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|a 10.1109/TVCG.2017.2689016
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|a eng
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| 100 |
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|a Meyerhenke, Henning
|e verfasserin
|4 aut
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| 245 |
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|a Drawing Large Graphs by Multilevel Maxent-Stress Optimization
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|c 2018
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|a Text
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|a Date Completed 19.03.2019
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|a Date Revised 19.03.2019
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a Drawing large graphs appropriately is an important step for the visual analysis of data from real-world networks. Here we present a novel multilevel algorithm to compute a graph layout with respect to the maxent-stress metric proposed by Gansner et al. (2013) that combines layout stress and entropy. As opposed to previous work, we do not solve the resulting linear systems of the maxent-stress metric with a typical numerical solver. Instead we use a simple local iterative scheme within a multilevel approach. To accelerate local optimization, we approximate long-range forces and use shared-memory parallelism. Our experiments validate the high potential of our approach, which is particularly appealing for dynamic graphs. In comparison to the previously best maxent-stress optimizer, which is sequential, our parallel implementation is on average 30 times faster already for static graphs (and still faster if executed on a single thread) while producing a comparable solution quality
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a Nollenburg, Martin
|e verfasserin
|4 aut
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| 700 |
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|a Schulz, Christian
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on visualization and computer graphics
|d 1996
|g 24(2018), 5 vom: 03. Mai, Seite 1814-1827
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