Application-Specific SRAM Design Using Output Prediction to Reduce Bit-Line Switching Activity and Statistically Gated Sense Amplifiers for Up to 1.9$\times$ Lower Energy/Access

This paper presents an application-specific SRAM design targeted towards applications with highly correlated data (e.g., video and imaging applications). A prediction-based reduced bit-line switching activity scheme is proposed to reduce switching activity on the bit-lines based on the proposed bit-cell and array structure. A statistically gated sense-amplifier approach is used to exploit signal statistics on the bit-lines to reduce energy consumption of the sensing network. These techniques provide up to 1.9 × lower energy/access when compared with an 8T SRAM. These savings are in addition to the savings that are achieved through voltage scaling and demonstrate the advantages of an application-specific SRAM design.