Abstract
This paper deals with the mapping of the parallel island-based genetic algorithm with unidirectional ring migrations to nVidia CUDA software model. The proposed mapping is tested using Rosenbrock’s, Griewank’s and Michalewicz’s benchmark functions. The obtained results indicate that our approach leads to speedups up to seven thousand times higher compared to one CPU thread while maintaining a reasonable results quality. This clearly shows that GPUs have a potential for acceleration of GAs and allow to solve much complex tasks.
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Pospichal, P., Jaros, J., Schwarz, J. (2010). Parallel Genetic Algorithm on the CUDA Architecture. 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_46
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DOI: https://doi.org/10.1007/978-3-642-12239-2_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12238-5
Online ISBN: 978-3-642-12239-2
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