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Power and energy minimization is a critical concern for the battery life, reliability, and yield of many minimum-sized SRAMs. In this paper, we extend our previously proposed hybrid analytical-empirical model for minimizing and predicting the delay and delay variability of SRAMs, VAR-TX, to a new enhanced version, exVAR-TX, to minimize and predict the power/energy and power/energy variability of a 16-nm 6T-SRAM under the influence of the three major types of variations: Fabrication, Operation, and Implementation. Using exVAR-TX for architectural optimization [exhaustively computing and comparing the range of feasible architectures subject to interdie (die-to-die/D2D) and intradie (within-die/WID) process and operation variations (PVT), electromigration (EM), negative bias temperature instability (NBTI), and soft-errors, among others] on top of deploying the most recent state of the art effective mitigation techniques we show that energy and energy-delay-product (EDP) of 64KB 16-nm 6T-SRAM could be reduced by ~12.5X and ~33%, respectively, as compared to the existing conventional designs.

Power/Energy Minimization Techniques for Variability-Aware High-Performance 16-nm 6T-SRAM