The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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A Wide-Window Superscalar Microprocessor Profiling Performance Model Using Multiple Branch Prediction

대형 윈도우에서 다중 분기 예측법을 이용하는 수퍼스칼라 프로세서의 프로화일링 성능 모델

  • 이종복 (한성대 공대 정보통신학과)
  • Published : 2009.07.01
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Abstract

This paper presents a profiling model of a wide-window superscalar microprocessor using multiple branch prediction. The key idea is to apply statistical profiling technique to the superscalar microprocessor with a wide instruction window and a multiple branch predictor. The statistical profiling data are used to obtain a synthetical instruction trace, and the consecutive multiple branch prediction rates are utilized for running trace-driven simulation on the synthesized instruction trace. We describe our design and evaluate it with the SPEC 2000 integer benchmarks. Our performance model can achieve accuracy of 8.5 % on the average.

Keywords

References

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