A reliable non‐volatile in‐memory computing associative memory based on spintronic neurons and synapses

Abstract

Abstract This article introduces an innovative non‐volatile associative memory (AM) that leverages spintronic synapses, employing magnetic tunnel junctions (MTJ) in conjunction with neurons constructed using carbon nanotube field‐effect transistors (CNTFETs). Our proposed design represents a significant advancement in area optimization and outperforms prior designs. We adopt MTJ‐based spintronic devices due to their remarkable attributes, including dependable reconfigurability and nonvolatility. Simultaneously, CNTFETs effectively address the longstanding limitations traditionally associated with MOSFETs. In this work, our proposed design undergoes rigorous simulations that account for process variations. The results demonstrate that our AM system closely approximates its ideal mathematical model, even with significant process variations. Furthermore, we investigate the impact of Tunnel Magnetoresistance (TMR) on the performance of our proposed AM system. Our investigations reveal that, even with a TMR as low as 100%, our design matches and often surpasses the performance of its counterparts operating with a TMR of 300%. This achievement holds profound significance from a fabrication standpoint, as fabricating MTJs with high TMR values can be intricate and costly. Overall, our novel AM system represents a significant breakthrough in emerging technologies, harnessing the unique strengths of spintronic synapses and advanced carbon nanotube transistors while robustly addressing challenges in performance and variability.

Keywords

• associative memory
• emerging technologies
• in‐memory computing
• neural network
• nonvolatility
• spintronic synapse and neuron