An Experimental Study of External Memory Algorithms for Connected Components

G. Brodal, Rolf Fagerberg, David Hammer, U. Meyer, M. Penschuck, Hung Tran
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引用次数: 2

Abstract

We empirically investigate algorithms for solving Connected Components in the external memory model. In particular, we study whether the randomized O(Sort(E)) algorithm by Karger, Klein, and Tarjan can be implemented to compete with practically promising and simpler algorithms having only slightly worse theoretical cost, namely Borůvka’s algorithm and the algorithm by Sibeyn and collaborators. For all algorithms, we develop and test a number of tuning options. Our experiments are executed on a large set of different graph classes including random graphs, grids, geometric graphs, and hyperbolic graphs. Among our findings are: The Sibeyn algorithm is a very strong contender due to its simplicity and due to an added degree of freedom in its internal workings when used in the Connected Components setting. With the right tunings, the Karger-Klein-Tarjan algorithm can be implemented to be competitive in many cases. Higher graph density seems to benefit Karger-Klein-Tarjan relative to Sibeyn. Borůvka’s algorithm is not competitive with the two others. 2012 ACM Subject Classification Mathematics of computing → Paths and connectivity problems; Theory of computation → Graph algorithms analysis
连接元件外部存储算法的实验研究
我们实证研究了解决外部存储器模型中连接组件的算法。我们特别研究了Karger, Klein和Tarjan的随机化O(Sort(E))算法是否可以实现,以与理论成本稍差的具有实际前景和更简单的算法,即Borůvka的算法和Sibeyn及其合作者的算法竞争。对于所有算法,我们开发和测试了许多调优选项。我们的实验是在大量不同的图类上进行的,包括随机图、网格图、几何图和双曲图。我们的发现包括:Sibeyn算法是一个非常强大的竞争者,因为它的简单性,并且在连接组件设置中使用时,它的内部工作增加了自由度。通过适当的调整,kager - klein - tarjan算法可以在许多情况下具有竞争力。相对于Sibeyn,更高的图形密度似乎对kager - klein - tarjan有利。Borůvka的算法与其他两种算法没有竞争关系。2012 ACM学科分类计算数学→路径和连通性问题;计算理论→图算法分析
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