Parallel Exact Shortest Paths in Almost Linear Work and Square Root Depth
Nairen Cao, Jeremy T. Fineman
摘要
This paper presents a randomized parallel single-source shortest paths (SSSP) algorithm for directed graphs with non-negative integer edge weights that solves the problem exactly in Õ(m) work and n 1/2+o(1) span, with high probability. All previous exact SSSP algorithms with nearly linear work have linear span, even for undirected unweighted graphs. Our main technical contribution is to show a reduction from the exact SSSP to directed hopsets [6] using the iterative gradual rounding technique [9]. An (h, ϵ)-hopset is a set of weighted edges (sometimes called shortcuts) that when added to the graph admit h-hop paths with weights no more than (1 + ϵ) times the true shortest path distances.
Furthermore, we show how to combine this algorithm with Forster and Nanongkai's framework [15] to improve the distributed exact SSSP algorithm. Specifically, we obtain an Õ( √ n + D + n 2/5+o(1) D 2/5 )-round algorithm in the CONGEST model for exact SSSP in directed graphs with non-negative integer edge weights, where D is the unweighted diameter of the underlying undirected graph.
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引用它的顶会 Paper2
- DAG Projections: Reducing Distance and Flow Problems to DAGsBernhard Haeupler, Yonggang Jiang, Thatchaphol SaranurakSTOC 2026 · 被引用 2 次
- Strongly Polynomial Parallel Work-Depth Tradeoffs for Directed SSSPAdam Karczmarz, Wojciech Nadara, Marek SokolowskiSODA 2026
它引用的顶会 Paper4
- Parallel approximate undirected shortest paths via low hop emulatorsAlexandr Andoni, Clifford Stein, Peilin ZhongSTOC 2020 · 被引用 50 次
- Faster parallel algorithm for approximate shortest pathJason LiSTOC 2020 · 被引用 48 次
- Efficient construction of directed hopsets and parallel approximate shortest pathsNairen Cao, Jeremy T. Fineman, Katina RussellSTOC 2020 · 被引用 13 次
- Parallel Breadth-First Search and Exact Shortest Paths and Stronger Notions for Approximate DistancesVáclav Rozhon, Bernhard Haeupler, Anders Martinsson, Christoph Grunau 等STOC 2023 · 被引用 6 次
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