Conversion of control dependence to data dependence

  • Authors:

  • J. R. Allen;Ken Kennedy;Carrie Porterfield;Joe Warren

  • Affiliations:

  • Rice University, Houston, Texas;Rice University, Houston, Texas;Rice University, Houston, Texas;Rice University, Houston, Texas

  • Venue:
  • POPL '83 Proceedings of the 10th ACM SIGACT-SIGPLAN symposium on Principles of programming languages
  • Year:
  • 1983

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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.