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Power modeling for high-level power estimation

机译:用于高级功率估算的功率建模

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摘要

In this paper, we propose a modeling approach that captures the dependence of the power dissipation of a combinational logic circuit on its input/output signal switching statistics. The resulting power macromodel, consisting of a single four-dimensional table, can be used to estimate the power consumed in the circuit for any given input/output signal statistics. Given a low-level (typically gate-level) description of the circuit, we describe a characterization process by which such a table model can be automatically built. The four dimensions of our table-based model are the average input signal probability, average input transition density, average spatial correlation coefficient, and average output zero-delay transition density. This approach has been implemented and models have been built for many benchmark circuits. Over a wide range of input signal statistics, we show that this model gives very good accuracy, with an rms error of about 4% and average error of about 6%. Except for one out of about 10 000 cases, the largest error observed was under 20%. If one ignores the glitching activity, then the rms error becomes under 1%, the average error becomes under 5%, and the largest error observed in all cases is under 18%.
机译:在本文中,我们提出了一种建模方法,该方法捕获了组合逻辑电路的功耗对其输入/输出信号切换统计数据的依赖性。由此产生的功率宏模型(由单个四维表组成)可用于估计任何给定的输入/输出信号统计数据在电路中消耗的功率。给定电路的低级描述(通常是门级描述),我们描述了一种表征过程,通过该过程可以自动建立这种表模型。我们基于表的模型的四个维度是平均输入信号概率,平均输入过渡密度,平均空间相关系数和平均输出零延迟过渡密度。已经实现了这种方法,并为许多基准电路建立了模型。在广泛的输入信号统计范围内,我们证明该模型具有非常好的精度,均方根误差约为4%,平均误差约为6%。除了约1万例病例中的1例,观察到的最大误差在20%以下。如果忽略毛刺活动,则均方根误差将低于1%,平均误差将低于5%,并且在所有情况下观察到的最大误差都将低于18%。

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