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Differential evolution algorithm on the GPU with C-CUDA

L.P. de Veronese, R.A. Krohling
Dept. de Inf., Univ. Fed. do Espirito Santo, Vitoria, Brazil
IEEE Congress on Evolutionary Computation (CEC), 2010

@conference{de2010differential,

   title={Differential evolution algorithm on the GPU with C-CUDA},

   author={De Veronese, LP and Krohling, R.A.},

   booktitle={Evolutionary Computation (CEC), 2010 IEEE Congress on},

   pages={1–7},

   organization={IEEE},

   year={2010}

}

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Several areas of knowledge are being benefited with the reduction of the computing time by using the technology of Graphics Processing Units (GPU) and the Compute Unified Device Architecture (CUDA) platform. In case of Evolutionary algorithms, which are inherently parallel, this technology may be advantageous for running experiments demanding high computing time. In this paper, we provide an implementation of the Differential Evolution (DE) algorithm in C-CUDA. The algorithm was tested on a suite of well-known benchmark optimization problems and the computing time has been compared with the same algorithm implemented in C. Results demonstrate that the computing time can significantly be reduced using C-CUDA. As far as we know, this is the first implementation of DE algorithm in C-CUDA.
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