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SIAM Review
Article . 1999 . Peer-reviewed
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Parallel Multilevel series k-Way Partitioning Scheme for Irregular Graphs

Parallel multilevel series k-way partitioning scheme for irregular graphs
Authors: Karypis, George; Kumar, Vipin;

Parallel Multilevel series k-Way Partitioning Scheme for Irregular Graphs

Abstract

Summary: In this paper we present a parallel formulation of a multilevel \(k\)-way graph partitioning algorithm. A key feature of this parallel formulation is that it is able to achieve a high degree of concurrency while maintaining the high quality of the partitions produced by the serial multilevel \(k\)-way partitioning algorithm. In particular, the time taken by our parallel graph partitioning algorithm is only slightly longer than the time taken for re-arrangement of the graph among processors according to the new partition. Experiments with a variety of finite element graphs show that our parallel formulation produces high-quality partitionings in a short amount of time. For example, a 128-way partitioning of graphs with one million vertices can be computed in a little over two seconds on a 128-processor Cray T3D. Furthermore, the quality of the partitions produced is comparable (edge-cuts within 5\%) to those produced by the serial multilevel \(k\)-way algorithm. Thus our parallel algorithm makes it feasible to perform frequent repartitioning of graphs in dynamic computations without compromising the partitioning quality.

Keywords

parallel sparse matrix algorithms, Iterative numerical methods for linear systems, Computational methods for sparse matrices, Graph theory (including graph drawing) in computer science, Kernighan--Lin heuristic, parallel graph partitioning, Parallel numerical computation, multilevel partitioning methods, spectral partitioning methods

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
232
Top 1%
Top 1%
Top 10%
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