Choice Predictor for Free

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dc.contributor.author Ekpanyapong, Mongkol
dc.contributor.author Korkmaz, Pinar
dc.contributor.author Lee, Hsien-Hsin Sean
dc.date.accessioned 2005-03-21T16:51:04Z
dc.date.available 2005-03-21T16:51:04Z
dc.date.issued 2003
dc.identifier.uri http://hdl.handle.net/1853/5921
dc.description.abstract Reducing 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.extent 275406 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.publisher Georgia Institute of Technology en
dc.relation.ispartofseries CERCS;GIT-CERCS-03-03
dc.subject Energy consumption en
dc.subject Microprocessors en
dc.subject Design en
dc.subject Profile-guided static prediction techniques en
dc.subject Static Correlation Choice prediction en
dc.subject SCC en
dc.subject Static Choice prediction en
dc.subject SC en
dc.subject Branch prediction en
dc.subject Die area en
dc.title Choice Predictor for Free en
dc.type Technical Report en


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