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We use exponential start time clustering to design faster and more work-efficient parallel graph algorithms involving distances. Previous algorithms usually rely on graph decomposition routines with strict restrictions on the diameters of…

Data Structures and Algorithms · Computer Science 2015-06-25 Gary L. Miller , Richard Peng , Adrian Vladu , Shen Chen Xu

We present the first work-optimal polylogarithmic-depth parallel algorithm for the minimum cut problem on non-sparse graphs. For $m\geq n^{1+\epsilon}$ for any constant $\epsilon>0$, our algorithm requires $O(m \log n)$ work and $O(\log^3…

Data Structures and Algorithms · Computer Science 2021-02-19 Andrés López-Martínez , Sagnik Mukhopadhyay , Danupon Nanongkai

Semisort is a fundamental algorithmic primitive widely used in the design and analysis of efficient parallel algorithms. It takes input as an array of records and a function extracting a \emph{key} per record, and reorders them so that…

Data Structures and Algorithms · Computer Science 2023-04-21 Xiaojun Dong , Yunshu Wu , Zhongqi Wang , Laxman Dhulipala , Yan Gu , Yihan Sun

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…

Data Structures and Algorithms · Computer Science 2017-11-07 Jeremy T. Fineman

We present a randomized $O(m \log^2 n)$ work, $O(\text{polylog } n)$ depth parallel algorithm for minimum cut. This algorithm matches the work bounds of a recent sequential algorithm by Gawrychowski, Mozes, and Weimann [ICALP'20], and…

Data Structures and Algorithms · Computer Science 2021-12-30 Daniel Anderson , Guy E. Blelloch

We develop the first parallel graph coloring heuristics with strong theoretical guarantees on work and depth and coloring quality. The key idea is to design a relaxation of the vertex degeneracy order, a well-known graph theory concept, and…

Data Structures and Algorithms · Computer Science 2020-11-12 Maciej Besta , Armon Carigiet , Zur Vonarburg-Shmaria , Kacper Janda , Lukas Gianinazzi , Torsten Hoefler

Several classic problems in graph processing and computational geometry are solved via incremental algorithms, which split computation into a series of small tasks acting on shared state, which gets updated progressively. While the…

Data Structures and Algorithms · Computer Science 2020-03-24 Dan Alistarh , Nikita Koval , Giorgi Nadiradze

We describe approximation algorithms in Linial's classic LOCAL model of distributed computing to find maximum-weight matchings in a hypergraph of rank $r$. Our main result is a deterministic algorithm to generate a matching which is an…

Data Structures and Algorithms · Computer Science 2023-10-13 David G. Harris

A \emph{metric tree embedding} of expected \emph{stretch~$\alpha \geq 1$} maps a weighted $n$-node graph $G = (V, E, \omega)$ to a weighted tree $T = (V_T, E_T, \omega_T)$ with $V \subseteq V_T$ such that, for all $v,w \in V$,…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-08-25 Stephan Friedrichs , Christoph Lenzen

We present the first near-linear work and poly-logarithmic depth algorithm for computing a minimum cut in a graph, while previous parallel algorithms with poly-logarithmic depth required at least quadratic work in the number of vertices. In…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-03 Barbara Geissmann , Lukas Gianinazzi

We investigate distributed memory parallel sorting algorithms that scale to the largest available machines and are robust with respect to input size and distribution of the input elements. The main outcome is that four sorting algorithms…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-17 Michael Axtmann , Peter Sanders

For $n$-vertex $m$-edge graphs with integer polynomially-bounded costs and capacities, we provide a randomized parallel algorithm for the minimum cost flow problem with $\tilde O(m+n^ {1.5})$ work and $\tilde O(\sqrt{n})$ depth. On…

Data Structures and Algorithms · Computer Science 2025-03-18 Jan van den Brand , Hossein Gholizadeh , Yonggang Jiang , Tijn de Vos

We present a simple randomized algorithm that can efficiently maintain a $(\Delta+1)$ coloring as the graph undergoes edge insertion and deletion updates, where $\Delta$ denotes an upper bound on the maximum degree. A key advantage is the…

Data Structures and Algorithms · Computer Science 2025-12-11 Mohsen Ghaffari , Jaehyun Koo

In this paper we provide a parallel algorithm that given any $n$-node $m$-edge directed graph and source vertex $s$ computes all vertices reachable from $s$ with $\tilde{O}(m)$ work and $n^{1/2 + o(1)}$ depth with high probability in $n$ .…

Data Structures and Algorithms · Computer Science 2019-12-09 Arun Jambulapati , Yang P. Liu , Aaron Sidford

We present a space and time efficient practical parallel algorithm for approximating the diameter of massive weighted undirected graphs on distributed platforms supporting a MapReduce-like abstraction. The core of the algorithm is a…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-10 Matteo Ceccarello , Andrea Pietracaprina , Geppino Pucci , Eli Upfal

We present a parallel algorithm for the $(1-\epsilon)$-approximate maximum flow problem in capacitated, undirected graphs with $n$ vertices and $m$ edges, achieving $O(\epsilon^{-3}\text{polylog} n)$ depth and $O(m \epsilon^{-3}…

Data Structures and Algorithms · Computer Science 2024-02-26 Arpit Agarwal , Sanjeev Khanna , Huan Li , Prathamesh Patil , Chen Wang , Nathan White , Peilin Zhong

This paper presents new deterministic and distributed low-diameter decomposition algorithms for weighted graphs. In particular, we show that if one can efficiently compute approximate distances in a parallel or a distributed setting, one…

Data Structures and Algorithms · Computer Science 2022-09-07 Václav Rozhoň , Michael Elkin , Christoph Grunau , Bernhard Haeupler

A low out-degree orientation directs each edge of an undirected graph with the goal of minimizing the maximum out-degree of a vertex. In the parallel batch-dynamic setting, one can insert or delete batches of edges, and the goal is to…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-23 Guy Blelloch , Andrew Brady , Laxman Dhulipala , Jeremy Fineman , Kishen Gowda , Chase Hutton

We study the classical scheduling problem on parallel machines %with precedence constraints where the precedence graph has the bounded depth $h$. Our goal is to minimize the maximum completion time. We focus on developing approximation…

Data Structures and Algorithms · Computer Science 2023-02-02 Bin Fu , Yumei Huo , Hairong Zhao

Existing parallel algorithms for wavelet tree construction have a work complexity of $O(n\log\sigma)$. This paper presents parallel algorithms for the problem with improved work complexity. Our first algorithm is based on parallel integer…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-17 Julian Shun
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