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ASPDAC
2015
ACM

Fast statistical analysis of rare failure events for memory circuits in high-dimensional variation space

4 years 7 months ago
Fast statistical analysis of rare failure events for memory circuits in high-dimensional variation space
- Accurately estimating the rare failure rates for nanoscale memory circuits is a challenging task, especially when the variation space is high-dimensional. In this paper, we summarize two novel techniques to address this technical challenge. First, we describe a subset simulation (SUS) technique to estimate the rare failure rates for continuous performance metrics. The key idea of SUS is to express the rare failure probability of a given circuit as the product of several large conditional probabilities by introducing a number of intermediate failure events. These conditional probabilities can be efficiently estimated with a set of Markov chain Monte Carlo samples generated by a modified Metropolis algorithm. Second, to efficiently estimate the rare failure rates for discrete performance metrics, scaled-sigma sampling (SSS) can be used. SSS aims to generate random samples from a distorted probability distribution for which the standard deviation (i.e., sigma) is scaled up. Next, the fa...
Shupeng Sun, Xin Li 0001
Added 16 Apr 2016
Updated 16 Apr 2016
Type Journal
Year 2015
Where ASPDAC
Authors Shupeng Sun, Xin Li 0001
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