Towards an OpenCL implementation of genetic algorithms on GPUs

Authors:
Tadeusz Puź/niakowski;Marek A. Bednarczyk
Affiliations:
Institute of Informatics, University of Gda$#324/sk, Gda$#324/sk, Poland;Faculty of Informatics, Polish-Japanese Institute of Information Technology, Poland
Venue:
SIIS'11 Proceedings of the 2011 international conference on Security and Intelligent Information Systems
Year:
2011

Citing 2
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Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Comparison of Performance between Different Selection Strategies on Simple Genetic Algorithms

CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-2 (CIMCA-IAWTIC'06) - Volume 02

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Abstract

The paper compares usual sequential implementations in C of a Genetic Algorithm with parallel implementations in OpenCL. It turns out that the speedup obtained by turning parallel depends on the choice of the selection methods used in GA. In particular the simple tournament selection method yields better results than the selection based on the roulette rule. In case of the latter which requires a synchronization of threads which manipulate individual chromosomes. This is done to compute the joint fitness of a population and find the best specimen. With the help of scan method this can be achieved with O(logn) complexity.