Hierarchical statistical characterization of mixed-signal circuits using behavioral modeling
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Response Surface Methodology: Process and Product in Optimization Using Designed Experiments
Optimization of Integrated Spiral Inductors Using Sequential Quadratic Programming
Proceedings of the conference on Design, automation and test in Europe - Volume 1
Statistical Timing Analysis for Intra-Die Process Variations with Spatial Correlations
Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
Analysis of full-wave conductor system impedance over substrate using novel integration techniques
Proceedings of the 42nd annual Design Automation Conference
Asymptotic probability extraction for non-normal distributions of circuit performance
Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
Stochastic analysis of interconnect performance in the presence of process variations
Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
Non-gaussian statistical interconnect timing analysis
Proceedings of the conference on Design, automation and test in Europe: Proceedings
Variability-Aware Multilevel Integrated Spiral Inductor Synthesis
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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As technologies continue to shrink in size, modeling the effect of process variations on circuit performance is assuming profound significance. Process variations affect the on-chip performance of both active and passive components. This necessitates the inclusion of the effect of these variations on distributed interconnect structures in modeling overall circuit performance. In this work, first it is shown through field-solver simulations that larger process variations lead to non-Gaussian PDFs (Probability Density Functions) for the circuit equivalent parameters of distributed passives. Next, a method for accurate statistical analysis of coupled circuit-EM (Electromagnetic) systems without computing the equivalent circuit parameters of EM-modeled objects is demonstrated. This method also obviates the need to generate random variables representing the equivalent circuit parameters, from distributions which are correlated, non-Gaussian and non-closed-form. The proposed approach relies on application of the Response Surface (RS) methodology to the y-parameters of both the circuit and the distributed structures independently and expressing the eventual performance measures through a suitable combination of the y-parameters. The eventual performance measures are expressed through a hierarchical approach in terms of the underlying Gaussian random variables representing the process parameters. A rapid Response Surface Monte Carlo (RSMC) analysis on these derived response surfaces furnishes the PDFs and can also be used to predict the yield based on different qualifying criteria and objective functions.