Abstract
Multi-core computers give the opportunity to solve high-performance applications more efficiently by using parallel computing. In this way, it is possible to achieve the same results in less time compared to the non-parallel version. Since computers continue to grow on the number of cores, we need to make our parallel applications scalable. This paper shows how a Genetic Algorithm (GA) in a non-parallel version takes long time to solve an optimization problem; in comparison, using multi-core parallel computing the processing time can be reduced significantly as the number of cores grows. The tests were made on a quad-core computer; a comparison of the speeding up in relation to the number of cores is shown.
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Serrano, R., Tapia, J., Montiel, O., Sepúlveda, R., Melin, P. (2008). High Performance Parallel Programming of a GA Using Multi-core Technology. In: Castillo, O., Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Soft Computing for Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 154. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70812-4_17
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DOI: https://doi.org/10.1007/978-3-540-70812-4_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70811-7
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