Difficult-path branch prediction using subordinate microthreads

  • Chappell R
  • Tseng F
  • Yoaz A
 et al. 
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Abstract

Branch misprediction penalties continue to increase as
microprocessor cores become wider and deeper. Thus, improving branch
prediction accuracy remains an important challenge. Simultaneous
subordinate microthreading (SSMT) provides a means to improve branch
prediction accuracy. SSMT machines run multiple, concurrent microthreads
in support of the primary thread. We propose to dynamically construct
microthreads that can speculatively and accurately pre-compute branch
outcomes along frequently mispredicted paths. The mechanism is intended
to be implemented entirely in hardware. We present the details for doing
so. We show how to select the right paths, how to generate accurate
predictions, and how to get this information in a timely way. We achieve
an average gain of 8.4% (42% maximum) over a very aggressive baseline
machine on the SPECint95 and SPECint2000 benchmark suites

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Authors

  • Robert S. Chappell

  • Francis Tseng

  • Adi Yoaz

  • Yale N. Patt

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