A multilevel algorithm for partitioning graphs
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Partitioning strategies for structured multiblock grids
Parallel Computing - Special issue on graph partioning and parallel computing
Parallel multilevel k-way partitioning scheme for irregular graphs
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
Comparison of Partitioning Strategies for PDE Solvers on Multiblock Grids
PARA '98 Proceedings of the 4th International Workshop on Applied Parallel Computing, Large Scale Scientific and Industrial Problems
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
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A local refinement method for data partitioning has been constructed. The method balances the workload and minimizes locally the number of edge-cuts. The arithmetic complexity of the algorithm is low. The method is well suited for refinement in multilevel partitioning where the intermediate partitions are near optimal but slightly unbalanced. It is also useful for improvement of global partitioning methods and repartitioning in dynamic problems where the workload changes slightly. The algorithm has been compared with corresponding methods in Chaco and Metis in the context of multilevel partitioning. The cost of carrying out the partitioning with our method is lower than in Chaco and of the same order as in Metis, and still the quality of the partitioning is comparable and in some cases even better.