Abstract
This paper presents the first implementation of a generic memetic algorithm on one of the two GPU (Graphic Processing Unit) chips of a GTX295 gaming card. Observed speedups range between ×70 and ×120, mainly depending on the population size.
An automatic parallelization of a memetic algorithm is provided through an upgrade of the EASEA language, so that the EC community can benefit from the extraordinary power of these cards without needing to program them.
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Krüger, F., Maitre, O., Jiménez, S., Baumes, L., Collet, P. (2010). Speedups between ×70 and ×120 for a Generic Local Search (Memetic) Algorithm on a Single GPGPU Chip. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2010. Lecture Notes in Computer Science, vol 6024. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12239-2_52
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DOI: https://doi.org/10.1007/978-3-642-12239-2_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12238-5
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