Abstract
Sequential multi-constraint graph partitioners have been developed to address the load balancing requirements of multi-phase simulations. The efficient execution of large multi-phase simulations on high performance parallel computers requires that the multi-constraint partitionings are computed in parallel. This paper presents a parallel formulation of a recently developed multi-constraint graph partitioning algorithm. We describe this algorithm and give experimental results conducted on a 128-processor Cray T3E. We show that our parallel algorithm is able to efficiently compute partitionings of similar edge-cuts as serial multi-constraint algorithms, and can scale to very large graphs. Our parallel multi-constraint graph partitioner is able to compute a threeconstraint 128-way partitioning of a 7.5million node graph in about 7 seconds on 128 processors of a Cray T3E.
Cite
CITATION STYLE
Schloegel, K., Karypis, G., & Kumar, V. (2000). Parallel multilevel algorithms for multi-constraint graph partitioning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1900, pp. 296–310). Springer Verlag. https://doi.org/10.1007/3-540-44520-x_39
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