Finding near-optimal cuts: an empirical evaluation

We empirically evaluate the performance of a provably near optimal approximation algorithm for finding minimum quotient cuts against variants of methods that are currently in use for graph partitioning. We report on experiments on graphs with up to 100,000 nodes and 650,000 edges. These experiments show that for a certain class of graphs the approximation algorithm becomes relatively more and more effective as problem sizes grow. We hope that this provides motivation for using the theoretically attractive approximation algorithm for partitioning large graphs that occur in practice. As a caveat we compare our methods to an implementation of a spectral method for finding minimum ratio cuts in some VLSI benchmark circuits.

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