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Impact of Random Dopant Fluctuations on the Timing Characteristics of Flip-Flops

机译:随机掺杂波动对触发器时序特性的影响

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In this work, we have analyzed the effects of variability, due to random dopant fluctuation (RDF), on the timing characteristics of flip-flops for the future technology generations of 25, 18, and 13 nm, based on extensive Monte Carlo simulations. The results show that RDF has a significant impact on all of the timing parameters and that these parameters do not follow a normal distribution; in particular, they are skewed and exhibit a large tail. Moreover, the dispersion and skewness of the timing parameters increase with technology scaling. The study of the exact shape of these distributions, especially in the tail section, is of fundamental importance in the design and modeling of high-performance, reliable, and economically feasible circuits. In this paper, the distribution tails are estimated based on simulation data, with the aid of statistical nonparametric probability density functions, and it has been found that timing distributions can better be represented by certain nonparametric distributions, in particular Pearson and Johnson systems. The use of these representations during the statistical static timing analysis will provide more accurate results as compared with the normal approximation of distributions and will eventually reduce the probability of yield loss.
机译:在这项工作中,我们基于广泛的蒙特卡洛模拟,分析了由于随机掺杂物波动(RDF)引起的可变性对25、18和13 nm下一代技术触发器的时序特性的影响。结果表明,RDF对所有时序参数均具有显着影响,并且这些参数不遵循正态分布。特别是它们偏斜并且尾巴很大。此外,时序参数的离散度和偏度随着技术的扩展而增加。研究这些分布的确切形状,特别是在尾部,对高性能,可靠且经济可行的电路的设计和建模至关重要。在本文中,借助统计数据,借助统计非参数概率密度函数对分布尾部进行了估计,并且发现时序分布可以更好地由某些非参数分布表示,特别是Pearson和Johnson系统。在统计静态时序分析中使用这些表示形式,与分布的正态近似相比将提供更准确的结果,并最终降低产量损失的可能性。

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