Abusing a hypergraph partitioner for unweighted graph partitioning

Abstract

We investigate using the Mondriaan matrix partitioner for unweighted graph partitioning in the communication volume and edgecut metrics. By converting the unweighted graphs to appropriate matrices, we measure Mondriaan’s performance as a graph partitioner for the 10th DIMACS challenge on graph partitioning and clustering. We find that Mondriaan can effectively be used as a graph partitioner: w.r.t. the edge-cut metric, Mondriaan’s average results are within 21% of the best known results as listed in Chris Walshaw’s partitioning archive.