Fast Evaluation of GP Trees on GPGPU by Optimizing Hardware Scheduling

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Ogier Maitre and Pierre Collet and Nicolas Lachiche",
  title =        "Fast Evaluation of GP Trees on GPGPU by Optimizing
                 Hardware Scheduling",
  booktitle =    "Proceedings of the 13th European Conference on Genetic
                 Programming, EuroGP 2010",
  year =         "2010",
  editor =       "Anna Isabel Esparcia-Alcazar and Aniko Ekart and 
                 Sara Silva and Stephen Dignum and A. Sima Uyar",
  volume =       "6021",
  series =       "LNCS",
  pages =        "301--312",
  address =      "Istanbul",
  month =        "7-9 " # apr,
  organisation = "EvoStar",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, GPU",
  isbn13 =       "978-3-642-12147-0",
  DOI =          "doi:10.1007/978-3-642-12148-7_26",
  abstract =     "This paper shows that it is possible to use General
                 Purpose Graphic Processing Unit cards for a fast
                 evaluation of different Genetic Programming trees on as
                 few as 32 fitness cases by using the hardware
                 scheduling of NVIDIA cards. Depending on the function
                 set, observed speedup ranges between x50 and x250 on
                 one half of an NVidia GTX295 GPGPU card, vs a single
                 core of an Intel Quad core Q8200.",
  notes =        "Part of \cite{Esparcia-Alcazar:2010:GP} EuroGP'2010
                 held in conjunction with EvoCOP2010 EvoBIO2010 and

Genetic Programming entries for Ogier Maitre Pierre Collet Nicolas Lachiche