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dc.contributor.authorGajdoš, Petr
dc.contributor.authorJežowicz, Tomáš
dc.contributor.authorUher, Vojtěch
dc.contributor.authorDohnálek, Pavel
dc.date.accessioned2016-03-30T11:53:16Z
dc.date.available2016-03-30T11:53:16Z
dc.date.issued2016
dc.identifier.citationSwarm and Evolutionary Computation. 2016, vol. 26, p. 56-63.cs
dc.identifier.issn2210-6502
dc.identifier.issn2210-6510
dc.identifier.urihttp://hdl.handle.net/10084/111415
dc.description.abstractGraphs in computer science are widely used in social network analysis, computer networks, transportation networks, and many other areas. In general, they can visualize relationships between objects. However, fast drawing of graphs and other structures containing large numbers of data points with readable layouts is still a challenge. This paper describes a novel variant of the Fruchterman–Reingold graph layout algorithm which is adapted to GPU parallel architecture. A new approach based on space-filling curves and a new way of repulsive forces computation on GPU are described. The paper contains both performance and quality tests of the new algorithm.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesSwarm and Evolutionary Computationcs
dc.relation.urihttp://dx.doi.org/10.1016/j.swevo.2015.07.006cs
dc.rightsCopyright © 2015 Elsevier B.V. All rights reserved.cs
dc.subjectGraph layoutscs
dc.subjectNearest neighborscs
dc.subjectFruchterman–Reingoldcs
dc.subjectFast graph visualizationcs
dc.subjectGPUcs
dc.subjectCUDAcs
dc.titleA parallel Fruchterman-Reingold algorithm optimized for fast visualization of large graphs and swarms of datacs
dc.typearticlecs
dc.identifier.doi10.1016/j.swevo.2015.07.006
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume26cs
dc.description.lastpage63cs
dc.description.firstpage56cs
dc.identifier.wos000370099700006


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