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Population Parallel GP on the G80 GPU

Denis Robilliard, Virginie Marion-Poty, Cyril Fonlupt
Laboratoire d’Informatique du Littoral, Maison de la Recherche Blaise Pascal, Calais Cedex, France
Proceedings of the 11th European conference on Genetic programming, EuroGP’08

@conference{robilliard2008population,

   title={Population parallel GP on the G80 GPU},

   author={Robilliard, D. and Marion-Poty, V. and Fonlupt, C.},

   booktitle={Proceedings of the 11th European conference on Genetic programming},

   pages={98–109},

   isbn={3540786708},

   year={2008},

   organization={Springer-Verlag}

}

The availability of low cost powerful parallel graphics cards has stimulated a trend to port GP on Graphics Processing Units (GPUs). Previous works on GPUs have shown evaluation phase speedups for large training cases sets. Using the CUDA language on the G80 GPU, we show it is possible to efficiently interpret several GP programs in parallel, thus obtaining speedups also for small training sets starting at less than 100 training cases. Our scheme was embedded in the well-known ECJ library, providing an easy entry point for owners of G80 GPUs.
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