Efficiently computing static single assignment form and the control dependence graph

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Efficiently computing static single assignment form and the control dependence graph (1991)

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by Ron Cytron , Jeanne Ferrante , Barry K. Rosen , Mark N. Wegman , F. Kenneth Zadeck

Venue:	ACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS
Citations:	989 - 8 self

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@ARTICLE{Cytron91efficientlycomputing,
    author = {Ron Cytron and Jeanne Ferrante and Barry K. Rosen and Mark N. Wegman and F. Kenneth Zadeck},
    title = {Efficiently computing static single assignment form and the control dependence graph},
    journal = {ACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS},
    year = {1991},
    volume = {13},
    pages = {451--490}
}

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Abstract

In optimizing compilers, data structure choices directly influence the power and efficiency of practical program optimization. A poor choice of data structure can inhibit optimization or slow compilation to the point that advanced optimization features become undesirable. Recently, static single assignment form and the control dependence graph have been proposed to represent data flow and control flow propertiee of programs. Each of these previously unrelated techniques lends efficiency and power to a useful class of program optimization. Although both of these structures are attractive, the difficulty of their construction and their potential size have discouraged their use. We present new algorithms that efficiently compute these data structures for arbitrary control flow graphs. The algorithms use dominance frontiers, a new concept that may have other applications. We also give analytical and experimental evidence that all of these data structures are usually linear in the size of the original program. This paper thus presents strong evidence that these structures can be of practical use in optimization.

Keyphrases

control dependence graph static single assignment form data structure optimization feature present new algorithm experimental evidence practical use useful class potential size new concept poor choice program optimization original program practical program optimization strong evidence algorithm use dominance frontier control flow propertiee data structure choice arbitrary control flow graph data flow unrelated technique

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