Target prediction for indirect jumps

  • Authors:

  • Po-Yung Chang;Eric Hao;Yale N. Patt

  • Affiliations:

  • Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, Michigan;Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, Michigan;Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, Michigan

  • Venue:
  • Proceedings of the 24th annual international symposium on Computer architecture
  • Year:
  • 1997

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Abstract

As the issue rate and pipeline depth of high performance superscalar processors increase, the amount of speculative work issued also increases. Because speculative work must be thrown away in the event of a branch misprediction, wide-issue, deeply pipelined processors must employ accurate branch predictors to effectively exploit their performance potential. Many existing branch prediction schemes are capable of accurately predicting the direction of conditional branches. However, these schemes are ineffective in predicting the targets of indirect jumps achieving, on average, a prediction accuracy rate of 51.8% for the SPECint95 benchmarks. In this paper, we propose a new prediction mechanism, the target cache, for predicting indirect jump targets. For the perl and gcc benchmarks, this mechanism reduces the indirect jump misprediction rate by 93.4% and 63.35% and the overall execution time by 14% and 5%.