We describe an approach to parallel graph partitioning that scales to hundreds of processors and produces a high solution quality. For example, for many instances from Walshaw's benchmark collection we improve the best known partitioning. We use the well known framework of multi-level graph partitioning. All components are implemented by scalable parallel algorithms. Quality improvements compared to previous systems are due to better prioritization of edges to be contracted, better approximation algorithms for identifying matchings, better local search heuristics, and perhaps most notably, a parallelization of the FM local search algorithm that works more locally than previous approaches.
KaPPa REF is a "classical" matching based multi-level graph partitioning algorithm designed for scalable parallel execution.
Engineering a scalable high quality graph partitioner
2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS)
2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS)
Computer Science