An Efficient Bayesian Yield Estimation Method for High Dimensional and High Sigma SRAM Circuits

Jinyuan Zhai, Changhao Yan, Sheng-Guo Wang, Dian Zhou
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引用次数: 5

Abstract

With increasing dimension of variation space and computational intensive circuit simulation, accurate and fast yield estimation of realistic SRAM chip remains a significant and complicated challenge. In this paper, du Experiment results show that the proposed method has an almost constant time complexity as the dimension increases, and gains 6× speedup over the state-of-the- art method in the 485D cases.
高维高西格玛SRAM电路的高效贝叶斯良率估计方法
随着变化空间维度的增加和计算密集型电路仿真,准确快速地估计实际SRAM芯片的成品率仍然是一个重大而复杂的挑战。实验结果表明,随着维数的增加,该方法具有几乎恒定的时间复杂度,并且在485D情况下,该方法的速度比目前的方法提高了6倍。
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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