Physical Modeling of Bitcell Stability in Subthreshold SRAMs for Leakage–Area Optimization under PVT Variations

Abstract

Subthreshold SRAM design is crucial for addressing the memory bottleneck in energy constrained applications. While statistical optimization can be applied based on Monte-Carlo (MC) simulation, exploration of bitcell design space is time consuming. This paper presents a framework for model-based design and optimization of subthreshold SRAM bitcells under random PVT variations. By incorporating key design and process features, a physical model of bitcell static noise margin (SNM) has been derived analytically. It captures intra-die SNM variations by the combination of a folded-normal distribution and a non-central chi-squared distribution. Validations with MC simulation show its accuracy of modeling SNM distributions down to 25mV beyond 6-sigma for typical bitcells in 28nm. Model-based tuning of subthreshold SRAM bitcells is investigated for design tradeoff between leakage, area and stability. When targeting a specific SNM constraint, we show that an optimal standby voltage exists which offers minimum bitcell leakage power – any deviation above or below increases the power consumption. When targeting a specific standby voltage, our design flow identifies bitcell instances of 12× less leakage power or 3× reductions in area as compared to the minimum-length design.