Distributed Genetic Programming on GPUs using CUDA

Created by W.Langdon from gp-bibliography.bib Revision:1.4496

  author =       "Simon L. Harding and Wolfgang Banzhaf",
  title =        "Distributed Genetic Programming on {GPUs} using
  booktitle =    "Workshop on Parallel Architectures and Bioinspired
  year =         "2009",
  editor =       "Ignacio Hidalgo and Francisco Fernandez and 
                 Juan Lanchares",
  pages =        "1--10",
  address =      "Raleigh, NC, USA",
  month =        "13 " # sep,
  publisher =    "Universidad Complutense de Madrid",
  keywords =     "genetic algorithms, genetic programming, GPU",
  URL =          "http://www.evolutioninmaterio.com/preprints/CudaParallelCompilePP.pdf",
  abstract =     "Using of a cluster of Graphics Processing Unit (GPU)
                 equipped computers, it is possible to accelerate the
                 evaluation of individuals in Genetic Programming.
                 Program compilation, fitness case data and fitness
                 execution are spread over the cluster of computers,
                 allowing for the efficient processing of very large
                 datasets. Here, the implementation is demonstrated on
                 datasets containing over 10 million rows and several
                 hundred megabytes in size.

                 Populations of candidate individuals are compiled into
                 NVidia CUDA programs and executed on a set of client
                 computers - each with a different subset of the

                 The paper discusses the implementation of the system
                 and acts as a tutorial for other researchers
                 experimenting with genetic programming and GPUs.",
  notes =        "mono dot net. WPABA'09

Genetic Programming entries for Simon Harding Wolfgang Banzhaf