Work

Simple parallel and distributed algorithms for spectral graph sparsification

Year: 2014

Type: preprint

Abstract: We describe a simple algorithm for spectral graph sparsification, based on iterative computations of weighted spanners and uniform sampling. Leveraging the algorithms of Baswana and Sen for computing spanners, we obtain the first distributed spectral sparsification algorithm. We also obtain a parallel algorithm with improved work and time guarantees. Combining this algorithm with the parallel framework of Peng and Spielman for solving symmetric diagonally dominant linear systems, we get a parallel solver which is much closer to being practical and significantly more efficient in terms of the total work.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1402.3851

Author: Koutis, Ioannis

Institution: University of Puerto Rico at Río Piedras

Language: English

Topic: Complexity and Algorithms in Graphs

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: National Science Foundation

Awards: G6671297155, CAREER: Fast algorithms via a spectral theory for graphs with a prescribed cut structure

OpenAlex ID: W2951869612

Cites: 12

Cited by:

Related to: 20