An analysis of dynamic branch prediction schemes on system workloads

  • Authors:

  • Nicolas Gloy;Cliff Young;J. Bradley Chen;Michael D. Smith

  • Affiliations:

  • Division of Applied Sciences, Harvard University;Division of Applied Sciences, Harvard University;Division of Applied Sciences, Harvard University;Division of Applied Sciences, Harvard University

  • Venue:
  • ISCA '96 Proceedings of the 23rd annual international symposium on Computer architecture
  • Year:
  • 1996

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Abstract

Recent studies of dynamic branch prediction schemes rely almost exclusively on user-only simulations to evaluate performance. We find that an evaluation of these schemes with user and kernel references often leads to different conclusions. By analyzing our own Atom-generated system traces and the system traces from the Instruction Benchmark Suite, we quantify the effects of kernel and user interactions on branch prediction accuracy. We find that user-only traces yield accurate prediction results only when the kernel accounts for less than 5% of the total executed instructions. Schemes that appear to predict well under user-only traces are not always the most effective on full-system traces: the recently-proposed two-level adaptive schemes can suffer from higher aliasing than the original per-branch 2-bit counter scheme. We also find that flushing the branch history state at fixed intervals does not accurately model the true effects of user/kernel interaction.