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Statistical estimation of leakage power dissipation in nano-scale complementary metal oxide semiconductor digital circuits using generalised extreme value distribution

机译:基于广义极值分布的纳米级互补金属氧化物半导体数字电路泄漏功率耗散的统计估计

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摘要

In this study, the authors present an accurate approach for the estimation of statistical distribution of leakage power consumption in the presence of process variations in nano-scale complementary metal oxide semiconductor (CMOS) technologies. The technique, which is additive with respect to the individual gate leakage values, employs a generalised extreme value (GEV) distribution. Compared with the previous methods based on (two-parameter) lognormal distribution, this method uses the GEV distribution with three parameters to increase the accuracy. Using the suggested distribution, the leakage yield of the circuits may be modelled. The accuracy of the approach is studied by comparing its results with those of a previous technique and HSPICE-based Monte Carlo simulations on ISCAS85 benchmark circuits for 45 nm CMOS technology. The comparison reveals a higher accuracy for the proposed approach. The proposed distribution does not add to the complexity and cost of simulations compared with the case of the lognormal distribution based on the additive approach.
机译:在这项研究中,作者提出了一种在纳米级互补金属氧化物半导体(CMOS)技术存在工艺变化的情况下估算漏电功耗统计分布的准确方法。该技术相对于各个栅极泄漏值具有累加性,它采用了广义极值(GEV)分布。与以前的基于(两参数)对数正态分布的方法相比,该方法使用具有三个参数的GEV分布来提高准确性。使用建议的分布,可以对电路的泄漏量进行建模。通过将其结果与先前技术的结果以及基于HSPICE的45 nm CMOS技术的ISCAS85基准电路的基于HSPICE的蒙特卡罗仿真进行比较,研究了该方法的准确性。比较表明,该方法具有较高的准确性。与基于加法的对数正态分布相比,该提议的分布不会增加仿真的复杂性和成本。

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