Efficient modeling of spatial correlations for parameterized statistical static timing analysis

This paper presents an efficient method to model spatial correlations in the context of parameterized statistical static timing analysis (SSTA). Multiple spatially-correlated process parameters with different spatial properties can be handled by this method simultaneously and efficiently. Experiment results with industrial circuits show that the proposed approach is significantly more efficient than the existing principle component analysis approach without loosing accuracy.