Talks and Poster Presentations (with Proceedings-Entry):
M. Nöllenburg, H. Meyerhenke, C. Schulz:
"Drawing Large Graphs by Multilevel Maxent-Stress Optimization";
Talk: Graph Drawing and Network Visualization (GDŽ15),
Los Angeles, USA;
- 2015-09-26; in: "Graph Drawing and Network Visualization (GD'15)",
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 a recently proposed metric that combines layout stress and entropy. As opposed to previous work, we do not solve the 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 one thread) while producing a comparable solution quality.
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Created from the Publication Database of the Vienna University of Technology.