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Efficient Parametric Yield Estimation Over Multiple Process Corners via Bayesian Inference Based on Bernoulli Distribution.
- Source :
-
IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems . Sep2020, Vol. 39 Issue 10, p3144-3148. 5p. - Publication Year :
- 2020
-
Abstract
- Parametric yield estimation over multiple process corners plays an important role in robust circuit design. In this article, we propose a novel Bayesian inference method based on Bernoulli distribution (BI-BD) to efficiently estimate the multicorner yields for binary output circuit. The key idea is to encode the circuit performance correlation among different corners as our prior knowledge. Consequently, after combining a few simulation samples, the yield estimation over all corners can be calibrated via Bayesian inference based on iterative reweighted least squares (IRLS) and expectation maximization (EM). A circuit example demonstrates that the proposed BI-BD method can achieve up to 2.0 × cost reduction over the conventional Monte Carlo method without surrendering any accuracy. [ABSTRACT FROM AUTHOR]
- Subjects :
- *BINOMIAL distribution
*PROBABILITY density function
*COST control
Subjects
Details
- Language :
- English
- ISSN :
- 02780070
- Volume :
- 39
- Issue :
- 10
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems
- Publication Type :
- Academic Journal
- Accession number :
- 146079977
- Full Text :
- https://doi.org/10.1109/TCAD.2019.2940682