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Related papers: Improved Parallel Algorithms for Spanners and Hops…

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Sparse, irregular graphs show up in various applications like linear algebra, machine learning, engineering simulations, robotic control, etc. These graphs have a high degree of parallelism, but their execution on parallel threads of modern…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-02-17 Nimish Shah , Wannes Meert , Marian Verhelst

This paper presents new parallel algorithms for generating Euclidean minimum spanning trees and spatial clustering hierarchies (known as HDBSCAN$^*$). Our approach is based on generating a well-separated pair decomposition followed by using…

Data Structures and Algorithms · Computer Science 2021-04-05 Yiqiu Wang , Shangdi Yu , Yan Gu , Julian Shun

We develop an efficient parallel algorithm for answering shortest-path queries in planar graphs and implement it on a multi-node CPU/GPU clusters. The algorithm uses a divide-and-conquer approach for decomposing the input graph into small…

Data Structures and Algorithms · Computer Science 2015-03-26 Guillaume Chapuis , Hristo Djidjev

A $(\beta,\epsilon)$-hopset for a weighted undirected $n$-vertex graph $G=(V,E)$ is a set of edges, whose addition to the graph guarantees that every pair of vertices has a path between them that contains at most $\beta$ edges, whose length…

Data Structures and Algorithms · Computer Science 2016-05-17 Michael Elkin , Ofer Neiman

Graph clustering has many important applications in computing, but due to growing sizes of graphs, even traditionally fast clustering methods such as spectral partitioning can be computationally expensive for real-world graphs of interest.…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-11 Julian Shun , Farbod Roosta-Khorasani , Kimon Fountoulakis , Michael W. Mahoney

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

We show an improved parallel algorithm for decomposing an undirected unweighted graph into small diameter pieces with a small fraction of the edges in between. These decompositions form critical subroutines in a number of graph algorithms.…

Data Structures and Algorithms · Computer Science 2013-07-16 Gary L. Miller , Richard Peng , Shen Chen Xu

A spanner of a graph is a subgraph that preserves lengths of shortest paths up to a multiplicative distortion. For every $k$, a spanner with size $O(n^{1+1/k})$ and stretch $(2k+1)$ can be constructed by a simple centralized greedy…

Data Structures and Algorithms · Computer Science 2023-07-10 Rubi Arviv , Lily Chung , Reut Levi , Edward Pyne

Let $G = (V,E,w)$ be a weighted undirected graph on $|V| = n$ vertices and $|E| = m$ edges, let $k \ge 1$ be any integer, and let $\epsilon < 1$ be any parameter. We present the following results on fast constructions of spanners with…

Data Structures and Algorithms · Computer Science 2021-08-03 Hung Le , Shay Solomon

This paper presents efficient distributed algorithms for a number of fundamental problems in the area of graph sparsification: We provide the first deterministic distributed algorithm that computes an ultra-sparse spanner in…

Data Structures and Algorithms · Computer Science 2022-09-26 Marcel Bezdrighin , Michael Elkin , Mohsen Ghaffari , Christoph Grunau , Bernhard Haeupler , Saeed Ilchi , Václav Rozhoň

Preferential attachment lies at the heart of many network models aiming to replicate features of real world networks. To simulate the attachment process, conduct statistical tests, or obtain input data for benchmarks, efficient algorithms…

Data Structures and Algorithms · Computer Science 2023-01-18 Daniel Allendorf , Ulrich Meyer , Manuel Penschuck , Hung Tran

Random walks are a fundamental primitive used in many machine learning algorithms with several applications in clustering and semi-supervised learning. Despite their relevance, the first efficient parallel algorithm to compute random walks…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-12-02 Michael Kapralov , Silvio Lattanzi , Navid Nouri , Jakab Tardos

This paper presents near-optimal deterministic parallel and distributed algorithms for computing $(1+\varepsilon)$-approximate single-source shortest paths in any undirected weighted graph. On a high level, we deterministically reduce this…

Data Structures and Algorithms · Computer Science 2022-09-26 Václav Rozhoň , Christoph Grunau , Bernhard Haeupler , Goran Zuzic , Jason Li

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 give the first Congested Clique algorithm that computes a sparse hopset with polylogarithmic hopbound in polylogarithmic time. Given a graph $G=(V,E)$, a $(\beta,\epsilon)$-hopset $H$ with "hopbound" $\beta$, is a set of edges added to…

Data Structures and Algorithms · Computer Science 2020-01-22 Yasamin Nazari

We present a new parallel algorithm for $k$-clique counting/listing that has polylogarithmic span (parallel time) and is work-efficient (matches the work of the best sequential algorithm) for sparse graphs. Our algorithm is based on…

Data Structures and Algorithms · Computer Science 2021-07-19 Jessica Shi , Laxman Dhulipala , Julian Shun

For a positive parameter $\beta$, the $\beta$-bounded distance between a pair of vertices $u,v$ in a weighted undirected graph $G = (V,E,\omega)$ is the length of the shortest $u-v$ path in $G$ with at most $\beta$ edges, aka {\em hops}.…

Data Structures and Algorithms · Computer Science 2017-04-28 Michael Elkin , Ofer Neiman

We consider the problem of testing graph cluster structure: given access to a graph $G=(V, E)$, can we quickly determine whether the graph can be partitioned into a few clusters with good inner conductance, or is far from any such graph?…

Data Structures and Algorithms · Computer Science 2018-09-19 Ashish Chiplunkar , Michael Kapralov , Sanjeev Khanna , Aida Mousavifar , Yuval Peres

Most of the literature on spanners focuses on building the graph from scratch. This paper instead focuses on adding edges to improve an existing graph. A major open problem in this field is: given a graph embedded in a metric space, and a…

Computational Geometry · Computer Science 2022-12-20 Joachim Gudmundsson , Sampson Wong

We present a simple greedy procedure to compute an $(\alpha,\beta)$-spanner for a graph $G$. We then show that this procedure is useful for building fault-tolerant spanners, as well as spanners for weighted graphs. Our first main result is…

Data Structures and Algorithms · Computer Science 2026-03-19 Elizaveta Popova , Elad Tzalik