The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Applied Numerical Mathematics - Special issue on numerical grid generation-technologies for advanced simulations
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Modeling and Testing of SRAM for New Failure Mechanisms Due to Process Variations in Nanoscale CMOS
VTS '05 Proceedings of the 23rd IEEE Symposium on VLSI Test
Statistical analysis of SRAM cell stability
Proceedings of the 43rd annual Design Automation Conference
Proceedings of the conference on Design, automation and test in Europe
SRAM parametric failure analysis
Proceedings of the 46th Annual Design Automation Conference
Yield estimation via multi-cones
Proceedings of the 49th Annual Design Automation Conference
Proceedings of the International Conference on Computer-Aided Design
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Reliability analysis of SRAM core-cells requires statistical methods with very high accuracy to cope with very low failure probabilities. Although new statistical methods have been recently proposed, to the best of our knowledge, there is no method able to evaluate the joint failure probability (the probability that at least one failure mechanism occurs) of an SRAM core-cell with enough accuracy in a reasonable time. We propose a statistical simulation method based on the analytical integration of the multivariate Gaussian distribution function.