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EASEA: specification and execution of evolutionary algorithms on GPGPU

Ogier Maitre, Frederic Kruger, Stephane Querry, Nicolas Lachiche, Pierre Collet
Pole API, Bd Sebastien Brant BP 10413, 67412 Illkirch Cedex, France
Soft Computing – A Fusion of Foundations, Methodologies and Applications (26 May 2011), pp. 1-19.

@article{maitre2011easea,

   title={EASEA: specification and execution of evolutionary algorithms on GPGPU},

   author={Maitre, O. and Kr{\"u}ger, F. and Querry, S. and Lachiche, N. and Collet, P.},

   journal={Soft Computing-A Fusion of Foundations, Methodologies and Applications},

   pages={1–19},

   publisher={Springer},

   year={2011}

}

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EASEA is a framework designed to help non-expert programmers to optimize their problems by evolutionary computation. It allows to generate code targeted for standard CPU architectures, GPGPU-equipped machines as well as distributed memory clusters. In this paper, EASEA is presented by its underlying algorithms and by some example problems. Achievable speedups are also shown onto different NVIDIA GPGPUs cards for different optimization algorithm families.
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