Comparison of Fine Grained and Coarse Grained Parallel Models in Particle Swarm Optimization Algorithm

Date

2011-11-23

Author

Baştürk, Alper
Akay, Rüştü
Kalınlı, Adem

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Many optimization problems are generally complex and required to be solved in parallel architectures due to theircomputational costs. The main issue about the parallelism is that the parallel architectures may affect the performancebecause the original models are constructed based upon the sequential architectures. Therefore, the parallelizationapproaches should consider the efficiency in addition to reducing computational cost. The objective of this paper is two-fold.First goal is presenting a parallelization approaches and investigating the performance efficiency of the parallel models.Second purpose is implementing the models in parallel programming environments and examining the time efficiency. In thisstudy, two parallel models are developed for Particle Swarm Optimization (PSO) algorithm: fine-grained and coarse-grainedmodels. The models are tested on some benchmark problems. Results demonstrate that the parallel models considered canbe efficiently used for improving both performance and speed-up.

Subject Keywords

Parallel approaches, Fine-grained, Coarse-grained, Particle swarm optimization

URI

https://hdl.handle.net/11511/72077
http://archives.un-pub.eu/index.php/P-ITCS/issue/view/53/showToc

Conference Name

2nd World Conference on Information Technology WCIT-2011, (23 - 27 Kasım 2011)

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Citation Formats

A. Baştürk, R. Akay, and A. Kalınlı, “Comparison of Fine Grained and Coarse Grained Parallel Models in Particle Swarm Optimization Algorithm,” Antalya, Türkiye, 2011, p. 751, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/72077.