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arXiv · 1807.09417

Shared-Memory Parallel Maximal Clique Enumeration

Apurba Das·Seyed-Vahid Sanei-Mehri·Srikanta Tirthapura
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Abstract

We present shared-memory parallel methods for Maximal Clique Enumeration (MCE) from a graph. MCE is a fundamental and well-studied graph analytics task, and is a widely used primitive for identifying dense structures in a graph. Due to its computationally intensive nature, parallel methods are imperative for dealing with large graphs. However, surprisingly, there do not yet exist scalable and parallel methods for MCE on a shared-memory parallel machine. In this work, we present efficient shared-memory parallel algorithms for MCE, with the following properties: (1) the parallel algorithms are provably work-efficient relative to a state-of-the-art sequential algorithm (2) the algorithms have a provably small parallel depth, showing that they can scale to a large number of processors, and (3) our implementations on a multicore machine shows a good speedup and scaling behavior with increasing number of cores, and are substantially faster than prior shared-memory parallel algorithms for MCE.

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Apurba Das, Seyed-Vahid Sanei-Mehri, Srikanta Tirthapura. 2018-07-25. Shared-Memory Parallel Maximal Clique Enumeration. https://arxiv.org/abs/1807.09417

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