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John R. Allen

dblp:34/3948 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1983
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Compilers and program optimization · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Compilers and program optimization › parallelization
automatic parallelization
0.011983
Conversion of Control Dependence to Data Dependence · POPL 1983
Compilers and program optimization › dependence analysis
control dependence
0.011983
Conversion of Control Dependence to Data Dependence · POPL 1983
Compilers and program optimization
dependence analysis
0.011983
Conversion of Control Dependence to Data Dependence · POPL 1983

Methods — techniques the papers use, named apart from their topics

vectorization · 0.0program transformation · 0.0
YearPublicationVenuePosition
1983 Conversion of Control Dependence to Data Dependence
abstract
Program analysis methods, especially those which support automatic vectorization, are based on the concept of interstatement dependence where a dependence holds between two statements when one of the statements computes values needed by the other. Powerful program transformation systems that convert sequential programs to a form more suitable for vector or parallel machines have been developed using this concept [AllK 82, KKLW 80].The dependence analysis in these systems is based on data dependence. In the presence of complex control flow, data dependence is not sufficient to transform programs because of the introduction of control dependences. A control dependence exists between two statements when the execution of one statement can prevent the execution of the other. Control dependences do not fit conveniently into dependence-based program translators.One solution is to convert all control dependences to data dependences by eliminating goto statements and introducing logical variables to control the execution of statements in the program. In this scheme, action statements are converted to IF statements. The variables in the conditional expression of an IF statement can be viewed as inputs to the statement being controlled. The result is that control dependences between statements become explicit data dependences expressed through the definitions and uses of the controlling logical variables.This paper presents a method for systematically converting control dependences to data dependences in this fashion. The algorithms presented here have been implemented in PFC, an experimental vectorizer written at Rice University.
John R. Allen, Ken Kennedy, Carrie Porterfield, Joe D. Warren
POPL1