Loop Termination Prediction

نویسندگان

  • Timothy Sherwood
  • Brad Calder
چکیده

Deeply pipelined high performance processors require highly accurate branch prediction to drive their instruction fetch. However there remains a class of events which are not easily predictable by standard two level predictors. One such event is loop termination. In deeply nested loops, loop terminations can account for a significant amount of the mispredictions. We propose two techniques for dealing with loop terminations. A simple hardware extension to existing prediction architectures called Loop Termination Prediction is presented, which captures the long regular repeating patterns of loops. In addition, a software technique called Branch Splitting is examined, which breaks loops with iteration counts above the detection of current predictors into smaller loops that may be effectively captured. Our results show that for many programs adding a small loop termination buffer can reduce the missprediction rate by up to a difference of 2%.

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تاریخ انتشار 2000