面向2连通部件全动态维护的共享内存并行算法

Chirayu Anant Haryan, G. Ramakrishna, Kishore Kothapalli, D. Banerjee
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引用次数: 4

摘要

查找图的双连通分量在许多其他图问题中有大量应用,包括平面性测试、计算中心性度量、查找(加权)顶点覆盖、着色等。近年来,人们设计了跨顺序和并行计算模型的高效算法来解决这个问题。然而,当前的算法不能在底层图通过插入或删除边以动态方式随时间变化的情况下工作。在顺序设置中,在插入或删除单个边时获得图的双连接分量的动态算法在二十多年前就已为人所知。对于这一问题的并行算法研究并不多。在本文中,我们设计了共享内存并行算法,该算法在插入或删除一批边后获得图的双连通分量。因此,我们的算法将能够利用由于一批更新而引入的并行性。我们在128核的AMD EPYC 7742 CPU上实现我们的算法。我们对来自多个类别的10个真实世界图形的实验表明,我们的算法优于并行的最先进的静态算法。本文的实现和扩展版本见[5]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Shared-Memory Parallel Algorithms for Fully Dynamic Maintenance of 2-Connected Components
Finding the biconnected components of a graph has a large number of applications in many other graph problems including planarity testing, computing the centrality metrics, finding the (weighted) vertex cover, coloring, and the like. Recent years saw the design of efficient algorithms for this problem across sequential and parallel computational models. However, current algorithms do not work in the setting where the underlying graph changes over time in a dynamic manner via the insertion or deletion of edges. Dynamic algorithms in the sequential setting that obtain the biconnected components of a graph upon insertion or deletion of a single edge are known from over two decades ago. Parallel algorithms for this problem are not heavily studied. In this paper, we design shared-memory parallel algorithms that obtain the biconnected components of a graph subsequent to the insertion or deletion of a batch of edges. Our algorithms hence will be capable of exploiting the parallelism adduced due to a batch of updates. We implement our algorithms on an AMD EPYC 7742 CPU having 128 cores. Our experiments on a collection of 10 real-world graphs from multiple classes indicate that our algorithms outperform parallel state-of-the-art static algorithms.11The implementation and an extended version of this paper is at [5].
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