识别双连接组件的高效多核算法

Meher Chaitanya, Kishore Kothapalli
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引用次数: 14

摘要

本文设计并实现了一种求给定图的双连通分量的算法。我们的算法是基于实验证据,即在并行设置中查找图的桥通常更容易和更快。我们利用这个性质首先将图分解为独立的和最大的2边连通子图。为了确定这些2边连接子图中的连接点,我们再次将其转换为在辅助图上寻找桥的问题。有趣的是,在转换过程中,图形的大小可能会增加。然而,我们表明,考虑到在并行设置中更容易找到桥,这种大小和运行时间的小增加被抵消了。我们在运行12个线程的Intel i7 980X CPU上实现了我们的算法。我们表明,我们的算法比在同一平台上实现的最著名的当前算法平均快2.45倍。最后,我们通过应用Cong和Bader在[7].Â中提出的稀疏化技术,将我们的方法扩展到密集图
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Multicore Algorithms For Identifying Biconnected Components
In this paper we design and implement an algorithm for finding the biconnected components of a given graph. Our algorithm is based on experimental evidence that finding the bridges of a graph is usually easier and faster in the parallel setting. We use this property to first decompose the graph into independent and maximal 2-edge-connected subgraphs. To identify the articulation points in these 2-edge connected subgraphs, we again convert this into a problem of finding the bridges on an auxiliary graph. It is interesting to note that during the conversion process, the size of the graph may increase. However, we show that this small increase in size and the run time is offset by the consideration that finding bridges is easier in a parallel setting. We implement our algorithm on an Intel i7 980X CPU running 12 threads. We show that our algorithm is on average 2.45x faster than the best known current algorithms implemented on the same platform. Finally, we extend our approach to dense graphs by applying the sparsification technique suggested by Cong and Bader in [7].Â
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