How to share memory in a distributed system

Eli Upfal, Avi Wigderson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We study the power of shared-memory in models of parallel computation. We describe a novel distributed data structure that eliminates die need for shared memory without significantly increasing the run time of the parallel computation. More specifically we show how a complete network of processors can dcterministicly simulate one PRAM step in O(log h (loglog n)2) time, when both models use n processors, and the size of the PRAM's shared memory is polynomial in n. (The best previously known upper bound was the trivial O(n)). We also establish that this upper bounds is nearly optimal. We prove that an on-line simulation of T PRAM steps by a complete network of processors requires Ω(Tloglog n/loglog n A simple consequence of the upper bound is that an Ultracomputer (the only currently feasible general purpose parallel machine), can simulate one step of a PRAM (the most convenient parallel model to program), in O((log n loglog n)2) steps.

Original languageEnglish
Title of host publication25th Annual Symposium on Foundations of Computer Science, FOCS 1984
PublisherIEEE Computer Society
Pages171-180
Number of pages10
ISBN (Electronic)081860591X
StatePublished - 1984
Externally publishedYes
Event25th Annual Symposium on Foundations of Computer Science, FOCS 1984 - Singer Island, United States
Duration: 24 Oct 198426 Oct 1984

Publication series

NameProceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS
Volume1984-October
ISSN (Print)0272-5428

Conference

Conference25th Annual Symposium on Foundations of Computer Science, FOCS 1984
Country/TerritoryUnited States
CitySinger Island
Period24/10/8426/10/84

Bibliographical note

Publisher Copyright:
© 1984 IEEE.

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