Efficient Execution of Multi-Query Data Analysis Batches Using Compiler Optimization Strategies

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dc.contributor.authorAndrade, Henriqueen_US
dc.contributor.authorAryangat, Sureshen_US
dc.contributor.authorKurc, Tahsinen_US
dc.contributor.authorSaltz, Joelen_US
dc.contributor.authorSussman, Alanen_US
dc.date.accessioned2004-05-31T23:30:50Z
dc.date.available2004-05-31T23:30:50Z
dc.date.created2003-07en_US
dc.date.issued2003-08-01en_US
dc.description.abstractThis work investigates the leverage that can be obtained from compiler optimization techniques for efficient execution of multi-query workloads in data analysis applications. Our approach is to address multi-query optimization at the algorithmic level by transforming a declarative specification of scientific data analysis queries into a high-level imperative program that can be made more efficient by applying compiler optimization techniques. These techniques -- including loop fusion, common subexpression elimination and dead code elimination -- are employed to allow data and computation reuse across queries. We describe a preliminary experimental analysis on a real remote sensing application that is used to analyze very large quantities of satellite data. The results show our techniques achieve sizable reduction in the amount of computation and I/O necessary for executing query batches and in average executing times for the individual queries in a given batch. (UMIACS-TR-2003-76)en_US
dc.format.extent550399 bytes
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/1903/1300
dc.language.isoen_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
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-4507en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-2003-76en_US
dc.titleEfficient Execution of Multi-Query Data Analysis Batches Using Compiler Optimization Strategiesen_US
dc.typeTechnical Reporten_US

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