A comparative study of three GPU-based metaheuristics

Authors:
Youssef S. G. Nashed;Pablo Mesejo;Roberto Ugolotti;Jérémie Dubois-Lacoste;Stefano Cagnoni
Affiliations:
Department of Information Engineering, University of Parma, Italy;Department of Information Engineering, University of Parma, Italy;Department of Information Engineering, University of Parma, Italy;IRIDIA, CoDE, Université Libre de Bruxelles, Belgium;Department of Information Engineering, University of Parma, Italy
Venue:
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Year:
2012

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Abstract

In this paper we compare GPU-based implementations of three metaheuristics: Particle Swarm Optimization, Differential Evolution, and Scatter Search. A GPU-based implementation, obviously, does not change the general properties of the algorithms. As well, we give for granted that GPU-based implementation of both algorithm and fitness function produces a significant speed-up with respect to a sequential implementation. Accordingly, the main goal of this work has been to fairly assess the efficiency of the GPU-based implementations of the three metaheuristics, based on the statistical analysis of the results they obtain in optimizing a benchmark of twenty functions within a prefixed limited time.