Multi-GPU Island-Based Genetic Algorithm

Namrata Mahakalkar, A. R. Mahajan
Department of Computer Science and Engineering, P.I.E.T, Nagpur
International Journal on Advanced Computer Theory and Engineering, Volume 1, Issue 2, 2012


   title={Multi-GPU Island-Based Genetic Algorithm},

   author={Mahakalkar, Namrata and Mahajan, AR},



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Genetic algorithms are effective in solving many optimization tasks. However, the long execution time associated with it prevents its use in many domains. In this paper, we propose a new approach for parallel implementation of genetic algorithm on graphics processing units (GPUs) using CUDA programming model. This paper introduces a novel implementation of the genetic algorithm exploiting a multi-GPU cluster. The proposed implementation employs an island-based genetic algorithm where every GPU evolves a single island. Recently there has been a growing interest in developing parallel algorithms using graphic processing units (GPU) also referred as GPU computation. Advances in the video gaming industry have led to the production of low-cost, high performance graphics processing units that possess more memory bandwidth and computational capability than central processing units (CPUs). As GPUs are available in personal computers, and they are easy to use and manage through several GPU programming languages, graphics engines are being adopted widely in scientific computing.
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