Modulation of switching dynamics in magnetic tunnel junctions for low-error-rate computational random-access memory
Yang Lv, Brahmdutta Dixit, and Jian-Ping Wang

TL;DR
This paper introduces a voltage-controlled magnetic anisotropy method to improve switching reliability in magnetic tunnel junctions, significantly reducing error rates and energy consumption in CRAM systems.
Contribution
It presents a novel VCMA-based approach to modulate MTJ switching dynamics, reducing errors and energy use in CRAM for the first time.
Findings
VCMA reduces CRAM error rate by 61.43% at a specific coefficient.
Error reduction amplifies with higher TMR ratios.
VCMA decreases logic voltage and energy consumption.
Abstract
The conventional computer architecture has been facing challenges answering the ever-increasing demands from emerging applications, such as AI, for energy-efficient computation and memory hardware systems. Computational Random Access Memory (CRAM) represents a true in-memory computing paradigm that integrates logic and memory functions within the same array. At its core, CRAM relies on Magnetic Tunnel Junctions (MTJs), which serve as the foundational building blocks for implementing both memory storage and logic operations. However, a key challenge in CRAM lies in the non-ideal error rates associated with switching dynamics of MTJs, necessitating innovative approaches to reduce errors and optimize logic margins. This work proposes a novel approach of utilizing the voltage-controlled magnetic anisotropy (VCMA) to steepen the switching probability transfer curve (SPTC), thereby…
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Taxonomy
TopicsMagnetic properties of thin films · Neural Networks and Applications · Magnetic Field Sensors Techniques
