arXiv · 1505.00693
n-Level Hypergraph Partitioning
Abstract
We develop a multilevel algorithm for hypergraph partitioning that contracts the vertices one at a time and thus allows very high quality. This includes a rating function that avoids nonuniform vertex weights, an efficient "semi-dynamic" hypergraph data structure, a very fast coarsening algorithm, and two new local search algorithms. One is a $k$-way hypergraph adaptation of Fiduccia-Mattheyses local search and gives high quality at reasonable cost. The other is an adaptation of size-constrained label propagation to hypergraphs. Comparisons with hMetis and PaToH indicate that the new algorithm yields better quality over several benchmark sets and has a running time that is comparable to hMetis. Using label propagation local search is several times faster than hMetis and gives better quality than PaToH for a VLSI benchmark set.
Explore related subjects
Keep this discovery
Vitali Henne, Henning Meyerhenke, Peter Sanders, Sebastian Schlag, Christian Schulz. 2015-05-04. n-Level Hypergraph Partitioning. https://arxiv.org/abs/1505.00693
Cite the original work for its findings. Save a collection to share your selection of sources.