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Large-scale statistical performance modeling of analog and mixed-signal circuits

Publication ,  Conference
Li, X; Zhang, W; Wang, F
Published in: Proceedings of the Custom Integrated Circuits Conference
November 26, 2012

The aggressive scaling of IC technology results in large-scale performance variations that cannot be efficiently captured by traditional modeling techniques. This paper presents the recent development of statistical performance modeling and its important applications. In particular, we focus on two core techniques, sparse regression (SR) and Bayesian model fusion (BMF), that facilitate large-scale performance modeling with low computational cost. The basic ideas of SR and BMF are first explained and then their efficacy is compared to other traditional modeling approaches by using several analog and mixed-signal circuit examples. © 2012 IEEE.

Duke Scholars

Published In

Proceedings of the Custom Integrated Circuits Conference

DOI

ISSN

0886-5930

Publication Date

November 26, 2012
 

Citation

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Li, X., Zhang, W., & Wang, F. (2012). Large-scale statistical performance modeling of analog and mixed-signal circuits. In Proceedings of the Custom Integrated Circuits Conference. https://doi.org/10.1109/CICC.2012.6330570
Li, X., W. Zhang, and F. Wang. “Large-scale statistical performance modeling of analog and mixed-signal circuits.” In Proceedings of the Custom Integrated Circuits Conference, 2012. https://doi.org/10.1109/CICC.2012.6330570.
Li X, Zhang W, Wang F. Large-scale statistical performance modeling of analog and mixed-signal circuits. In: Proceedings of the Custom Integrated Circuits Conference. 2012.
Li, X., et al. “Large-scale statistical performance modeling of analog and mixed-signal circuits.” Proceedings of the Custom Integrated Circuits Conference, 2012. Scopus, doi:10.1109/CICC.2012.6330570.
Li X, Zhang W, Wang F. Large-scale statistical performance modeling of analog and mixed-signal circuits. Proceedings of the Custom Integrated Circuits Conference. 2012.

Published In

Proceedings of the Custom Integrated Circuits Conference

DOI

ISSN

0886-5930

Publication Date

November 26, 2012