Title:
Choice Predictor for Free
Choice Predictor for Free
| 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.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.identifier.uri | http://hdl.handle.net/1853/5921 | |
| 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 | Text | |
| dc.type.genre | Technical Report | |
| dspace.entity.type | Publication | |
| local.contributor.corporatename | Center for Experimental Research in Computer Systems | |
| local.relation.ispartofseries | CERCS Technical Report Series | |
| relation.isOrgUnitOfPublication | 1dd858c0-be27-47fd-873d-208407cf0794 | |
| relation.isSeriesOfPublication | bc21f6b3-4b86-4b92-8b66-d65d59e12c54 |