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首页> 外文期刊>Journal of Low Power Electronics >Statistical Moment Estimation of Delay and Power in Circuit Simulation
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Statistical Moment Estimation of Delay and Power in Circuit Simulation

机译:电路仿真中延迟和功率的统计矩估计

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摘要

Monte Carlo methods and simulation are often used to estimate the mean, variance, and higher order statistical moments of circuit properties like delay and power. The main issues with Monte Carlo methods are the required long run time and the need for prior detailed knowledge of the distribution of the variations. Additionally, most of available circuit simulation tools can run Monte Carlo analysis for Gaussian, lognormal and uniform distribution only. In this paper, in order to estimate these statistical moments, we propose a new method based on a uniform sampling technique and a weighted sample estimator. The proposed method needs significantly fewer simulation runs, and does not need detailed prior knowledge of the variation distributions. Furthermore, it can be used for any type of probability distribution irrespective of the circuit simulation tool used for the analysis. The results obtained show that the proposed method needs 100× fewer simulations iterations than Monte Carlo runs for accurate moments estimation of delay and power for standard cells in 45 nm and 32 nm technologies.
机译:蒙特卡洛方法和仿真通常用于估计电路特性(如延迟和功率)的均值,方差和高阶统计矩。蒙特卡洛方法的主要问题是需要较长的运行时间,并且需要事先详细了解变化的分布。此外,大多数可用的电路仿真工具只能对高斯分布,对数正态分布和均匀分布运行蒙特卡洛分析。在本文中,为了估计这些统计矩,我们提出了一种基于统一采样技术和加权样本估计量的新方法。所提出的方法需要少得多的仿真运行,并且不需要详细的变化分布先验知识。此外,它可用于任何类型的概率分布,而与用于分析的电路仿真工具无关。获得的结果表明,对于45 nm和32 nm技术中标准单元的延迟和功率的精确矩估计,所提出的方法比Monte Carlo运行所需的仿真迭代少100倍。

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