Reducing the Branch Power Cost in Embedded Processors Through Static Scheduling, Profiling and SuperBlock Formation

نویسندگان

  • Michael Hicks
  • Colin Egan
  • Bruce Christianson
  • Patrick Quick
چکیده

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.

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تاریخ انتشار 2006