Authors: Rogério De Moraes Calazan; Nadia Nedjah; Luiza De Macedo Mourelle
Addresses: Department of Communication and Information Technology, Brazilian Navy, Rua 1o. de Março, 118, 5o. andar, Centro, Rio de Janeiro, RJ, Brazil. ' Department of Electronics Engineering and Telecommunications, State University of Rio de Janeiro, Rua São Francisco Xavier, 524, bloco F, sala 5145, Maracanã, Rio de Janeiro, RJ, Brazil ' Department of Systems Engineering and Computation, State University of Rio de Janeiro, Rua São Francisco Xavier, 524, bloco F, sala 5145, Maracanã, Rio de Janeiro, RJ, Brazil
Abstract: The particle swarm optimisation or PSO is a heuristic based on a population of individuals, in which the candidates for a solution of the problem at hand evolve through a simulation process of a social adaptation simplified model. Combining robustness, efficiency and simplicity, PSO has gained great popularity as many successful applications are reported. The algorithm has proven to have several advantages over other algorithms that are based on swarm intelligence principles. The use of PSO for solving problems that involve computationally demanding functions often results in low performance. In order to accelerate the process, one can proceed with the parallelisation of the algorithm and/or mapping it directly onto hardware. This paper presents a novel massively parallel co-processor for PSO implemented in reconfigurable hardware. The implementation results show that the proposed architecture is very promising as it achieved superior performance in terms of execution time when compared to the direct software execution of the algorithm.
Keywords: swarm intelligence; reconfigurable hardware; particle swarm optimisation; PSO; parallel co-processors; high performance architectures.
International Journal of High Performance Systems Architecture, 2011 Vol.3 No.4, pp.233 - 240
Available online: 20 Feb 2012 *Full-text access for editors Access for subscribers Purchase this article Comment on this article