Computer Science ›› 2014, Vol. 41 ›› Issue (9): 263-268.doi: 10.11896/j.issn.1002-137X.2014.09.050

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Research and Design of Parallel Particle Swarm Optimization Algorithm Based on CUDA

CHEN Feng,TIAN Yu-bo and YANG Min   

  • Online:2018-11-14 Published:2018-11-14

Abstract: In the application of graphic processing unit (GPU) to accelerate particle swarm optimization (PSO) algorithm for parallel computing,many references worsen the performance of PSO algorithm on CPU side in order to highlight the acceleration performance.The concept of “Effective Speedup” was proposed in this paper to measure the achievement of GPU-PSO algorithm and CPU-PSO algorithm.The proposed method aims at accelerating the implementation to the target precision.The GPU parallel algorithm was compared with the best CPU serial algorithm,which does not require the same number of particles between CPU side and GPU side.Experiments based on several benchmark test functions using compute unified device architecture (CUDA) show that substantially increasing the number of particles on GPU side can significantly accelerate the accomplishment of PSO algorithm to the target precision.Compared with CPU-PSO, an “Effective Speedup” of more than 10 has been achieved.

Key words: Particle swarm optimization (PSO),Parallel computing,Graphic processing unit (GPU),Compute unified device architecture (CUDA)

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