Fast parallel genetic programming: multi-core CPU versus many-core GPU

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Chitty:2012:SC,
  author =       "Darren M. Chitty",
  title =        "Fast parallel genetic programming: multi-core CPU
                 versus many-core GPU",
  journal =      "Soft Computing",
  year =         "2012",
  volume =       "16",
  number =       "10",
  pages =        "1795--1814",
  month =        oct,
  keywords =     "genetic algorithms, genetic programming, GPU",
  language =     "English",
  publisher =    "Springer-Verlag",
  ISSN =         "1432-7643",
  DOI =          "doi:10.1007/s00500-012-0862-0",
  size =         "20 pages",
  abstract =     "Genetic Programming (GP) is a computationally
                 intensive technique which is also highly parallel in
                 nature. In recent years, significant performance
                 improvements have been achieved over a standard GP
                 CPU-based approach by harnessing the parallel
                 computational power of many-core graphics cards which
                 have hundreds of processing cores. This enables both
                 fitness cases and candidate solutions to be evaluated
                 in parallel. However, this paper will demonstrate that
                 by fully exploiting a multi-core CPU, similar
                 performance gains can also be achieved. This paper will
                 present a new GP model which demonstrates greater
                 efficiency whilst also exploiting the cache memory.
                 Furthermore, the model presented in this paper will use
                 Streaming SIMD Extensions to gain further performance
                 improvements. A parallel version of the GP model is
                 also presented which optimises multiple thread
                 execution and cache memory. The results presented will
                 demonstrate that a multi-core CPU implementation of GP
                 can yield performance levels that match and exceed
                 those of the latest graphics card implementations of
                 GP. Indeed, a performance gain of up to 420-fold over
                 standard GP is demonstrated and a threefold gain over a
                 graphics card implementation.",
  notes =        "Intel i7, SIMD (SSE) GP, CPU cache, KDD cup 1999, 20
                 Mux, sextic, Shuttle 0.42 to 18 billion GP operations
                 per sec = 420 to 18480 MGPops up to 8200 to 555410
                 MGPops (2DStackGP multi-core table 12). p1813 'at least
                 a twofold gain in speed over the best graphics card
                 approaches from the literature'",
  URL =          "http://www.cs.bris.ac.uk/Publications/Papers/2001629.pdf",
}

Genetic Programming entries for Darren M Chitty

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