GPU-based coevolutionary particle swarm optimization

被引：0
|
作者：
Zhao Liang [1 ]
Zhu Yanxing [2 ]
Zhang Jianyu [1 ]
Ye Zhencheng [1 ]
机构：
[1] East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China
[2] Ethylene Plant Jilin Petrochem Co Ltd, PetroChina, Jilin 132021, Jilin, Peoples R China
来源：
PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017) | 2017年
关键词：
GPU; CUDA; Particle swarm optimization; Coevolutionary particle swarm optimization;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Coevolutionary particle swarm optimization (CPSO) algorithm has been investigated and applied in the real world widely. When tackling the large-scale and complex real time optimization problems, the running time of CPSO algorithm is a barrier. In this paper, Graphics Processing Unit (GPU) is introduced to provide speedup in order to meet the real time requirements. The CPSO algorithm has been implemented on GPU concurrently using the CUDA architecture. The performance and run time of CPU-based and GPU-based CPSO algorithms are compared in detail. The experiment result shows that the GPU-based parallel computation mode can shorten the run time of CPSO algorithm apparently.
引用
收藏
页码：9883 / 9887
页数：5
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