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This paper presents an adjustment-based modeling framework for timing analysis under variability. Instead of building a complex model (such as polynomial one) directly between the circuit timing and parameter variability, we propose to build a model that adjusts an approximate variation-aware timing into an accurate one. The idea is that it is easier to build a model that adjusts an approximate estimate...
This paper presents an adjustment-based modeling framework for statistical static timing analysis (SSTA) when the dimension of parameter variability is high. Instead of building a complex model between the circuit timing and parameter variability, we build a model which adjusts an approximate variation-aware timing into an accurate one. The intuition is that it is simpler to build a model which adjusts...
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