Nearly Work-Efficient Parallel Algorithm for Digraph Reachability

TL;DR

This paper introduces the first nearly work-efficient parallel algorithm for digraph reachability that operates with sublinear span, significantly advancing parallel graph algorithms for sparse high-diameter graphs.

Contribution

It presents a novel randomized parallel algorithm with nearly linear work and sublinear span for digraph reachability, extending to related problems.

Findings

Expected work is  O(m) for the algorithm.

Span is  O(n^{2/3}), enabling parallelism  n^{1/3}.

The diameter reduction algorithm is simple and runs in  O(m) time.

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 $\tilde{O}(m)$ and span $\tilde{O}(n^{2/3})$, and hence parallelism $\tilde{\Omega}(n^{1/3})$, on any graph with $n$ vertices and $m$ arcs. This is the first parallel algorithm having both nearly linear work and strongly sublinear span. 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 of a strongly connected graph, all with similar work and span. The main technical contribution is an \emph{efficient} Monte Carlo algorithm that, through the addition of $\tilde{O}(n)$ shortcuts, reduces the diameter of the graph to $\tilde{O}(n^{2/3})$ with high probability. While both sequential and parallel algorithms are known with those combinatorial properties, even the sequential algorithms are not efficient. This paper presents a surprisingly simple sequential algorithm that achieves the stated diameter reduction and runs in $\tilde{O}(m)$ time. Parallelizing that algorithm yields the main result, but doing so involves overcoming several other challenges.