A Capacitive Computing-In-Memory Circuit With Low Input Loading SRAM Bitcell and Adjustable ADC Input Range

Abstract

We present a 9T1C SRAM cell-based capacitive computing-in-memory circuit for neural network computation. The proposed design improves tolerance against process variation with a smaller cell area compared to previous capacitive SRAM CIM designs while inheriting the advantage of capacitive SRAM CIM hardware such as the linearity in multiply-accumulate (MAC) results and suppression of the static readout current. We also demonstrate a compact and low-power ADC for CIM readout, which improves the energy efficiency significantly. Finally, we demonstrate a programmable on-chip ADC reference voltage generator circuit for adjusting the ADC input range using bitcell replica arrays. The proposed circuit reduces the ADC bit-resolution requirement by considering the distribution of MAC results, and also helps to address the effect of the parasitic bitline capacitance. Measurement results show that a 128×128 macro fabricated in a 28 nm CMOS achieves 1519.5 TOPS/W at 0.7 V.