Statistical Gate Level Simulation via Voltage Controlled Current Source Models

Bao Liu, A. Kahng
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引用次数: 20

Abstract

Current source based gate models achieve orders of magnitude of improved accuracy than the previous voltage source and effective load capacitance based gate models. Increasingly significant variability in DSM and nanometer scale VLSI designs calls for statistical analysis and optimization. In this paper, we propose a more efficient statistical gate level simulation method than Monte Carlo simulation based on current source based gate models. We represent a variational voltage waveform of any shape by a time domain statistical variable, and compute variational gate output voltage waveform by time domain integration of statistical variables which takes into account input voltage waveform variation and process variations with their correlations. Our experiments show that our statistical gate level simulation achieves over 20times efficiency improvement with an average of 4.1%(22.3%) accuracy loss for the means (standard deviations) of gate delay compared with 1000times Monte Carlo simulation based on current source based gate models
通过电压控制电流源模型的统计门电平仿真
与之前基于电压源和有效负载电容的栅极模型相比,基于电流源的栅极模型的精度提高了几个数量级。在DSM和纳米级超大规模集成电路设计日益显著的可变性要求统计分析和优化。在本文中,我们提出了一种比基于电流源栅极模型的蒙特卡罗仿真更有效的统计栅极级仿真方法。我们用时域统计变量表示任意形状的变分电压波形,并通过考虑输入电压波形变化和过程变化及其相关性的统计变量的时域积分计算变分栅极输出电压波形。我们的实验表明,与基于电流源的栅极模型的1000倍蒙特卡罗模拟相比,我们的统计栅极级模拟实现了20倍以上的效率提高,栅极延迟均值(标准差)的平均精度损失为4.1%(22.3%)
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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