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Efficient SRAM failure rate prediction via Gibbs sampling

Publication ,  Conference
Dong, C; Li, X
Published in: Proceedings - Design Automation Conference
January 1, 2011

Statistical analysis of SRAM has emerged as a challenging issue because the failure rate of SRAM cells is extremely small. In this paper, we develop an efficient importance sampling algorithm to capture the rare failure event of SRAM cells. In particular, we adapt the Gibbs sampling technique from the statistics community to find the optimal probability distribution for importance sampling with minimum computational cost (i.e., a small number of transistor-level simulations). The proposed Gibbs sampling method applies an integrated optimization engine to adaptively explore the failure region by sampling a sequence of one-dimensional probability distributions. Several implementation issues such as one-dimensional random sampling and starting point selection are carefully studied to make the Gibbs sampling method efficient and accurate for SRAM failure rate prediction. Our experimental results of a commercial 65nm SRAM cell demonstrate that the proposed Gibbs sampling method achieves 3∼10× runtime speed-up over other state-of-the-art techniques without surrendering any accuracy. © 2011 ACM.

Duke Scholars

Published In

Proceedings - Design Automation Conference

DOI

ISSN

0738-100X

Publication Date

January 1, 2011

Start / End Page

200 / 205
 

Citation

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Dong, C., & Li, X. (2011). Efficient SRAM failure rate prediction via Gibbs sampling. In Proceedings - Design Automation Conference (pp. 200–205). https://doi.org/10.1145/2024724.2024769
Dong, C., and X. Li. “Efficient SRAM failure rate prediction via Gibbs sampling.” In Proceedings - Design Automation Conference, 200–205, 2011. https://doi.org/10.1145/2024724.2024769.
Dong C, Li X. Efficient SRAM failure rate prediction via Gibbs sampling. In: Proceedings - Design Automation Conference. 2011. p. 200–5.
Dong, C., and X. Li. “Efficient SRAM failure rate prediction via Gibbs sampling.” Proceedings - Design Automation Conference, 2011, pp. 200–05. Scopus, doi:10.1145/2024724.2024769.
Dong C, Li X. Efficient SRAM failure rate prediction via Gibbs sampling. Proceedings - Design Automation Conference. 2011. p. 200–205.

Published In

Proceedings - Design Automation Conference

DOI

ISSN

0738-100X

Publication Date

January 1, 2011

Start / End Page

200 / 205