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GPU-based asynchronous particle swarm optimization

Luca Mussi, Youssef S.G. Nashed, Stefano Cagnoni
Henesis s.r.l., Parma, Italy
Proceedings of the 13th annual conference on Genetic and evolutionary computation, GECCO ’11, 2011

@inproceedings{mussi2011gpu,

   title={GPU-based asynchronous particle swarm optimization},

   author={Mussi, L. and Nashed, Y.S.G. and Cagnoni, S.},

   booktitle={Proceedings of the 13th annual conference on Genetic and evolutionary computation},

   pages={1555–1562},

   year={2011},

   organization={ACM}

}

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This paper describes our latest implementation of Particle Swarm Optimization (PSO) with simple ring topology for modern Graphic Processing Units (GPUs). To achieve both the fastest execution time and the best performance, we designed a parallel version of the algorithm, as fine-grained as possible, without introducing explicit synchronization mechanisms among the particles’ evolution processes. The results we obtained show a significant speed-up with respect to both the sequential version of the algorithm run on an up-to-date CPU and our previously developed parallel implementation within the nVIDIA CUDA architecture.
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