GPU-based Parallel Particle Swarm Optimization

被引:120
|
作者
Zhou, You [1 ]
Tan, Ying [1 ]
机构
[1] Peking Univ, Key Lab Machine Percept & Intelligence, Minist Educ, Beijing 100871, Peoples R China
基金
国家高技术研究发展计划(863计划);
关键词
D O I
10.1109/CEC.2009.4983119
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A novel parallel approach to run standard particle swarm optimization (SPSO) on Graphic Processing Unit (GPU) is presented in this paper. By using the general-purpose computing ability of GPU and based on the software platform of Compute Unified Device Architecture (CUDA) from NVIDIA, SPSO can be executed in parallel on GPU. Experiments are conducted by running SPSO both on GPU and CPU, respectively, to optimize four benchmark test functions. The running time of the SPSO based on GPU (GPU-SPSO) is greatly shortened compared to that of the SPSO on CPU (CPU-SPSO). Running speed of GPU-SPSO can be more than 11 times as fast as that of CPU-SPSO, with the same performance. compared to CPU-SPSO, GPU-SPSO shows special speed advantages on large swarm population applications and hign dimensional problems, which can be widely used in real optimizing problems.
引用
收藏
页码:1493 / +
页数:2
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