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KaHIP v3.00 -- Karlsruhe High Quality Partitioning -- User Guide

This paper severs as a user guide to the graph partitioning framework KaHIP (Karlsruhe High Quality Partitioning). We give a rough overview of the techniques used within the framework and describe the user interface as well as the file formats used. Moreover, we provide a short description of the current library functions provided within the framework. Since version 3.00 we support multilevel partitioning, memetic algorithms, distributed and shared-memory parallel algorithms, node separator and ordering algorithms, edge partitioning algorithms as well as ILP solvers.

preprint2020arXivOpen access
Peter SandersChristian Schulz
Data Structures and AlgorithmsDistributed, Parallel, and Cluster Computing
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Peter SandersChristian Schulz

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