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Parasitic$RC$Aware Delay Corner Model for Sub-10-nm Logic Circuit Design

机译:寄生 $ RC $ 可识别低于10纳米逻辑电路的延迟角模型

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In this paper, we propose a new statistical corner model for the precise variation analysis of CMOS logic gate delay. The conventional corner model includes pessimism in its prediction of delay variation as a result of inadequate statistical consideration of device characteristics. Therefore, to develop an accurate delay corner model, we analytically derive corner modeling targets for device characteristics, which are statistically shrunk when considering the variation and the correlation of transistor and parasitic resistance and capacitance (RC). Then, the derived targets are obtained by multiplying the conventional corner parameters using the newly proposed corner scaling factors. Simulation results verify that the corner model fitted to the proposed targets accurately predicts the three standard deviation limits of delay variation. To implement the parasiticRCaware delay corner in compact models of the process design kit, an artificial neural network is used to model the complex relationship between the parasiticRCand the delay corner model. The delay variations predicted by the proposed model match well with the Monte Carlo simulation results at various simulation conditions, unlike the conventional corner model, which introduces pessimism.
机译:在本文中,我们提出了一个新的统计角模型,用于CMOS逻辑门延迟的精确变化分析。由于对设备特性的统计考虑不足,传统的转角模型在其延迟变化的预测中包括悲观主义。因此,为了开发准确的延迟角模型,我们分析得出了器件特性的角模型目标,当考虑晶体管的变化和相关性以及寄生电阻和电容时,角模型目标在统计上会缩小( n <斜体xmlns:mml = “ http ://www.w3.org/1998/Math/MathML “ xmlns:xlink = ” http://www.w3.org/1999/xlink “> RC n)。然后,通过使用新提出的拐角缩放因子乘以常规拐角参数来获得导出的目标。仿真结果验证了适合所提出目标的拐角模型能够准确预测延迟变化的三个标准偏差极限。要实现寄生 n <斜体xmlns:mml = “ http://www.w3.org/1998/Math/MathML ” xmlns:xlink = “ http://www.w3.org/1999/xlink “> RC naware在过程设计工具包的紧凑模型中的延迟角,使用人工神经网络来建模寄生虫之间的复杂关系 n RC n和延迟角模型。所提出的模型预测的延迟变化与各种模拟条件下的蒙特卡洛模拟结果非常吻合,这与传统的转角模型会引入悲观主义不同。

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