Aggregative Coarsening for Multilevel Hypergraph Partitioning

TL;DR

This paper introduces two new aggregative coarsening schemes inspired by algebraic multigrid and stable matching, integrated into a hypergraph partitioner to improve performance and quality.

Contribution

The paper presents novel aggregative coarsening schemes for multilevel hypergraph partitioning, enhancing existing algorithms with algebraic multigrid and stable matching techniques.

Findings

Improved partitioning quality on diverse hypergraph problems

Enhanced performance of the Zoltan hypergraph partitioner

Effective integration of new coarsening schemes within multilevel frameworks

Abstract

Algorithms for many hypergraph problems, including partitioning, utilize multilevel frameworks to achieve a good trade-off between the performance and the quality of results. In this paper we introduce two novel aggregative coarsening schemes and incorporate them within state-of-the-art hypergraph partitioner Zoltan. Our coarsening schemes are inspired by the algebraic multigrid and stable matching approaches. We demonstrate the effectiveness of the developed schemes as a part of multilevel hypergraph partitioning framework on a wide range of problems.