A Fast Hypergraph Bipartitioning Algorithm

Abstract

In this paper, we focus on the hypergraph bipartitioning problem and present a new multilevel hypergraph partitioning algorithm that is much faster and of similar quality compared with hMETIS. In the coarsening phase, successive coarsened hypergraphs are constructed using the MFCC (Modified First-Choice Coarsening) algorithm. After getting a small hypergraph containing only a small number of vertices, we will use a randomized algorithm to obtain an initial partition and then apply an A-FM (Alternating Fiduccia-Mattheyses) refinement algorithm to optimize it. In the uncoarsening phase, we will extract clusters level by level and apply the A-FM repeatedly. Experiments on large benchmarks issued in the DAC 2012 Routability-Driven Placement Contest show that we can achieve similar or even better quality (1% improvement in minimum cut on average) and save 50% to 80% running time comparing with the state-of-the-art partitioner hMETIS.