Nearly work-efficient parallel algorithm for digraph reachability

Jeremy T. Fineman
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引用次数: 28

Abstract

One of the simplest problems on directed graphs is that of identifying the set of vertices reachable from a designated source vertex. This problem can be solved easily sequentially by performing a graph search, but efficient parallel algorithms have eluded researchers for decades. For sparse high-diameter graphs in particular, there is no known work-efficient parallel algorithm with nontrivial parallelism. This amounts to one of the most fundamental open questions in parallel graph algorithms: Is there a parallel algorithm for digraph reachability with nearly linear work? This paper shows that the answer is yes. This paper presents a randomized parallel algorithm for digraph reachability and related problems with expected work Õ(m) and span Õ(n2/3), and hence parallelism Ω(m/n2/3) = Ω(n1/3), on any graph with n vertices and m arcs. This is the first parallel algorithm having both nearly linear work and strongly sublinear span, i.e., span Õ(n1−є) for any constant є>0. The algorithm can be extended to produce a directed spanning tree, determine whether the graph is acyclic, topologically sort the strongly connected components of the graph, or produce a directed ear decomposition, all with work Õ(m) and span Õ(n2/3). The main technical contribution is an efficient Monte Carlo algorithm that, through the addition of Õ(n) shortcuts, reduces the diameter of the graph to Õ(n2/3) with high probability. While both sequential and parallel algorithms are known with those combinatorial properties, even the sequential algorithms are not efficient, having sequential runtime Ω(mnΩ(1)). This paper presents a surprisingly simple sequential algorithm that achieves the stated diameter reduction and runs in Õ(m) time. Parallelizing that algorithm yields the main result, but doing so involves overcoming several other challenges.
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有向图可达性的近乎高效并行算法
有向图中最简单的问题之一是确定从指定的源顶点可到达的顶点集。这个问题可以通过执行图搜索轻松地顺序解决,但有效的并行算法已经困扰了研究人员几十年。特别是对于稀疏的大直径图,没有已知的具有非平凡并行性的高效并行算法。这相当于并行图算法中最基本的开放问题之一:是否存在近似线性工作的有向图可达性并行算法?本文表明,答案是肯定的。本文提出了一种随机并行算法,用于求解有向图可达性和相关问题,其期望功Õ(m)和跨度Õ(n2/3),因此并行度Ω(m/n2/3) = Ω(n1/3),适用于任何有n个顶点和m条弧的图。这是第一个同时具有近线性工作和强次线性张成空间的并行算法,即对于任何常数n >0,张成空间Õ(n1−n)。该算法可以扩展为生成有向生成树,确定图是否为无环,对图的强连接分量进行拓扑排序,或生成有向耳分解,所有这些都具有功Õ(m)和跨度Õ(n2/3)。主要的技术贡献是一种高效的蒙特卡罗算法,通过添加Õ(n)捷径,高概率地将图的直径减小到Õ(n2/3)。虽然顺序算法和并行算法都具有这些组合属性,但即使是顺序算法也不高效,因为它们具有顺序运行时Ω(mnΩ(1))。本文提出了一个非常简单的顺序算法,实现了规定的直径缩小,运行时间为Õ(m)。并行化该算法会产生主要结果,但这样做需要克服其他几个挑战。
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