Performance Evaluation of Particle Swarm Optimization Algorithms on GPU Using CUDA
Department of CSE, Lakireddy Bali Reddy College of Engineering, Mylavaram, India
International Journal of Engineering Science & Advanced Technology (IJESAT), Volume 2, Issue 1, p.257 – 265, 2012
@article{reddy2012performance,
title={Performance Evaluation of Particle Swarm Optimization Algorithms on GPU Using CUDA},
author={Reddy, V.K. and Reddy, LSS},
journal={International Journal of Engineering Science & Advanced Technology (IJESAT)},
volume={2},
number={1},
year={2012}
}
Particle Swarm Optimization (PSO) may be easy but powerful optimization algorithm relying on the social behavior of the particles. PSO has become popular due to its simplicity and its effectiveness in wide range of application with low computational cost. The main objective of this paper is to implement a parallel Asynchronous version and Synchronous versions of PSO on the Graphical Processing Unit (GPU) and compare the performance in terms of execution time and speedup with their sequential versions on the GPU. We also present the Implementation details and Performance observations of parallel PSO algorithms on GPU using Compute Unified Device Architecture (CUDA), a software platform from nVIDIA. We observed that the Asynchronous version of the algorithm outperforms other versions of the algorithm.
February 5, 2012 by hgpu
