The program dependence graph and its use in optimization

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The program dependence graph and its use in optimization (1987)

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by Jeanne Ferrante , Karl J. Ottenstein , Joe D. Warren

Venue:	ACM Transactions on Programming Languages and Systems
Citations:	995 - 3 self

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@ARTICLE{Ferrante87theprogram,
    author = {Jeanne Ferrante and Karl J. Ottenstein and Joe D. Warren},
    title = {The program dependence graph and its use in optimization},
    journal = {ACM Transactions on Programming Languages and Systems},
    year = {1987},
    volume = {9},
    pages = {319--349}
}

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Abstract

In this paper we present an intermediate program representation, called the program dependence graph (PDG), that makes explicit both the data and control dependence5 for each operation in a program. Data dependences have been used to represent only the relevant data flow relationships of a program. Control dependence5 are introduced to analogously represent only the essential control flow relationships of a program. Control dependences are derived from the usual control flow graph. Many traditional optimizations operate more efficiently on the PDG. Since dependences in the PDG connect computationally related parts of the program, a single walk of these dependences is sufficient to perform many optimizations. The PDG allows transformations such as vectorization, that previ-ously required special treatment of control dependence, to be performed in a manner that is uniform for both control and data dependences. Program transformations that require interaction of the two dependence types can also be easily handled with our representation. As an example, an incremental approach to modifying data dependences resulting from branch deletion or loop unrolling is intro-duced. The PDG supports incremental optimization, permitting transformations to be triggered by one another and applied only to affected dependences.

Keyphrases

program dependence graph data dependence control dependence control dependence5 dependence type related part branch deletion incremental approach required special treatment loop unrolling many optimization relevant data flow relationship pdg connect intermediate program representation affected dependence program transformation essential control flow relationship many traditional optimization single walk usual control flow graph incremental optimization

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