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Eliminating False Data Dependences using the Omega Test

dc.contributor.authorPugh, Williamen_US
dc.contributor.authorWonnacott, Daviden_US
dc.description.abstractArray data dependence analysis methods currently in use generate false dependences that can prevent useful program transformations. These false dependences arise because the questions asked are conservative approximations to the questions we really should be asking. Unfortunately, the questions we really should be asking go beyond integer programming and require decision procedures for a subclass of Presburger formulas. In this paper, we describe how to extend the Omega test so that it can answer these queries and allow us to eliminate these false data dependences. We have implemented the techniques described here and believe they are suitable for use in production compilers. (An earlier version of this paper appeared at the ACM SIGPLAN PLDI'92 conference). (Also cross-referenced as UMIACS-TR-93-132)en_US
dc.format.extent208517 bytes
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-3191en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-93-132en_US
dc.titleEliminating False Data Dependences using the Omega Testen_US
dc.typeTechnical Reporten_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US

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