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

H. Fatemi, Shahin Nazarian, Massoud Pedram
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引用次数: 21

Abstract

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 of about 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.
噪声输入波形下基于电流的短路功率计算方法
提出了一种精确的逻辑单元短路能耗计算模型。短路电流高度依赖于输入和输出电压值。因此,为了精确计算短路能量耗散,应考虑电池输入端和输出端的电压信号波形的实际形状。以前的方法,如用饱和斜坡近似串扰引起的噪声波形,可能导致短路能量估计误差高达最小尺寸逆变器的一个数量级。为了解决这一缺点,采用了基于电流的逻辑单元模型,该模型针对给定的噪声输入波形构建输出电压波形。然后使用输入和输出电压波形来计算短路电流,从而计算短路能量耗散。对标准单元库中的每个逻辑单元执行表征过程,以模拟相关的电气参数,例如寄生电容和非线性电流源。此外,我们的模型能够计算由VLSI电路中的小故障引起的短路能量耗散,在某些情况下,这可能是电路总能量耗散的关键因素。实验结果表明,与SPICE相比,不同类型的逻辑单元在包含小故障的噪声输入波形下的平均误差约为1%,最大误差为3%,而运行时加速高达16,000倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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