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    Abstract:

    SimpleScalar is a superscalar processor monitor which is used widely in performance analysis. This paper first analyzes the internal architecture of SimpleScalar, and on this basis, in-depth analyzes the mechanism to achieve branch prediction. Through an in-depth study of Perceptron-based branch predictor imple- mentation mechanism, it proposes a design to let SimpleScalar support Perceptron-based branch predictor. And this has practical significance for superscalar processor performance modeling and research.

    Reference
    1 陈剑龙,傅忠传,崔刚. SimpleScalar模拟器内核分析及应用.哈尔滨工业大学学报, 2004,36 (5):652-653.
    2 Smith JE. A study of branch prediction strategies. Proc. of the 8th Annual International Symposium on Computer Architecture. 1981.135-148.
    3 Yeh TY, Patt YN. A comparison of dynamic branch predictors that use two levels of branch history. Proc. of the 20th Annual International Symposium on Computer Architecture. 1993.257-266. 联性的RelevanceHeur算法。实验数据对比表明, RelevanceHeur算法能快速地选择出比原有启发式算法更优的候选指令集合,并且时间性能大大优于已有的算法,能够很好的应用于支持自定义指令扩展的ASIP应用中。
    4 Jimenez DA, Lin C. Neural methods for dynamic branch prediction. ACM Transactions on Computer Systems, 2002,20(4):369-397.
    5 Ho CY, Chng KF, Yau CH, Anthony SS. Fong. A study of dynamic branch predictors: Counter versus percep- tron. Proc. of the International Conference on Informa- tion Technology. 2007.528 – 563.
    6 Jimenez DA, Lin C. Dynamic branch prediction with perceptron. Proc. of the 7th Int’l Symposium on High Performance Computer Architecture. 2001.197–206.
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叶新栋,唐志强,涂时亮. Perceptron-Based 分支预测SimpleScalar中的实现.计算机系统应用,2010,19(1):51-54

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  • Received:April 06,2009
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