Dynamic branch predictor logic alone accounts for approximately 10% of total processor power dissipation. Recent research indicates that the power cost of a large dynamic branch predictor is offset by the power savings created by its increased accuracy. We describe a method of reducing dynamic predictor power dissipation without degrading prediction accuracy by using a combination of local delay region scheduling and run time profiling of branches. Feedback into the static code is achieved with hint bits and avoids the need for dynamic prediction for some individual branches. This method requires only minimal hardware modifications and coexists with a dynamic predictor. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Hicks, M., Egan, C., Christianson, B., & Quick, P. (2006). Reducing the branch power cost in embedded processors through static scheduling, profiling and SuperBlock formation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4186 LNCS, pp. 366–372). Springer Verlag. https://doi.org/10.1007/11859802_31
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