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Recursive Data Structures and Parallelism Detection

dc.contributor.authorHendren, Laurie J.en_US
dc.date.accessioned2007-04-23T17:33:26Z
dc.date.available2007-04-23T17:33:26Z
dc.date.issued1988-06en_US
dc.description.abstractInterference estimation is a key aspect of automatic parallelization of programs. In this paper we study the problem of estimating interference in a language with dynamic data-structures. We focus on the case of binary trees to illustrate the approach. We develop a structural flow-analysis technique that allows us to estimate whether two statements influence disjoint sub-trees of a forest of dynamically-allocated binary trees. The method uses a regular-expression-like representation of the relationships between the nodes of the trees and is based on the algebraic properties of such expressions. We have implemented our analysis in Standard ML and have obtained some promising experimental results.en_US
dc.format.extent1936786 bytes
dc.format.extent496670 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.identifier.citationhttp://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR88-924en_US
dc.identifier.urihttps://hdl.handle.net/1813/6764
dc.language.isoen_USen_US
dc.publisherCornell Universityen_US
dc.subjectcomputer scienceen_US
dc.subjecttechnical reporten_US
dc.titleRecursive Data Structures and Parallelism Detectionen_US
dc.typetechnical reporten_US

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