SRAM Bit-line Swings Optimization using Generalized Waterfilling

We propose an information-theoretic approach to optimize non-uniform bit-line swings for static random access memories (SRAMs). We formulate convex optimization problems whose objectives are to minimize energy (for low-power SRAMs), maximize speed (for high-speed SRAMs), and minimize energy-delay product for a given constraint on mean squared error of retrieved words. We show that these optimization problems can be interpreted as generalized water-filling including classical waterfilling, ground-flattening and water-filling, and sand-pouring and water-filling, respectively. Numerical results show that energy-optimal swing assignment reduces energy consumption by half at a peak signal-to-noise ratio of 30dB for an 8-bit accessed word.