Statistical BSIM3 model parameter extraction and fast/slow model parameter determination for high speed SRAM parametric yield estimation

To achieve high yield without degrading performance, it is important to consider process variations during circuit designing. There is also a strong need of good model parameters for fast/slow cases, which represent the performance variations. We have developed a statistical model parameter extraction method, to extract sets of process related BSIM3 parameters from in-line measurement data such as drain saturation current and threshold voltage. This extraction method is based on our pre-silicon parameter generation methodology, which makes the model parameter predictable when changing some parameters related to the process. We have also proposed a method to determine the fast/slow model parameters using the statistical model parameters, for circuit designing. We have applied this method to a 0.20 μm process SRAM test chip, and have obtained good results comparing to measurement, thus making it possible to estimate parametric yield by simulation