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dc.contributor.authorEkpanyapong, Mongkol
dc.contributor.authorKorkmaz, Pinar
dc.contributor.authorLee, Hsien-Hsin Sean
dc.date.accessioned2005-03-21T16:51:04Z
dc.date.available2005-03-21T16:51:04Z
dc.date.issued2003
dc.identifier.urihttp://hdl.handle.net/1853/5921
dc.description.abstractReducing energy consumption has become the first priority in designing microprocessors for all market segments including embedded, mobile, and high performance processors. The trend of state-of-the-art branch predictor designs such as a hybrid predictor continues to feature more and larger prediction tables, thereby exacerbating the energy consumption. In this paper, we present two novel profile-guided static prediction techniques--- Static Correlation Choice (SCC) prediction and Static Choice (SC) prediction for alleviating the energy consumption without compromising performance. Using our techniques, the hardware choice predictor of a hybrid predictor can be completely eliminated from the processor and replaced with our off-line profiling schemes. Our simulation results show an average 40% power reduction compared to several hybrid predictors. In addition, an average 27% die area can be saved in the branch predictor hardware for other performance features.en
dc.format.extent275406 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technologyen
dc.relation.ispartofseriesCERCS;GIT-CERCS-03-03
dc.subjectEnergy consumptionen
dc.subjectMicroprocessorsen
dc.subjectDesignen
dc.subjectProfile-guided static prediction techniquesen
dc.subjectStatic Correlation Choice predictionen
dc.subjectSCCen
dc.subjectStatic Choice predictionen
dc.subjectSCen
dc.subjectBranch predictionen
dc.subjectDie areaen
dc.titleChoice Predictor for Freeen
dc.typeTechnical Reporten


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