统计时序分析中过渡时间变异性的考虑

T. Kouno, H. Onodera
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引用次数: 10

摘要

本文讨论了统计静态时序分析(SSTA)中过渡时间变异性的处理方法。在SSTA中,信号到达时间被视为一个统计变量。在实际应用中,信号的过渡时间也会因工艺变化而产生波动,需要考虑这种影响。此外,在多个扇入门中,存在与每个输入相关的多个转换时间变量。需要对多种可能性进行有效处理。本文首先讨论了过渡时变率对延迟分布的影响。提出了一种由时延变异性推导过渡时间变异性的方法,并利用线性化模型考虑了过渡时间变异性的影响。实验表明,该方法的误差小于0.2%,而忽略过渡时可变性的影响,误差增大到4%。对于多个扇入门,我们通过对多个转换时间变量进行加权平均,将多个转换时间变量转化为单个变量。在我们的实验中,转换的误差在1%左右。在不改变现有SSTA方法框架的情况下,提出的过渡时间变率处理方法提高了SSTA的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Consideration of Transition-Time Variability in Statistical Timing Analysis
This paper discusses the treatment of the transition-time variability in statistical static timing analysis (SSTA). In SSTA, the signal arrival time is treated as a statistical variable. In reality, the signal transition time also fluctuates due to process variations, which effect should be taken into account. Also, in a multiple fan-in gate, there exist multiple transition-time variabilities associated with each input. Effective treatment of the multiple possibilities is required. This paper first discusses the effect of transition-time variability on the delay distribution. A method is proposed that derives the variability of transition time from the delay variability and considers the effect of transition-time variability using a linearized model. An experiment shows that the error of the method is less than 0.2% whereas the error grows to 4% if we neglect the effect of transition-time variability. For multiple fan-in gates, we convert multiple transition time variabilities into a single variability by taking a weighted average of the variabilities. The error of the conversion is around 1% in our experiments. The proposed treatments of the transition-time variability improve the accuracy of SSTA without changing the framework of existing SSTA methods.
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