SPICE modeling of process variation using location depth corner models
For robust designs, the influence of process variations has to be considered during circuit simulation. We propose a nonparametric statistical method to find sets of simulation parameters that cover the process spread with a minimum number of simulation runs. Process corners are determined from e-te...
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| Veröffentlicht in: | IEEE transactions on semiconductor manufacturing 2004-05, Vol.17 (2), p.201-213 |
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| container_title | IEEE transactions on semiconductor manufacturing |
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| creator | Rappitsch, G. Seebacher, E. Kocher, M. Stadlober, E. |
| description | For robust designs, the influence of process variations has to be considered during circuit simulation. We propose a nonparametric statistical method to find sets of simulation parameters that cover the process spread with a minimum number of simulation runs. Process corners are determined from e-test parameter vectors using a location depth algorithm. The e-test corner vectors are then transformed to SPICE parameter vectors by a linear mapping. A special corner extension algorithm makes the resulting simulation setup robust against moderate process shifts while preserving the underlying correlation structure. To be applicable in a production and circuit design environment, the models are integrated into an automated model generation flow for usage within a design-framework. The statistical methods are validated for analog/mixed-signal benchmark circuits. |
| doi_str_mv | 10.1109/TSM.2004.826940 |
| format | Article |
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We propose a nonparametric statistical method to find sets of simulation parameters that cover the process spread with a minimum number of simulation runs. Process corners are determined from e-test parameter vectors using a location depth algorithm. The e-test corner vectors are then transformed to SPICE parameter vectors by a linear mapping. A special corner extension algorithm makes the resulting simulation setup robust against moderate process shifts while preserving the underlying correlation structure. To be applicable in a production and circuit design environment, the models are integrated into an automated model generation flow for usage within a design-framework. 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We propose a nonparametric statistical method to find sets of simulation parameters that cover the process spread with a minimum number of simulation runs. Process corners are determined from e-test parameter vectors using a location depth algorithm. The e-test corner vectors are then transformed to SPICE parameter vectors by a linear mapping. A special corner extension algorithm makes the resulting simulation setup robust against moderate process shifts while preserving the underlying correlation structure. To be applicable in a production and circuit design environment, the models are integrated into an automated model generation flow for usage within a design-framework. The statistical methods are validated for analog/mixed-signal benchmark circuits.</description><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Circuit design</subject><subject>Circuit simulation</subject><subject>Circuit synthesis</subject><subject>Computer simulation</subject><subject>Corners</subject><subject>Electric, optical and optoelectronic circuits</subject><subject>Electronics</subject><subject>Exact sciences and technology</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Monte Carlo methods</subject><subject>Parametric statistics</subject><subject>Process design</subject><subject>Production</subject><subject>Robustness</subject><subject>Semiconductors</subject><subject>SPICE</subject><subject>Statistical analysis</subject><subject>Testing, measurement, noise and reliability</subject><subject>Theoretical study. 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| ispartof | IEEE transactions on semiconductor manufacturing, 2004-05, Vol.17 (2), p.201-213 |
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| source | IEEE Electronic Library (IEL) |
| subjects | Algorithms Applied sciences Circuit design Circuit simulation Circuit synthesis Computer simulation Corners Electric, optical and optoelectronic circuits Electronics Exact sciences and technology Mathematical analysis Mathematical models Monte Carlo methods Parametric statistics Process design Production Robustness Semiconductors SPICE Statistical analysis Testing, measurement, noise and reliability Theoretical study. Circuits analysis and design Vectors Vectors (mathematics) |
| title | SPICE modeling of process variation using location depth corner models |
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