Evolutionary Computing on Consumer Graphics Hardware

Authors:
Ka-Ling Fok;Tien-Tsin Wong;Man-Leung Wong
Affiliations:
Chinese University of Hong Kong;Chinese University of Hong Kong;Lingnan University
Venue:
IEEE Intelligent Systems
Year:
2007

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Abstract

Evolutionary algorithms are effective, robust methods for solving many practical problems such as feature selection,electrical-circuitsynthesis, and data mining. However, they can take a long time on some difficult problems because they need toperform several fitnessevaluations. Parallelizing these algorithms is a promising way to overcome this limitation. The authors proposeto implement a parallelEA on consumer graphics cards. Experiments demonstrated that this parallel EA is much more effective than anordinary EA, achievingbetween 1.25 to 5 times greater speed using a current-generation graphics card. Because most personal computershave graphics cards, andthese computers are easy to use and manage, more people will be able to use the parallel algorithm to solvetheir real-world problems.