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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DOI：
10.1145/2966986.2967029
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发表时间：
2016-11
期刊：
影响因子：
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通讯作者：
Handi Yu;Jun Tao;Changhai Liao;Yangfeng Su;Dian Zhou;Xuan Zeng;Xin Li
中科院分区：
文献类型：
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作者：
Handi Yu;Jun Tao;Changhai Liao;Yangfeng Su;Dian Zhou;Xuan Zeng;Xin Li
本文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，可靠地估计涉及超过20,000个独立随机变量的相关罕见故障事件的总体故障率。
In this paper, 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 Hierarchal 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 estimates the overall failure rate of correlated rare failure events involving more than 20,000 independent random variables.