An advanced statistical compact model strategy for SRAM simulation at reduced VDD
An advanced statistical compact model strategy for SRAM simulation at reduced VDD
复制标题
用于在降低 VDD 下进行 SRAM 仿真的先进统计紧凑模型策略
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
A. Asenov
中科院分区：
文献类型：
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作者：
P. Asenov;D. Reid;Scott Roy;C. Millar;A. Asenov
精确的统计紧凑模型提取和电路仿真是当代SRAM设计的关键问题。小SRAM单元晶体管的高统计可变性与高密度相结合导致由与平均值的5-6σ偏差确定的产量问题。本文提出的紧凑的建模方法利用了坚实的理解的物理现象的基础设备的变化。它的说明是基于全面的“原子"3D设备模拟。提取的统计模型，然后利用SRAM SNM仿真，并对基于高斯VT的仿真基准。结果表明，除了随着电源电压VDD的降低而增加的成品率估计误差之外，高斯VT模拟也未能捕获标称SNM和SNM之间的去相关。
Accurate statistical compact model extraction and circuit simulation are key issues in contemporary SRAM design. The high statistical variability of the small SRAM cell transistors in combination with high density leads to yield problems determined by 5-6σ deviations from the mean. The compact modeling approach presented in this paper utilizes a firm understanding of the physical phenomenon underlying device variability. Its illustration is based on comprehensive `atomistic' 3D device simulations. Extracted statistical models are then utilized in SRAM SNM simulation, and benchmarked against Gaussian VT based simulation. The results show that aside from the increasing error in the yield estimate with the reduction of the supply voltage VDD, Gaussian VT simulations also fail to capture the decorrelation between nominal SNM and SNM.
紧凑建模策略对现代 SRAM 中 SNM 和读取电流变化的影响
DOI：
10.1109/sispad.2011.6035024
发表时间：
2011
期刊：
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影响因子：
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作者：
Asenov P
通讯作者：
Asenov P
影响因子：
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作者：
B. Cheng;D. Dideban;N. Moezi;C. Millar;G. Roy;Xingsheng Wang;Scott Roy;A. Asenov
通讯作者：
B. Cheng;D. Dideban;N. Moezi;C. Millar;G. Roy;Xingsheng Wang;Scott Roy;A. Asenov