C3PU: Cross-Coupling Capacitor Processing Unit Using Analog-Mixed Signal for AI Inference

Abstract

This paper presents a novel cross-coupling capacitor processing unit (C3PU) that supports analog-mixed signal in-memory computing to perform multiply-and-accumulate (MAC) operations. The C3PU consists of a capacitive unit, a CMOS transistor, and a voltage-to-time converter (VTC). The capacitive unit serves as a computational element that holds the multiplier operand and performs multiplication once the multiplicand is applied at the terminal. The multiplicand is the input voltage that is converted to a pulse width signal using a low power VTC. The transistor transfers this multiplication where a voltage level is generated. A demonstrator of 5×4 C3PU array that is capable of implementing 4 MAC units is presented. The design has been verified using Monte Carlo simulation in 65 nm technology. The 5×4 C3PU consumed energy of 66.4 fJ/MAC at 0.3 V voltage supply with an error of 5.7%. The proposed unit achieves lower energy and occupies a smaller area by 3.4× and 3.6× , respectively, with similar error value when compared to a digital-based 8×4 -bit fixed point MAC unit. The C3PU has been utilized through an iris flower classification utilizing an artificial neural network which achieved a 90% classification accuracy compared to ideal accuracy of 96.67% using MATLAB.