IEEE Transactions on Parallel and Distributed Systems

IEEE Transactions on Parallel and Distributed Systems (TPDS) is a scholarly archival journal published monthly. Parallelism and distributed computing are foundational research and technology to rapidly advance computer systems and their applications. Read the full scope of TPDS

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From the September 2017 Issue

Parallel Graph Partitioning for Complex Networks

By Henning Meyerhenke, Peter Sanders, and Christian Schulz

Free Featured ArticleProcessing large complex networks like social networks or web graphs has attracted considerable interest. To do this in parallel, we need to partition them into pieces of roughly equal size. Unfortunately, previous parallel graph partitioners originally developed for more regular mesh-like networks do not work well for complex networks. Here we address this problem by parallelizing and adapting the label propagation technique originally developed for graph clustering. By introducing size constraints, label propagation becomes applicable for both the coarsening and the refinement phase of multilevel graph partitioning. This way we exploit the hierarchical cluster structure present in many complex networks. We obtain very high quality by applying a highly parallel evolutionary algorithm to the coarsest graph. The resulting system is both more scalable and achieves higher quality than state-of-the-art systems like ParMetis or PT-Scotch. For large complex networks the performance differences are very big. As an example, our algorithm partitions a web graph with 3.3 G edges in 16 seconds using 512 cores of a high-performance cluster while producing a high quality partition—none of the competing systems can handle this graph on our system.

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