Low Power and Compact Mixed-Mode Signal Processing Hardware using Spin-Neurons

Mrigank Sharad1,  Deliang Fan2,  Kaushik Roy2
1Purdue University, 2Purdue Univeristy


CMOS Digital signal processing hardware are power efficient but consume large area, whereas, analog processing units, based on CMOS technology are compact, but power hungry. Emerging magneto-metallic spin-torque devices like domain wall magnets can however perform analog-mode computation like summation and thresholding at ultra low voltage. Such devices can be exploited in designing spin-CMOS hybrid analog processing units that are compact as well as low power. In this work we present a mixed-mode signal processing scheme employing “domain wall neurons” that involves energy efficient analog-mode computation upon digital data. Simulation results for 8-bit, 16-tap FIR filter show that such a design can achieve 10x lower power consumption and 16x lower area as compared to an optimized digital CMOS design at the same technology node. In such a design area saving can be traded off for enhanced power savings, depending upon the target application.