Title
Parallelism in Randomized Incremental Algorithms
Abstract
AbstractIn this article, we show that many sequential randomized incremental algorithms are in fact parallel. We consider algorithms for several problems, including Delaunay triangulation, linear programming, closest pair, smallest enclosing disk, least-element lists, and strongly connected components.We analyze the dependencies between iterations in an algorithm and show that the dependence structure is shallow with high probability or that, by violating some dependencies, the structure is shallow and the work is not increased significantly. We identify three types of algorithms based on their dependencies and present a framework for analyzing each type. Using the framework gives work-efficient polylogarithmic-depth parallel algorithms for most of the problems that we study.This article shows the first incremental Delaunay triangulation algorithm with optimal work and polylogarithmic depth. This result is important, since most implementations of parallel Delaunay triangulation use the incremental approach. Our results also improve bounds on strongly connected components and least-element lists and significantly simplify parallel algorithms for several problems.
Year
DOI
Venue
2020
10.1145/3402819
Journal of the ACM
Keywords
DocType
Volume
Randomized incremental algorithms,Delaunay triangulation,linear programming,closest pair,smallest enclosing disk,least-element lists,strongly connected components
Journal
67
Issue
ISSN
Citations 
5
0004-5411
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Guy E. Blelloch12927207.30
Yan Gu2435.10
Julian Shun359332.57
Yihan Sun47311.19