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    Practical Techniques to Augment Dependence Analysis in the Presence of Symbolic Terms

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    Author
    Goff, Gina
    Date
    May 1997
    Abstract
    Dependence analysis is an indispensable tool in the automatic vectorization and parallelization of sequential programs, but performing symbolic dependence analysis can be costly and may fail to resolve many unknown terms. In this thesis, we explore ways to overcome the problems symbolic terms create for dependence analysis. We investigate three approaches to enhancing code optimization in the presence of symbolic terms: run-time testing, inserting user assertions, and compiling the program together with its input. Breaking conditions are created by the dependence analyzer when the presence of symbolic terms make it impossible to prove or disprove independence. If a breaking condition is satisfied at run-time, then optimized code can be executed. We show that the use of breaking conditions was responsible for more than one-fifth of all dependences eliminated in our test suite. Index array assertions are user-inserted directives describing special properties of the index arrays used in a program. We show that such directives can eliminate additional dependences by providing information that cannot be obtained using dependence analysis. Partial evaluation can be used to inspect a program's input file and disseminate the actual values of symbolic variables before dependence analysis is done. We show that partial evaluation assists dependence analysis by reducing the number of unknown symbolic terms. Algorithms for these techniques, developed and implemented in a parallelizing compiler, are presented, along with the results of several empirical studies.
    Description
    This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/19163
    Citation
    Goff, Gina. "Practical Techniques to Augment Dependence Analysis in the Presence of Symbolic Terms." (1997) https://hdl.handle.net/1911/96489.
    Type
    Technical report
    Citable link to this page
    https://hdl.handle.net/1911/96489
    Rights
    You are granted permission for the noncommercial reproduction, distribution, display, and performance of this technical report in any format, but this permission is only for a period of forty-five (45) days from the most recent time that you verified that this technical report is still available from the Computer Science Department of Rice University under terms that include this permission. All other rights are reserved by the author(s).
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    Home | FAQ | Contact Us | Privacy Notice | Accessibility Statement
    Managed by the Digital Scholarship Services at Fondren Library, Rice University
    Physical Address: 6100 Main Street, Houston, Texas 77005
    Mailing Address: MS-44, P.O.BOX 1892, Houston, Texas 77251-1892
    Site Map