Architecture-Aware Analytical Yield Model for Read Access in Static Random Access Memory

We prove analytically that the yield of static random access memory (SRAM) is intrinsically a function of its architecture owing to the correlation among cell failures. In addition, architecture-aware analytical yield models are proposed for read access. The yield results using the proposed models show that the most dominant factor determining yield is the variation in the voltage difference between bitlines due to the cell leakage current variation according to the SRAM architecture. The models also show the possibility that the most dominant factor determining the yield can change with the relative ratios among the amounts of changes in the correlation, recovery sample space, distributions of the sense amplifier enable time, voltage difference between bitlines, as well as sense amplifier offset voltage, memory capacity, and redundancy scheme. The proposed yield models show that combined row and column redundancy ensures the highest yield, whereas column redundancy is the most efficient.