Tejas S. Karkhanis
ABSTRACT
A proposed performance model for superscalar processorsconsists of 1) a component that models the relationshipbetween instructions issued per cycle and the sizeof the instruction window under ideal conditions, and 2)methods for calculating transient performance penaltiesdue to branch mispredictions, instruction cache misses,and data cache misses.Using trace-derived data dependenceinformation, data and instruction cache miss rates,and branch miss-prediction rates as inputs, the model canarrive at performance estimates for a typical superscalarprocessor that are within 5.8% of detailed simulation onaverage and within 13% in the worst case. The modelalso provides insights into the workings of superscalarprocessors and long-term microarchitecture trends such aspipeline depths and issue widths.
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