Statistical cells timing metrics characterization

To characterize statistical moments of cell delays and slopes, the standard method is Monte Carlo (MC) method. However, this method suffers from very high computational cost. In this paper, we propose a technique to quickly and accurately estimate Standard Deviation (SD) of standard cell delays and slopes. The proposed technique is based on the identification, performed with a reduced set of MC simulations, of delay and output slope SD functions that take input slope, output load and supply voltage as input arguments. These identified functions are then used to estimate SDs of delays and slopes at different operating conditions (input slope, output load, supply voltage). This proposed method provides at least 76% of CPU gains, with respect to MC, while keeping high accuracy.