Parallel Small Vertex Connectivity in Near-Linear Work and Polylogarithmic Depth

Fuente: arXiv
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Main Authors: Jiang, Yonggang, Yun, Changki
Format: Preprint
Published: 2025
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author Jiang, Yonggang
Yun, Changki
author_facet Jiang, Yonggang
Yun, Changki
contents We present a randomized parallel algorithm in the {\sf PRAM} model for $k$-vertex connectivity. Given an undirected simple graph, our algorithm either finds a set of fewer than $k$ vertices whose removal disconnects the graph or reports that no such set exists. The algorithm runs in $O(m \cdot \text{poly}(k, \log n))$ work and $O(\text{poly}(k, \log n))$ depth, which is nearly optimal for any $k = \text{poly}(\log n)$. Prior to our work, algorithms with near-linear work and polylogarithmic depth were known only for $k=3$ [Miller, Ramachandran, STOC'87]; for $k=4$, sequential algorithms achieving near-linear time were known [Forster, Nanongkai, Yang, Saranurak, Yingchareonthawornchai, SODA'20], but no algorithm with near-linear work could achieve even sublinear (on $n$) depth.
format Preprint
id arxiv_https___arxiv_org_abs_2504_06033
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Parallel Small Vertex Connectivity in Near-Linear Work and Polylogarithmic Depth
Jiang, Yonggang
Yun, Changki
Data Structures and Algorithms
We present a randomized parallel algorithm in the {\sf PRAM} model for $k$-vertex connectivity. Given an undirected simple graph, our algorithm either finds a set of fewer than $k$ vertices whose removal disconnects the graph or reports that no such set exists. The algorithm runs in $O(m \cdot \text{poly}(k, \log n))$ work and $O(\text{poly}(k, \log n))$ depth, which is nearly optimal for any $k = \text{poly}(\log n)$. Prior to our work, algorithms with near-linear work and polylogarithmic depth were known only for $k=3$ [Miller, Ramachandran, STOC'87]; for $k=4$, sequential algorithms achieving near-linear time were known [Forster, Nanongkai, Yang, Saranurak, Yingchareonthawornchai, SODA'20], but no algorithm with near-linear work could achieve even sublinear (on $n$) depth.
title Parallel Small Vertex Connectivity in Near-Linear Work and Polylogarithmic Depth
topic Data Structures and Algorithms
url https://arxiv.org/abs/2504.06033