Probabilistic program analysis for parallelizing compilers

I. Forsythe, Peter Milligan, Paul Sage

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


Parallelizing compilers have difficulty analysing and optimising complex code. To address this, some analysis may be delayed until run-time, and techniques such as speculative execution used. Furthermore, to enhance performance, a feedback loop may be setup between the compile time and run-time analysis systems, as in iterative compilation. To extend this, it is proposed that the run-time analysis collects information about the values of variables not already determined, and estimates a probability measure for the sampled values. These measures may be used to guide optimisations in further analyses of the program. To address the problem of variables with measures as values, this paper also presents an outline of a novel combination of previous probabilistic denotational semantics models, applied to a simple imperative language.
Original languageEnglish
Title of host publicationHigh Performance Computing for Computational Science: VECPAR 2004
Number of pages13
Publication statusPublished - Apr 2005
EventHigh Performance Computing for Computational Science - VECPAR 2004 - Valencia, Spain
Duration: 01 Apr 200501 Apr 2005

Publication series

NameLecture Notes in Computer Science
ISSN (Electronic)1611-3349


ConferenceHigh Performance Computing for Computational Science - VECPAR 2004

Bibliographical note

ISSN: 0302-9743

ASJC Scopus subject areas

  • Computer Science (miscellaneous)


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