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论文类型：期刊论文

发表时间：2007-12-01

发表刊物：INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL

收录刊物：SCIE、Scopus

卷号：3

期号：6B

页面范围：1707-1714

ISSN号：1349-4198

关键字：particle swarm optimization; fine-grained; parallel process; GPU

摘要：Fine-grained parallel particle swarm optimization (FGPSO), though a popular and robust strategy for solving complicated optimization problems, is sometimes inconvenient to use as its population size is restricted by heavy data communication and the parallel computers are relatively difficult to use, manage, maintain and may not be accessible to most researchers. In this paper, we propose a FGPSO method based on GPU-acceleration, which maps a parallel PSO algorithm to texture-rendering on consumer-level graphics cards. The analytical results demonstrate that the proposed method increases the population size, speeds up its execution and provides ordinary users with a feasible FGPSO solution.