A CUDA-Based Multi-Channel Particle Swarm Algorithm

Wenna Li, Zhenyu Zhang
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引用次数: 4

Abstract

In order to improve the efficiency and accuracy of the particle swarm optimization algorithm in optimization, the parallel CUDA-based particle swarm algorithm is proposed and developed. With the Compute Unified Device Architecture (CUDA) technology, the parallel data structure is defined, and the mechanism of computing tasks mapping to CUDA is described. From the optimization experiments results of 4 benchmark functions it shows that the CUDA-based parallel algorithm can greatly save computing time and improve computing accuracy. This new¿@PSO algorithm is more suitable for the relevant application of the particle swarm algorithm.
基于cuda的多通道粒子群算法
为了提高粒子群优化算法的优化效率和精度,提出并开发了基于cuda的并行粒子群算法。利用计算统一设备架构(CUDA)技术,定义了并行数据结构,描述了计算任务映射到CUDA的机制。从4个基准函数的优化实验结果来看,基于cuda的并行算法可以大大节省计算时间,提高计算精度。这种新的pso算法更适合于粒子群算法的相关应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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