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EASEA: specification and execution of evolutionary algorithms on GPGPU

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Abstract

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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Notes

  1. http://www.lsiit.u-strasbg.fr/easea

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Authors and Affiliations

  1. Pôle API, Bd Sébastien Brant BP 10413, 67412, Illkirch Cedex, France

    Ogier Maitre, Frédéric Krüger, Stéphane Querry, Nicolas Lachiche & Pierre Collet

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  1. Ogier Maitre
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  2. Frédéric Krüger
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  3. Stéphane Querry
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  4. Nicolas Lachiche
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  5. Pierre Collet
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Correspondence to Ogier Maitre.

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Maitre, O., Krüger, F., Querry, S. et al. EASEA: specification and execution of evolutionary algorithms on GPGPU. Soft Comput 16, 261–279 (2012). https://doi.org/10.1007/s00500-011-0718-z

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