{"title":"Towards a theory of nearly constant time parallel algorithms","authors":"Joseph Gil, Yossi Matias, U. Vishkin","doi":"10.1109/SFCS.1991.185438","DOIUrl":null,"url":null,"abstract":"It is demonstrated that randomization is an extremely powerful tool for designing very fast and efficient parallel algorithms. Specifically, a running time of O(lg* n) (nearly-constant), with high probability, is achieved using n/lg* n (optimal speedup) processors for a wide range of fundamental problems. Also given is a constant time algorithm which, using n processors, approximates the sum of n positive numbers to within an error which is smaller than the sum by an order of magnitude. A variety of known and new techniques are used. New techniques, which are of independent interest, include estimation of the size of a set in constant time for several settings, and ways for deriving superfast optimal algorithms from superfast nonoptimal ones.<<ETX>>","PeriodicalId":320781,"journal":{"name":"[1991] Proceedings 32nd Annual Symposium of Foundations of Computer Science","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"137","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991] Proceedings 32nd Annual Symposium of Foundations of Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SFCS.1991.185438","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 137
Abstract
It is demonstrated that randomization is an extremely powerful tool for designing very fast and efficient parallel algorithms. Specifically, a running time of O(lg* n) (nearly-constant), with high probability, is achieved using n/lg* n (optimal speedup) processors for a wide range of fundamental problems. Also given is a constant time algorithm which, using n processors, approximates the sum of n positive numbers to within an error which is smaller than the sum by an order of magnitude. A variety of known and new techniques are used. New techniques, which are of independent interest, include estimation of the size of a set in constant time for several settings, and ways for deriving superfast optimal algorithms from superfast nonoptimal ones.<>