A methodology to improve timing yield in the presence of process variations

Sreeja Raj, S. Vrudhula, Janet Roveda
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引用次数: 77

Abstract

The ability to control the variations in IC fabrication process is rapidly diminishing as feature sizes continue towards the sub-100 nm regime. As a result, there is an increasing uncertainty in the performance of CMOS circuits. Accounting for the worst case values of all parameters will result in an unacceptably low timing yield. Design for Variability, which involves designing to achieve a given level of confidence in the performance of ICs, is fast becoming an indispensable part of IC design methodology. This paper describes a method to identify certain paths in the circuit that are responsible for the spread of timing performance. The method is based on defining a disutility function of the gate and path delays, which includes both the means and variances of the delay random variables. Based on the moments of this disutility function, an algorithm is presented which selects a subset of paths (called undominated paths) as being most responsible for the variation in timing performance. Next, a statistical gate sizing algorithm is presented, which is aimed at minimizing the delay variability of the nodes in the selected paths subject to constraints on the critical path delay and the area penalty. Monte-Carlo simulations with ISCAS '85 benchmark circuits show that our statistical optimization approach results in significant improvements in timing yield over traditional deterministic sizing methods.
一种在存在工艺变化的情况下提高定时良率的方法
随着特征尺寸继续向亚100纳米方向发展,控制IC制造工艺变化的能力正在迅速减弱。因此,CMOS电路性能的不确定性越来越大。考虑所有参数的最坏情况值将导致不可接受的低时序收益。可变性设计,包括设计以实现对集成电路性能的给定置信度,正迅速成为集成电路设计方法中不可或缺的一部分。本文描述了一种识别电路中对时序性能扩散负责的某些路径的方法。该方法基于定义门和路径延迟的负效用函数,该函数包括延迟随机变量的均值和方差。基于该负效用函数的矩,提出了一种算法,该算法选择路径子集(称为非支配路径)作为对定时性能变化最负责的路径。其次,提出了一种统计门大小算法,该算法在受关键路径延迟和面积惩罚约束的情况下,使所选路径上节点的延迟可变性最小化。ISCAS’85基准电路的蒙特卡罗模拟表明,我们的统计优化方法在时序产率方面比传统的确定性尺寸方法有显著改善。
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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