A parallel Fruchterman-Reingold algorithm optimized for fast visualization of large graphs and swarms of data

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Authors

Gajdoš, Petr
Ježowicz, Tomáš
Uher, Vojtěch
Dohnálek, Pavel

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Elsevier

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Abstract

Graphs 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.

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Subject(s)

Graph layouts, Nearest neighbors, Fruchterman–Reingold, Fast graph visualization, GPU, CUDA

Citation

Swarm and Evolutionary Computation. 2016, vol. 26, p. 56-63.