Engineering Multilevel Graph Partitioning Algorithms
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by
Peter Sanders, Christian Schulz
2010
Abstract
We present a multi-level graph partitioning algorithm using novel local
improvement algorithms and global search strategies transferred from the
multi-grid community. Local improvement algorithms are based max-flow min-cut
computations and more localized FM searches. By combining these techniques, we
obtain an algorithm that is fast on the one hand and on the other hand is able
to improve the best known partitioning results for many inputs. For example, in
Walshaw's well known benchmark tables we achieve 317 improvements for the
tables 1%, 3% and 5% imbalance. Moreover, in 118 additional cases we have been
able to reproduce the best cut in this benchmark.
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