Efficient Statistical Analysis for Correlated Rare Failure Events via Asymptotic Probability Approximation

Efficient Statistical Analysis for Correlated Rare Failure Events via Asymptotic Probability Approximation
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通过渐近概率近似对相关罕见故障事件进行有效统计分析

DOI:
10.1109/tcad.2020.2979804
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发表时间:
2020-12
影响因子:
2.9
通讯作者:
Xin Li
Xin Li
中科院分区:
计算机科学3区
文献类型:
--
作者:
Fulin Peng;H;i Yu;Jun Tao;Yangfeng Su;Dian Zhou;Xuan Zeng;Xin Li

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在这篇文章中,提出了一种新的渐近概率近似(阿帕)方法来估计包含大量复制单元的复杂电路(例如,SRAM位单元)。阿帕的核心思想是基于一组仔细定义的故障事件来近似整体电路故障率。一个有效的分层子集模拟(H-SUS)的方法来计算上述故障率和统计方法进一步提出了估计阿帕的置信区间。我们的数值实验表明,阿帕可以准确和可靠地估计相关的罕见故障事件涉及超过20 000个独立的随机变量的总体故障率。
In this article, a novel asymptotic probability approximation (APA) method is proposed to estimate the overall rare probability of correlated failure events for complex circuits containing a large number of replicated cells (e.g., SRAM bit-cells). The key idea of APA is to approximate the overall circuit failure rate based on a set of carefully defined failure events. An efficient hierarchical subset simulation (H-SUS) method is developed to calculate the aforementioned failure rate and a statistical methodology is further proposed to estimate the confidence interval of APA. Our numerical experiments demonstrate that APA can accurately and reliably estimate the overall failure rate of correlated rare failure events involving more than 20 000 independent random variables.
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