Correlation-aware statistical timing analysis with non-gaussian delay distributions
Proceedings of the 42nd annual Design Automation Conference
A new statistical max operation for propagating skewness in statistical timing analysis
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
VLSID '07 Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems
Statistical timing analysis under spatial correlations
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
First-Order Incremental Block-Based Statistical Timing Analysis
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Asymptotic Probability Extraction for Nonnormal Performance Distributions
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Statistical Timing Analysis: From Basic Principles to State of the Art
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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This paper introduces a Gaussian mixture model to represent delay and slew distributions in the statistical static timing analysis, and proposes algorithms for propagating them on a given circuit graph. The Gaussian mixture model can represent a non-Gaussian distribution due to the statistical Max operation properly, and any correlation efficiently, since it consists of plural Gaussian distributions. Therefore, not only topological correlations caused by re-convergent paths but also the correlation between each element and the critical delay, which is useful for circuit optimization, are calculated easily. The propagated slews are used to compute delay distributions of circuit elements dynamically so as to improve the accuracy. The proposed Gaussian mixture model is evaluated by comparing with Monte Carlo simulation, and the results show its effectiveness.