Timing analysis with compact variation-aware standard cell models

A compact variation-aware timing model for a standard cell in a cell library is developed. The cell model incorporates variations in the input waveform and loading, process parameters, and the environment into the cell timing model. The cell model operates on full waveforms, which are modeled using principal component analysis (PCA). PCA enables the construction of a compact model of a set of waveforms impacted by variations in loading, process parameters, and the environment. Cell characterization involves describing with equations how waveforms are transformed by a cell as a function of the input waveforms, process parameters, and the environment. The models have been evaluated by calculating the delay of paths. The results demonstrate improved accuracy in comparison with table-based static timing analysis at comparable computational cost. Complexity of the models as a function of the number of parameters modeling variation is also discussed, and shows reduced memory requirements as the number of parameters describing variations increases.