Current Proceedings on Technology

Yazarlar: Rustu Akay, Alper Basturk, Adem Kalinli

Konular:-

Anahtar Kelimeler:Parallel approaches,Fine-grained,Coarse-grained,Particle swarm optimization  

Özet:   Many optimization problems are generally complex and required to be solved in parallel architectures due to their computational costs. The main issue about the parallelism is that the parallel architectures may affect the performance because the original models are constructed based upon the sequential architectures. Therefore, the parallelization approaches 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 this study, two parallel models are developed for Particle Swarm Optimization (PSO) algorithm: fine-grained and coarse-grained models. The models are tested on some benchmark problems. Results demonstrate that the parallel models considered can be efficiently used for improving both performance and speed-up. 

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