pbitMCE:在多核处理器上实现最大团枚举的基于位的方法

N. Dasari, D. Ranjan, M. Zubair
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引用次数: 11

摘要

极大团枚举是图论中的一个基本问题。它在许多网络分析应用和计算生物学中起着至关重要的作用。MCE是一个被广泛研究的问题。最近,Eppstein等人提出了一种最先进的序列算法,该算法使用基于退化的顶点排序来提高效率。在本文中,我们使用一种新的基于位的数据结构,提出了一种新的并行实现Eppstein等人的算法。新的数据结构不仅显著地减小了工作集的大小,而且通过启用位并行性提高了算法的性能。我们说明了退化排序在负载平衡中的重要性,并通过实验评估了调度对算法性能的影响。我们给出了几种类型的合成图和真实世界图的实验结果,这些图有多达5000万个顶点和1亿个边。我们表明,我们的方法比Eppstein等人的方法性能高出4倍,并且在具有32核的多核机器上运行时也可扩展到29倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
pbitMCE: A bit-based approach for maximal clique enumeration on multicore processors
Maximal clique enumeration (MCE) is a fundamental problem in graph theory. It plays a vital role in many network analysis applications and in computational biology. MCE is an extensively studied problem. Recently, Eppstein et al. proposed a state-of-the-art sequential algorithm that uses degeneracy based ordering of vertices to improve the efficiency. In this paper, we propose a new parallel implementation of the algorithm of Eppstein et al. using a new bit-based data structure. The new data structure not only reduces the working set size significantly but also by enabling the use of bit-parallelism improves the performance of the algorithm. We illustrate the significance of degeneracy ordering in load balancing and experimentally evaluate the impact of scheduling on the performance of the algorithm. We present experimental results on several types of synthetic and real-world graphs with up to 50 million vertices and 100 million edges. We show that our approach outperforms Eppstein et al.'s approach by up to 4 times and also scales up to 29 times when run on a multicore machine with 32 cores.
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