Dynamic dependence analysis: A novel method for data dependence evaluation

P. Peterson, D. Padua

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A dynamic evaluation of the effects of data dependence analysis in the Perfect Benchmarks is demonstrated. We show that it is possible to measure the optimal parallelism, as defined by our model, and to compare the obtained parallelism for various data dependence tests with the optimal parallelism. We find that a variation of Banerjee’s inequalities is sufficient in all cases to obtain more than half of the available parallelism, and that the Omega test does not contribute significantly to the measured parallelism.

Original languageEnglish (US)
Title of host publicationLanguages and Compilers for Parallel Computing - 5th International Workshop, Proceedings
EditorsUtpal Banerjee, David Gelernter, Alex Nicolau, David Padua
PublisherSpringer-Verlag Berlin Heidelberg
Pages64-81
Number of pages18
ISBN (Print)9783540575023
DOIs
StatePublished - 1993
EventIFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2017 - Hamburg, Germany
Duration: Sep 3 2017Sep 7 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume757 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherIFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2017
CountryGermany
CityHamburg
Period9/3/179/7/17

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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