COMPLEXITY RESULTS FOR PERMUTING DATA AND OTHER COMPUTATIONS ON PARALLEL PROCESSORS.

Allan Gottlieb, Clyde P. Kruskal

Research output: Contribution to journalArticle

Abstract

For a wide class of problems, we obtain lower bounds for algorithms executed on certain parallel processors. These bounds show that for sufficiently large problems many known algorithms are optimal. The central result of the paper is the following sharper lower bound for permutation algorithms. Any permutation algorithm for N data items on a P processor parallel machine without shared memory requires time on the order of N log//kP/P, where K is the maximum number of processors directly connected to a single processor. In particular, a speedup on the order of P is impossible if K is bounded.

Original languageEnglish (US)
Pages (from-to)193-209
Number of pages17
JournalJournal of the ACM
Volume31
Issue number2
DOIs
StatePublished - Apr 1984

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Parallel Processors
Permutation
Lower bound
Parallel Machines
Shared Memory
Speedup
Data storage equipment

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Graphics and Computer-Aided Design
  • Hardware and Architecture
  • Information Systems
  • Software
  • Theoretical Computer Science

Cite this

COMPLEXITY RESULTS FOR PERMUTING DATA AND OTHER COMPUTATIONS ON PARALLEL PROCESSORS. / Gottlieb, Allan; Kruskal, Clyde P.

In: Journal of the ACM, Vol. 31, No. 2, 04.1984, p. 193-209.

Research output: Contribution to journalArticle

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