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This paper presents a novel cross-coupling capacitor processing unit (C3PU)that supports analog-mixed signal in memory computing to performmultiply-and-accumulate (MAC) operations. The C3PU consists of a capacitiveunit, a CMOS transistor, and a voltage-to-time converter (VTC). The capacitiveunit serves as a computational element that holds the multiplier operand andperforms multiplication once the multiplicand is applied at the terminal. Themultiplicand is the input voltage that is converted to a pulse width signalusing a low power VTC. The transistor transfers this multiplication where avoltage level is generated. A demonstrator of 5x4 C3PU array that is capable ofimplementing 4 MAC units is presented. The design has been verified using MonteCarlo simulation in 65 nm technology. The 5x4 C3PU consumed energy of 66.4fJ/MAC at 0.3 V voltage supply with an error of 5.7%. The proposed unitachieves lower energy and occupies a smaller area by 3.4x and 3.6x,respectively, with similar error value when compared to a digital-based 8x4-bitfixed point MAC unit. The C3PU has been utilized through an iris fowerclassification utilizing an artificial neural network which achieved a 90%classification accuracy compared to ideal accuracy of 96.67% using MATLAB.

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