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A Current-based Method for Short Circuit Power Calculation under Noisy Input Waveforms

机译:噪声输入波形下基于电流的短路功率计算方法

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An accurate model is presented to calculate the short circuit energy dissipation of logic cells. The short circuit current is highly dependent on the input and output voltage values. Therefore the actual shape of the voltage signal waveforms at the input and output of the cell should be considered in order to precisely calculate the short circuit energy dissipation. Previous approaches such as the approximation of the crosstalk induced noisy waveforms with saturated ramps can lead to short circuit energy estimation errors as high as an order of magnitude for a minimum sized inverter. To resolve this shortcoming, a current-based logic cell model is utilized, which constructs the output voltage waveform for a given noisy input waveform. The input and output voltage waveforms are then used to calculate the short circuit current, and hence, short circuit energy dissipation. A characterization process is executed for each logic cell in the standard cell library to model the relevant electrical parameters e.g., the parasitic capacitances and nonlinear current sources. Additionally, our model is capable of calculating the short circuit energy dissipation caused by glitches in VLSI circuits, which in some cases can be a key contributor to the total circuit energy dissipation. Experimental results show an average error ofabout 1% and a maximum error of 3% compared to SPICE for different types of logic cells under noisy input waveforms including glitches while the runtime speedup is up to a factor of 16,000.
机译:提出了一个精确的模型来计算逻辑单元的短路能量耗散。短路电流高度依赖于输入和输出电压值。因此,应该考虑单元的输入和输出处的电压信号波形的实际形状,以便精确计算短路能量耗散。先前的方法(例如用饱和斜坡对串扰感应的噪声波形进行逼近)可能导致短路能量估算误差,对于最小尺寸的逆变器而言,误差高达一个数量级。为了解决该缺点,利用了基于电流的逻辑单元模型,该模型为给定的噪声输入波形构造了输出电压波形。然后,使用输入和输出电压波形来计算短路电流,从而计算出短路能量的消耗。对标准单元库中的每个逻辑单元执行表征过程,以对相关的电参数(例如,寄生电容和非线性电流源)进行建模。此外,我们的模型能够计算由VLSI电路中的毛刺引起的短路能量耗散,在某些情况下,这可能是总电路能量耗散的关键因素。实验结果表明,在嘈杂的输入波形(包括毛刺)下,不同类型的逻辑单元的平均误差约为SPICE的1%,最大误差为3%,而运行时加速则高达16,000倍。

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