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
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