Choice Predictor for Free

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.

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