Parallel multilevel algorithms for hypergraph partitioning

In this paper, we present parallel multilevel algorithms for the hypergraph partitioning problem. In particular, we describe schemes for parallel coarsening, parallel greedy k-way refinement and parallel multi-phase refinement. Using an asymptotic theoretical performance model, we derive the isoefficiency function for our algorithms and hence show that they are technically scalable when the maximum vertex and hyperedge degrees are small. We conduct experiments on hypergraphs from six different application domains to investigate the empirical scalability of our algorithms both in terms of runtime and partition quality. Our findings confirm that the quality of partition produced by our algorithms is stable as the number of processors is increased while being competitive with those produced by a state-of-the-art serial multilevel partitioning tool. We also validate our theoretical performance model through an isoefficiency study. Finally, we evaluate the impact of introducing parallel mu...

• Type: Journal
• Year: 2008
• Where: JPDC
• Authors: Aleksandar Trifunovic, William J. Knottenbelt
• Keywords: JPDC 2008, Multi-phase Refinement, Parallel Multilevel Algorithm, Theoretical Performance Model