Parallel peeling algorithms

Jiayang Jiang, M. Mitzenmacher, J. Thaler
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引用次数: 35

Abstract

The analysis of several algorithms and data structures can be framed as a peeling process on a random hypergraph: vertices with degree less than k are removed until there are no vertices of degree less than k left. The remaining hypergraph is known as the k-core. In this paper, we analyze parallel peeling processes, where in each round, all vertices of degree less than k are removed. It is known that, below a specific edge density threshold, the k-core is empty with high probability. We show that, with high probability, below this threshold, only 1⁄log((k-1)(r-1)) log logn+O(1) rounds of peeling are needed to obtain the empty k-core for r-uniform hypergraphs. Interestingly, we show that above this threshold, Ω(log n) rounds of peeling are required to find the non-empty k-core. Since most algorithms and data structures aim to peel to an empty k-core, this asymmetry appears fortunate. We verify the theoretical results both with simulation and with a parallel implementation using graphics processing units (GPUs). Our implementation provides insights into how to structure parallel peeling algorithms for efficiency in practice.
并行剥离算法
对几种算法和数据结构的分析可以看作是一个随机超图上的剥离过程:去除度数小于k的顶点,直到没有度数小于k的顶点。剩下的超图被称为k核。在本文中,我们分析了并行剥离过程,其中在每一轮中,去除所有度小于k的顶点。已知,在特定边缘密度阈值以下,k核大概率为空。我们证明,在这个阈值以下,很有可能只需要1⁄log((k-1)(r-1)) log logn+O(1)轮剥离就可以获得r-均匀超图的空k核。有趣的是,我们发现在这个阈值以上,需要Ω(log n)轮剥离才能找到非空的k核。由于大多数算法和数据结构的目标是剥离到一个空的k核,这种不对称似乎是幸运的。我们通过仿真和图形处理单元(gpu)的并行实现验证了理论结果。我们的实现提供了如何在实践中构建并行剥离算法以提高效率的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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