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Parallel Subgraph Isomorphism on Multi-core Architectures: A Comparison of Four Strategies Based on Tree Search

机译:基于树搜索的四种策略的平行子图同样:三种策略的比较

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Subgraph isomorphism is one of the most challenging problems on graph-based representations. Despite many efficient sequential algorithms have been proposed over the last decades, solving this problem on large graphs is still a time demanding task. For this reason, there is a recently growing interest in realizing effective parallel algorithms able to exploit at their best the modern multi-core architectures commonly available on servers and workstations. We propose a comparison of four parallel algorithms derived from the state-of-the-art sequential algorithm VF3-Light; two of them were presented in previous works, while the other two are introduced in this paper. In order to evaluate strong points and weaknesses of each algorithm, we performed a benchmark over six datasets of random large and dense graphs, both labelled and unlabelled, measuring memory usage, speed-up and efficiency. We also add a comparison with a different parallel algorithm, named Glasgow, that is not derived from VF3-Light.
机译:子图同构是基于图形的表示中最具挑战性的问题之一。尽管在过去的几十年中已经提出了许多有效的顺序算法,但在大图上解决了这个问题仍然是一个苛刻的任务。因此,在实现能够在服务器和工作站上常用的最佳现代多核架构中实现有效的并行算法,最近越来越多的平行算法。我们提出了从最先进的顺序算法Vf3-Light导出的四个并行算法的比较;其中两个是在以前的作品中呈现的,而另外两个是本文介绍的。为了评估每种算法的强点和弱点,我们在随机大而密集图的六个数据集中进行了基准,包括标记和未标记,测量内存使用,加速和效率。我们还添加了与不同的并行算法的比较,该算法名为Glasgow,这不是vf3光源的。

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