Power Optimization for SRAM and Its Scaling

Abstract

With technology scaling, there is a strong demand for smaller cell size, higher speed, and lower power in SRAMs. In addition, there are severe constraints for reliable read-and-write operations in the presence of increasing random variations that significantly degrade the noise margin. To understand these tradeoffs clearly and find a power-delay optimal solution for scaled SRAM, sequential quadratic programming is applied for optimizing 6-T SRAM for the first time. The use of analytical device models for transistor currents and formulate all the cell-operation requirements as constraints in an optimization problem. Our results suggest that, for optimal SRAM cell design, neither the supply voltage (V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dd</sub> ) nor the gate length (L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g</sub> ) scales, due to the need for an adequate noise margin amid leakage and threshold variability and relatively low dynamic activity of SRAM. This is true even with technology scaling. The cell area continues to scale despite the nonscaling gate length (L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">g</sub> ) with only a 7% area overhead at the 22-nm technology node as compared to simple scaling, at which point a 3-D structure is needed to continue the area-scaling trend. The suppression of gate leakage helps to reduce the power in ultralow-power SRAM, where subthreshold leakage is minimized at the cost of increase in cell area