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- Publisher Website: 10.1063/5.0202103
- Scopus: eid_2-s2.0-85194092338
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Article: Magnetic field-free stochastic computing based on the voltage-controlled magnetic tunnel junction
Title | Magnetic field-free stochastic computing based on the voltage-controlled magnetic tunnel junction |
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Authors | |
Issue Date | 20-May-2024 |
Publisher | American Institute of Physics |
Citation | Applied Physics Letters, 2024, v. 124, n. 21 How to Cite? |
Abstract | The stochastic computing (SC) has been proven to be an energy-efficient way to perform neural network. In this study, we propose a field-free voltage-controlled spintronics SC system based on the magnetic tunnel junction (MTJ). We observe a stochastic switching behavior of the MTJ and that it could be controlled by the voltage applied on the device. The voltage-controlled stochastic switching behavior is used to encode numbers ranging from 0 to 1 into a series of random bit-streams in the SC system. Furthermore, the handwritten recognition task is performed on the MTJ-based SC system, achieving a 95% maximum accuracy, which is comparable with the floating-point based neural network. Our work provides inspiration for the energy-efficient neural network systems. |
Persistent Identifier | http://hdl.handle.net/10722/346035 |
ISSN | 2023 Impact Factor: 3.5 2023 SCImago Journal Rankings: 0.976 |
DC Field | Value | Language |
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dc.contributor.author | Luo, Yanxiang | - |
dc.contributor.author | Wu, Yuxuan | - |
dc.contributor.author | Zeng, Kexin | - |
dc.contributor.author | Zhang, Like | - |
dc.contributor.author | Liu, Shuhui | - |
dc.contributor.author | Luo, Renjuan | - |
dc.contributor.author | Luo, Yawen | - |
dc.contributor.author | Zhang, Xuan | - |
dc.contributor.author | Fang, Bin | - |
dc.contributor.author | Zhou, Yan | - |
dc.contributor.author | Zeng, Zhongming | - |
dc.date.accessioned | 2024-09-06T00:30:35Z | - |
dc.date.available | 2024-09-06T00:30:35Z | - |
dc.date.issued | 2024-05-20 | - |
dc.identifier.citation | Applied Physics Letters, 2024, v. 124, n. 21 | - |
dc.identifier.issn | 0003-6951 | - |
dc.identifier.uri | http://hdl.handle.net/10722/346035 | - |
dc.description.abstract | The stochastic computing (SC) has been proven to be an energy-efficient way to perform neural network. In this study, we propose a field-free voltage-controlled spintronics SC system based on the magnetic tunnel junction (MTJ). We observe a stochastic switching behavior of the MTJ and that it could be controlled by the voltage applied on the device. The voltage-controlled stochastic switching behavior is used to encode numbers ranging from 0 to 1 into a series of random bit-streams in the SC system. Furthermore, the handwritten recognition task is performed on the MTJ-based SC system, achieving a 95% maximum accuracy, which is comparable with the floating-point based neural network. Our work provides inspiration for the energy-efficient neural network systems. | - |
dc.language | eng | - |
dc.publisher | American Institute of Physics | - |
dc.relation.ispartof | Applied Physics Letters | - |
dc.title | Magnetic field-free stochastic computing based on the voltage-controlled magnetic tunnel junction | - |
dc.type | Article | - |
dc.identifier.doi | 10.1063/5.0202103 | - |
dc.identifier.scopus | eid_2-s2.0-85194092338 | - |
dc.identifier.volume | 124 | - |
dc.identifier.issue | 21 | - |
dc.identifier.eissn | 1077-3118 | - |
dc.identifier.issnl | 0003-6951 | - |