Sensitivity Importance Sampling Yield Analysis and Optimization for High Sigma Failure Rate Estimation
Wenfei Hu, Zhikai Wang, Sen Yin, Zuochang Ye, Yan Wang
Abstract
The impact of process variation to advanced integrated circuits has become increasingly significant. Traditional sampling based yield analysis and optimization always require large amount of expensive simulations. This paper proposes an All Sensitivity Adversarial Importance Sampling (ASAIS) yield optimization method, which avoids samplings in outer optimization based on sensitivity. Moreover, Fast Sensitivity Importance Sampling (FSIS) yield analysis method is adopted as inner yield analysis to eliminate the sampling using transient sensitivity analysis. Experiments on SRAM show ASAIS generates more than 90X speedup of the entire yield optimization process, while FSIS speedup 3X-I5X over existing methods.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Related papers
- An efficient yield optimization method for analog circuits via gaussian process classification and varying-sigma samplingXiaodong Wang, Changhao Yan, Fan Yang, Dian Zhou et al.DAC 2022 · 6 citations
- An Efficient and Robust Yield Optimization Method for High-dimensional SRAM CircuitsXiaodong Wang, Tianchen Gu, Changhao Yan, Xiulong Wu et al.DAC 2020 · 10 citations
- Adjoint Transient Sensitivity Analysis for Objective Functions Associated to Many Time PointsWenfei Hu, Zuochang Ye, Yan WangDAC 2020 · 8 citations
- Accuracy Is Not Always We Need: Precision-Aware Bayesian Yield OptimizationJing Kou, Zidong Chen, Liang Zhang, Haiyan Qin et al.DAC 2025
- Efficient bayesian yield analysis and optimization with active learningShuo Yin, Xiang Jin, Linxu Shi, Kang Wang et al.DAC 2022 · 17 citations
