SRAM dynamic stability estimation using MPFP and its applications

In this paper, an accurate approach for estimating the dynamic stability of static random access memory (SRAM) is proposed. The conventional methods of SRAM stability estimation suffer from two major drawbacks: (1) using static failure criteria, such as SNM, which does not capture the transient and dynamic behavior of SRAM operation, and (2) using quasi-Monte-Carlo simulation, which approximates the failure distribution, resulting in large errors at the tails where the desired failure probabilities exist. These drawbacks are eliminated by employing accurate simulation-based dynamic failure criteria along with a new distribution-independent, Most-probable-failure-point search technique for accurate probability calculation. Compared to previously published techniques, the proposed dynamic stability technique offers orders of magnitude improvement in accuracy. Furthermore, the proposed dynamic stability technique enables the correct evaluation of stability in real operation conditions and for different dynamic circuit techniques, such as dynamic write back, where the conventional methods are not applicable.