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A 2-clock-cycle Na?ve Bayes classifier for dynamic branch prediction in pipelined RISC microprocessors

机译:一种用于流水型RISC微处理器的动态分支预测的2时钟周期Na?Ve贝叶斯分类器

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In this paper, we propose a Bayesian branch-prediction circuit consisting of an instruction-feature extractor and a nai?ve Bayes classifier (NBC). Its purpose is to replace conventional branch predictors in modern pipelined RISC microprocessors. The proposed circuit is based on the conventional neural branch predictor [1]; however, the linear classifier circuit is replaced by the proposed NBC circuit. Implementing approximate Bayesian computation and its highly-parallel architectures, the NBC circuit completes branch prediction within 2 clock cycles per instruction, and is this suitable for implementation on standard pipelined microprocessors.
机译:在本文中,我们提出了一种由指令特征提取器和NAI贝雷斯分类器(NBC)组成的贝叶斯分支预测电路。其目的是在现代流水线RISC微处理器中取代传统的分支预测因子。所提出的电路基于传统的神经分支预测器[1];但是,线性分级器电路由所提出的NBC电路代替。实现近似贝叶斯计算及其高度平行架构,NBC电路在每条指令的2个时钟周期内完成分支预测,并且这适用于在标准流水线微处理器上实现。

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