A general approach for multivariate statistical MOSFET compact modeling preserving correlations

André Lange, C. Sohrmann, R. Jancke, J. Haase, B. Cheng, U. Kovac, A. Asenov
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引用次数: 14

Abstract

As feature sizes shrink, random fluctuations gain importance in semiconductor manufacturing and integrated circuit design. Therefore, statistical device variability has to be considered in circuit design and analysis to properly estimate their impact and avoid expensive over-design. Statistical MOSFET compact modeling is required to accurately capture marginal distributions of varying device parameters and to preserve their statistical correlations. Due to limited simulator capabilities, variables are often assumed to be normally distributed. Although correlations may be captured using Principal Component Analysis, such an assumption may be inaccurate. As an alternative, Nonlinear Power Models have been proposed. Since we see some limitations in this approach, we analyze whether the multivariate Generalized Lambda Distribution is an alternative for statistical device modeling. Applying both approaches to extracted statistical device parameters, we conclude that both methods do not differ significantly in accuracy, but the multivariate Generalized Lambda Distribution is more general and less computationally expensive.
多元统计型MOSFET紧凑建模的一般方法
随着特征尺寸的缩小,随机波动在半导体制造和集成电路设计中变得越来越重要。因此,在电路设计和分析中必须考虑统计器件可变性,以正确估计其影响并避免昂贵的过度设计。统计MOSFET紧凑建模需要准确捕获不同器件参数的边际分布,并保持它们的统计相关性。由于模拟器功能有限,变量通常被假定为正态分布。尽管可以使用主成分分析捕获相关性,但这样的假设可能是不准确的。作为一种替代方法,人们提出了非线性功率模型。由于我们看到了这种方法的一些局限性,我们分析了多元广义Lambda分布是否是统计设备建模的替代方法。应用这两种方法提取统计设备参数,我们得出结论,这两种方法在精度上没有显着差异,但多元广义Lambda分布更通用,计算成本更低。
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