Field-free spin–orbit torque devices for logic and neural network applications

Robust field-free spin–orbit torque (SOT) switching plays an essential role in realizing practical SOT-based magnetic memories and logic devices. Leveraging the strong interlayer Dzyaloshinskii–Moriya interaction, field-free SOT switching is achieved with a threshold switching current density of 5.4 × 1010 A/m2. By exploiting the advantage of separated read–write paths, we demonstrate fundamental logic operations such as AND, OR, and NOT in a dual-channel SOT Hall bar device. We further explore the application of a digital SOT magnetic random access memory (MRAM) design in addressing the issue of the low ON/OFF ratio of the conventional spin-transfer torque MRAM, highlighting its potential for neural network applications. Our simulation results show that using digital SOT MRAM can achieve a classification accuracy of 92.2% for the MNIST dataset, outperforms the analog SOT MRAM case (<10%), and presents remarkable improvements in power and time efficiencies compared to the SRAM case. These findings establish digital SOT MRAM as a frontrunner for edge artificial intelligence applications and offline inference.

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Publication Details

Journal
APL Machine Learning
Published
2024-11-21
DOI
https://doi.org/10.1063/5.0226135
Citations
3
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.63

Funders

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article

Field-free spin–orbit torque devices for logic and neural network applications

Chi‐Feng Pai, Po‐Chuan Wang, Chun‐Yi Lin, Jui-Yu Hsieh et al.
3 citations
APL Machine Learning
Advanced Memory and Neural Computing
0.63
article

Field-free spin–orbit torque devices for logic and neural network applications

Chi‐Feng Pai, Po‐Chuan Wang, Chun‐Yi Lin, Jui-Yu Hsieh, Chia-Chin Tsai
article en
3 citations

Abstract

Robust field-free spin–orbit torque (SOT) switching plays an essential role in realizing practical SOT-based magnetic memories and logic devices. Leveraging the strong interlayer Dzyaloshinskii–Moriya interaction, field-free SOT switching is achieved with a threshold switching current density of 5.4 × 1010 A/m2. By exploiting the advantage of separated read–write paths, we demonstrate fundamental logic operations such as AND, OR, and NOT in a dual-channel SOT Hall bar device. We further explore the application of a digital SOT magnetic random access memory (MRAM) design in addressing the issue of the low ON/OFF ratio of the conventional spin-transfer torque MRAM, highlighting its potential for neural network applications. Our simulation results show that using digital SOT MRAM can achieve a classification accuracy of 92.2% for the MNIST dataset, outperforms the analog SOT MRAM case (<10%), and presents remarkable improvements in power and time efficiencies compared to the SRAM case. These findings establish digital SOT MRAM as a frontrunner for edge artificial intelligence applications and offline inference.

APL Machine LearningVol. 2(4)
National Taiwan University (TW)
National Taiwan University, National Science and Technology Council
Openalex Percentile: Top 30%
Advanced Memory and Neural Computing
0.63
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Field-free spin–orbit torque devices for logic and neural network applications — Chi‐Feng Pai, Po‐Chuan Wang, et al. · APL Machine Learning (2024) | TGRS Research Map | TGRS