Projects / KaHIP

KaHIP

KaHIP - Karlsruhe High Quality Partitioning - is a family of graph partitioning programs that tackle the balanced graph partitioning problem. It focuses on solution quality and implements flow-based methods, more-localized local searches, and several parallel and sequential meta-heuristics.

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  •  03 Mar 2014 22:58

    Release Notes: This release adds huge max-flow min-cut instances, created with the partitioning framework and containing up to 2.6 billion edges. The max-flow min-cut instances stem from the local search algorithms within KaFFPa that are used to improve a bipartition of the graph.

    •  19 Feb 2014 23:34

    Release Notes: This version integrates the size-constrained label propagation clustering algorithm as a standalone program.

    •  14 Feb 2014 00:34

    Release Notes: This is a major update improving partitioning speed and solution quality on social networks and Web graphs. It achieves this by integrating novel coarsening schemes that can also be used as simple local search algorithms. For example, this version can partition a Web graph with half a billion edges in roughly one minute while cutting far fewer edges than Metis.

    •  21 Dec 2013 14:14

      Release Notes: This is the initial release.

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