouhipour Peter J Bentley Hooman Shayani

Citations