GPU-Based Parallel Particle Swarm Optimization Methods for Graph Drawing

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dc.contributor.authorQu, Jianhua
dc.contributor.authorLiu, Xiyu
dc.contributor.authorSun, Minghe
dc.contributor.authorQi, Feng
dc.creator.orcidhttps://orcid.org/0000-0001-8503-9761en_US
dc.date.accessioned2023-04-03T15:50:42Z
dc.date.available2023-04-03T15:50:42Z
dc.date.issued2017-07-30
dc.description.abstractParticle Swarm Optimization (PSO) is a population-based stochastic search technique for solving optimization problems, which has been proven to be effective in a wide range of applications. However, the computational efficiency on large-scale problems is still unsatisfactory. A graph drawing is a pictorial representation of the vertices and edges of a graph. Two PSO heuristic procedures, one serial and the other parallel, are developed for undirected graph drawing. Each particle corresponds to a different layout of the graph. The particle fitness is defined based on the concept of the energy in the force-directed method. The serial PSO procedure is executed on a CPU and the parallel PSO procedure is executed on a GPU. Two PSO procedures have different data structures and strategies. The performance of the proposed methods is evaluated through several different graphs. The experimental results show that the two PSO procedures are both as effective as the force-directed method, and the parallel procedure is more advantageous than the serial procedure for larger graphs.en_US
dc.description.departmentManagement Science and Statisticsen_US
dc.description.sponsorshipNational Natural Science Foundation of Chinaen_US
dc.identifier.citationQu, J., Liu, X., Sun, M., & Qi, F. (2017). GPU-Based Parallel Particle Swarm Optimization Methods for Graph Drawing. Discrete Dynamics in Nature and Society, 2017, 2013673. doi:10.1155/2017/2013673en_US
dc.identifier.issn1607-887X
dc.identifier.otherhttps://doi.org/10.1155/2017/2013673
dc.identifier.urihttps://hdl.handle.net/20.500.12588/1803
dc.language.isoen_USen_US
dc.publisherHindawien_US
dc.relation.ispartofseriesDiscrete Dynamics in Nature and Society, 2017;
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.titleGPU-Based Parallel Particle Swarm Optimization Methods for Graph Drawingen_US
dc.typeArticleen_US

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