A multilevel algorithm for partitioning graphs
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
SIAM Journal on Scientific Computing
Mesh Partitioning: A Multilevel Balancing and Refinement Algorithm
SIAM Journal on Scientific Computing
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
Partitioning finite element meshes using space-filling curves
Future Generation Computer Systems - Special issue: Parallel computing technologies
Partitioning finite element meshes using space-filling curves
Future Generation Computer Systems - Special issue: Parallel computing technologies
A shape optimizing load distribution heuristic for parallel adaptive FEM computations
PaCT'05 Proceedings of the 8th international conference on Parallel Computing Technologies
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Graph partitioning is an important subproblem in many applications. To solve it efficiently, the multilevel strategy in combination with a matching algorithm and a local refinement heuristic has proven to be a powerful method, and several libraries exist providing such an implementation. Due to the large involvement of heuristics, the evaluation of these libraries is usually based on experiments. In this paper we show that single experiments are usually not sufficient to judge the quality of an algorithm, since even results obtained for graphs of and identical structure show high variations. This is still true, even if the applied algorithms do not contain any nondeterminism. We propose a scheme that considers these variations and therefore makes evaluations and comparisons of different implementations more meaningful. We have applied this technique to evaluate the improvements of the Helpful-Set 2-partitioning implementation and present the obtained results.