Advanced simulation of statistical variability and reliability in nano CMOS transistors
Advanced simulation of statistical variability and reliability in nano CMOS transistors
复制标题
纳米 CMOS 晶体管统计变异性和可靠性的高级模拟
DOI：
--
复制
发表时间：
2008
期刊：
影响因子：
--
通讯作者：
U. Kovac
中科院分区：
文献类型：
--
作者：
A. Asenov;S. Roy;R.A. Brown;G. Roy;C. Alexander;C. Riddet;C. Millar;B. Cheng;A. Martinez;N. Seoane;D. Reid;M. Bukhori;X. Wang;U. Kovac
在45纳米技术时代，不断增加的CMOS器件变化性已成为半导体制造和设计行业面临的最尖锐的问题之一。最有问题的是，在已经具有分子尺寸特征的晶体管中，电荷的离散性和物质的粒度引入了统计上的可变性[i]。芯片上相邻的两个具有完全相同的几何形状和应变分布的晶体管可能具有来自宽统计分布的两端的特性。结合统计可变性[II]，负偏置温度不稳定性(NBTI)和/或热载流子退化可能导致严重的统计可靠性问题。它已经深刻地影响了SRAM的设计，在逻辑电路中会导致统计时序问题，并越来越多地导致硬数字故障。在这两种情况下，统计可变性限制了电源电压的缩放，增加了功耗问题[III]。在这篇受邀的论文中，我们描述了使用漂移扩散(DD)、蒙特卡罗(MC)和量子输运(QT)模拟技术对统计可变性进行预测物理模拟的最新进展。
Increasing CMOS device variability has become one of the most acute problems facing the semiconductor manufacturing and design industries at, and beyond, the 45 nm technology generation. Most problematic of all is the statistical variability introduced by the discreteness of charge and granularity of matter in transistors with features already of molecular dimensions [i]. Two transistors next to each other on the chip with exactly the same geometries and strain distributions may have characteristics from each end of a wide statistical distribution. In conjunction with statistical variability [ii], negative bias temperature instability (NBTI) and/or hot carrier degradation can result in acute statistical reliability problems. It already profoundly affects SRAM design, and in logic circuits causes statistical timing problems and is increasingly leading to hard digital faults. In both cases, statistical variability restricts supply voltage scaling, adding to power dissipation problems [iii]. In this invited paper we describe recent advances in predictive physical simulation of statistical variability using drift diffusion (DD), Monte Carlo (MC) and quantum transport (QT) simulation techniques.