A parallel Bees Algorithm implementation on GPU

  • Authors:

  • Guo-Heng Luo;Sheng-Kai Huang;Yue-Shan Chang;Shyan-Ming Yuan

  • Affiliations:

  • Dept. of Computer Science and Engineering, National Chiao-Tung University, 1001, University Road, Hsinchu 300, Taiwan, ROC;Dept. of Computer Science and Engineering, National Chiao-Tung University, 1001, University Road, Hsinchu 300, Taiwan, ROC;Dept. of Computer Science and Information Engineering, National Taipei University, 151, University Road, New Taipei City 237, Taiwan, ROC;Dept. of Computer Science and Engineering, National Chiao-Tung University, 1001, University Road, Hsinchu 300, Taiwan, ROC

  • Venue:
  • Journal of Systems Architecture: the EUROMICRO Journal
  • Year:
  • 2014

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Abstract

Bees Algorithm is a population-based method that is a computational bound algorithm whose inspired by the natural behavior of honey bees to finds a near-optimal solution for the search problem. Recently, many parallel swarm based algorithms have been developed for running on GPU (Graphic Processing Unit). Since nowadays developing a parallel Bee Algorithm running on the GPU becomes very important. In this paper, we extend the Bees Algorithm (CUBA (i.e. CUDA based Bees Algorithm)) in order to be run on the CUDA (Compute Unified Device Architecture). CUBA (CUDA based Bees Algorithm). We evaluate the performance of CUBA by conducting some experiments based on numerous famous optimization problems. Results show that CUBA significantly outperforms standard Bees Algorithm in numerous different optimization problems.