Swarm’s flight: Accelerating the particles using C-CUDA
Departmento de Informatica, PPGI, Universidade Federal do Espirito Santo, Vitoria, ES, Brazil
IEEE Congress on Evolutionary Computation, 2009. CEC ’09
@inproceedings{de2009swarm,
title={Swarm’s flight: accelerating the particles using C-CUDA},
author={De P, V. and others},
booktitle={Proceedings of the Eleventh conference on Congress on Evolutionary Computation},
pages={3264–3270},
year={2009},
organization={IEEE Press}
}
With the development of Graphics Processing Units (GPU) and the Compute Unified Device Architecture (CUDA) platform, several areas of knowledge are being benefited with the reduction of the computing time. Our goal is to show how optimization algorithms inspired by Swarm Intelligence can take profit from this technology. In this paper, we provide an implementation of the Particle Swarm Optimization (PSO) algorithm in C-CUDA. The algorithm was tested on a suite of well-known benchmark optimization problems and the computing time has been compared with the same algorithm implemented in C and Matlab. Results demonstrate that the computing time can significantly be reduced using C-CUDA. As far as we know, this is the first implementation of PSO in C-CUDA.
June 2, 2011 by hgpu
