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

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 <inline-formula> <tex-math notation="LaTeX">$5 \times 4$ </tex-math></inline-formula> 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 <inline-formula> <tex-math notation="LaTeX">$5 \times 4$ </tex-math></inline-formula> C3PU consumed energy of 66.4 fJ/MAC at 0.3 V voltage supply with an error of 5.7&#x0025;. The proposed unit achieves lower energy and occupies a smaller area by <inline-formula> <tex-math notation="LaTeX">$3.4\times $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$3.6\times $ </tex-math></inline-formula>, respectively, with similar error value when compared to a digital-based <inline-formula> <tex-math notation="LaTeX">$8 \times 4$ </tex-math></inline-formula>-bit fixed point MAC unit. The C3PU has been utilized through an iris flower classification utilizing an artificial neural network which achieved a 90&#x0025; classification accuracy compared to ideal accuracy of 96.67&#x0025; using MATLAB.

Abstract licence: CC BY-NC-ND

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