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dc.contributor.authorPark, Jongse
dc.contributor.authorZhang, Xin
dc.contributor.authorNi, Kangqi
dc.contributor.authorEsmaeilzadeh, Hadi
dc.contributor.authorNaik, Mayur
dc.date.accessioned2014-07-15T20:25:27Z
dc.date.available2014-07-15T20:25:27Z
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/1853/52032
dc.descriptionResearch areas: Programming analysis, Approximate computingen_US
dc.description.abstractWe present ExpAX, a framework for automating approximate programming. ExpAX consists of these three components: (1) a programming model based on a new kind of program specification, which we refer to as error expectations. Our programming model enables programmers to implicitly relax the accuracy constraints without explicitly marking operations as approximate; (2) an approximation safety analysis that automatically infers a safe-to-approximate set of program operations; and (3) an optimization that automatically marks a subset of the safe-to-approximate operations as approximate while statistically adhering to the error expectations. We evaluate ExpAX on a diverse set of Java applications. The results show that ExpAX provides significant energy savings (up to 35%) with large reduction in programmer effort (between 3x to 113x ) while providing formal safety and statistical quality-of-result guarantees.
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.relation.ispartofseriesSCS Technical Report ; GT-CS-14-05en_US
dc.subjectApproximate programmingen_US
dc.subjectApproximation safety analysisen_US
dc.subjectExpAXen_US
dc.subjectGreedy refiningen_US
dc.subjectStochastic optimizationen_US
dc.titleExpAX: A Framework for Automating Approximate Programmingen_US
dc.typeTechnical Reporten_US
dc.contributor.corporatenameGeorgia Institute of Technology. College of Computingen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Computer Scienceen_US
dc.embargo.termsnullen_US


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