A parallel Bees Algorithm implementation on GPU
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...
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| Published in | Journal of systems architecture Vol. 60; no. 3; pp. 271 - 279 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Amsterdam
Elsevier B.V
01.03.2014
Elsevier Sequoia S.A |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1383-7621 1873-6165 |
| DOI | 10.1016/j.sysarc.2013.09.007 |
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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. |
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| AbstractList | 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. [PUBLICATION 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. |
| Author | Chang, Yue-Shan Yuan, Shyan-Ming Luo, Guo-Heng Huang, Sheng-Kai |
| Author_xml | – sequence: 1 givenname: Guo-Heng surname: Luo fullname: Luo, Guo-Heng email: lasifu@gmail.com organization: Dept. of Computer Science and Engineering, National Chiao-Tung University, 1001, University Road, Hsinchu 300, Taiwan, ROC – sequence: 2 givenname: Sheng-Kai surname: Huang fullname: Huang, Sheng-Kai email: kkuume@gmail.com organization: Dept. of Computer Science and Engineering, National Chiao-Tung University, 1001, University Road, Hsinchu 300, Taiwan, ROC – sequence: 3 givenname: Yue-Shan surname: Chang fullname: Chang, Yue-Shan email: ysc.ntpu@gmail.com organization: Dept. of Computer Science and Information Engineering, National Taipei University, 151, University Road, New Taipei City 237, Taiwan, ROC – sequence: 4 givenname: Shyan-Ming surname: Yuan fullname: Yuan, Shyan-Ming email: smyuan@gmail.com organization: Dept. of Computer Science and Engineering, National Chiao-Tung University, 1001, University Road, Hsinchu 300, Taiwan, ROC |
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| References_xml | – reference: H. Narasimhan, Parallel artificial bee colony (PABC) algorithm, in: 2009 World Congress on Nature & Biologically Inspired Computing, 2009, pp. 306–311. – volume: 181 start-page: 4642 year: 2011 end-page: 4657 ident: b0165 article-title: Evaluation of parallel particle swarm optimization algorithms within the CUDA architecture publication-title: Information Sciences – volume: 15 start-page: 1657 year: August 2011 end-page: 1669 ident: b0080 article-title: Graphics processing units and genetic programming: an overview publication-title: Soft Computing – reference: M. Phillips. Available from: < – volume: 62 start-page: 1421 year: 2002 end-page: 1432 ident: b0135 article-title: A parallel implementation of ant colony optimization publication-title: Journal of Parallel and Distributed Computing – reference: José M. Cecilia, José M. 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