Leveraging sensitivity analysis for fast, accurate estimation of SRAM dynamic write VMIN

Circuit reliability in the presence of variability is a major concern for SRAM designers. With the size of memory ever increasing, Monte Carlo simulations have become too time consuming for margining and yield evaluation. In addition, dynamic write-ability metrics have an advantage over static metrics because they take into account timing constraints. However, these metrics are much more expensive in terms of runtime. Statistical blockade is one method that reduces the number of simulations by filtering out non-tail samples, however the total number of simulations required still remains relatively large. In this paper, we present a method that uses sensitivity analysis to provide a total speedup of ~112X compared with recursive statistical blockade with only a 3% average loss in accuracy. In addition, we show how this method can be used to calculate dynamic VMIN and to evaluate several write assist methods.