| Autor: |
Biao Pan, Deming Zhang, Xueying Zhang, Haotian Wang, Jinyu Bai, Jianlei Yang, Youguang Zhang, Wang Kang, Weisheng Zhao |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
IEEE Journal of the Electron Devices Society, Vol 7, Pp 529-533 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2168-6734 |
| DOI: |
10.1109/JEDS.2019.2913637 |
| Popis: |
Novel skyrmion-magnetic tunnel junction (SK-MTJ) devices were investigated for the first time to implement the ternary neural networks (TNN). In the SK-MTJ, an extra magnetoresistance state beyond binary parallel and anti-parallel MTJ states was achieved by forming a skyrmion vortex structure in the free layer. Based on the SK-MTJ, we propose a synaptic architecture with bit-cell design of +1, 0, and -1 to replace the full precision floating point arithmetic with equivalent bit-wise multiplication operation. To explore the feasibility of the SK-MTJ-based synaptic devices for TNN application, circuitlevel simulations for image recognition task were conducted. The recognition rate can reach up to 99% with 5% device variation and an average power consumption of 29.23 μW. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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