Nonvolatile Associative Memory Design Based on Spintronic Synapses and CNTFET Neurons

Abstract

Many advances have been made in developing bio-inspired intelligent systems for performing important tasks like pattern association, which cannot be performed effectively by the conventional computer architectures. This paper presents a novel nonvolatile associative memory based on spintronic synapses utilizing magnetic tunnel junction (MTJ) and carbon nanotube field-effect transistors (CNTFET)-based neurons. MTJs introduce fascinating features like reconfigurability, nonvolatility, and high endurance to the design, while CNTFETs compensate for the flaws of the conventional transistors in deep nanoscale nodes. The comprehensive simulations validate the functionality of the proposed synaptic cell, and neuron, even in the presence of major process variations. The application of the proposed synaptic cell and neuron in the hardware realization of multi-associative memories is also investigated. The simulation results indicate that the proposed hardware-based multi-associative memory performs similar to its ideal software-based counterpart with a less than 3 percent difference in the successful recall rate. It also noteworthy that since the input and output of the proposed design are logical ‘0’ and ‘1’, the proposed design does not need any extra component for voltage conversion.