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https://doi.org/10.1...arrow_drop_down
https://doi.org/10.1007/bfb001...
Part of book or chapter of book . 1996 . Peer-reviewed
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DBLP
Conference object . 2023
Data sources: DBLP
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Interprocedural analysis for parallelization

Authors: Mary W. Hall; Brian R. Murphy; Saman P. Amarasinghe; Shih-Wei Liao; Monica S. Lam;

Interprocedural analysis for parallelization

Abstract

This paper presents an extensive empirical evaluation of an interprocedural parallelizing compiler, developed as part of the Stanford SUIF compiler system. The system incorporates a comprehensive and integrated collection of analyses, including privatization and reduction recognition for both array and scalar variables, and symbolic analysis of array subscripts. The interprocedural analysis framework is designed to provide analysis results nearly as precise as full inlining but without its associated costs. Experimentation with this system on programs from standard benchmark suites demonstrate that an integrated combination of interprocedural analyses can substantially advance the capability of automatic parallelization technology.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Average
Top 10%
Top 10%
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