{"title":"MESO Neuron: A Low-Power and Ultrafast Spin Neuron for Neuromorphic Computing","authors":"Junwei Zeng;Yabo Chen;Jiahao Liu;Chenglong Huang;Nuo Xu;Cheng Li;Liang Fang","doi":"10.1109/LMAG.2022.3146130","DOIUrl":null,"url":null,"abstract":"In this letter, a low-power and ultrafast spin neuron for mimicking biological neurons based on magneto-electric spin-orbit (MESO) neurons is presented. First, the physical model of a MESO neuron based on the Landau–Lifshitz–Gilbert (LLG) equation at room temperature is built for investigating the characteristics. By utilizing these characteristics of the MESO device, a current pulse is used to induce the stochastic switching behaviors. We successfully mimic the behavior of the biological neuron with single activation time down to 0.8 ns. Second, using model-derived device parameters, we further simulate a three-layer fully connected neural network using MESO neurons. Using the Mixed National Institute of Standards and Technology database handwritten pattern dataset, our system achieves a recognition accuracy of 98%. In addition, the influence of pulsewidth and amplitude on activation functions of MESO neurons is researched using HSPICE tools. The results show that as pulsewidth and amplitude are increasing, the power consumption and computing time increase while the energy consumption decreases. Specifically, the power consumption performance of a MESO neuron is about 10 µW and improved approximately three orders of magnitude compared to a 45 nm CMOS neuron.","PeriodicalId":13040,"journal":{"name":"IEEE Magnetics Letters","volume":"13 ","pages":"1-5"},"PeriodicalIF":1.1000,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Magnetics Letters","FirstCategoryId":"101","ListUrlMain":"https://ieeexplore.ieee.org/document/9695352/","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
In this letter, a low-power and ultrafast spin neuron for mimicking biological neurons based on magneto-electric spin-orbit (MESO) neurons is presented. First, the physical model of a MESO neuron based on the Landau–Lifshitz–Gilbert (LLG) equation at room temperature is built for investigating the characteristics. By utilizing these characteristics of the MESO device, a current pulse is used to induce the stochastic switching behaviors. We successfully mimic the behavior of the biological neuron with single activation time down to 0.8 ns. Second, using model-derived device parameters, we further simulate a three-layer fully connected neural network using MESO neurons. Using the Mixed National Institute of Standards and Technology database handwritten pattern dataset, our system achieves a recognition accuracy of 98%. In addition, the influence of pulsewidth and amplitude on activation functions of MESO neurons is researched using HSPICE tools. The results show that as pulsewidth and amplitude are increasing, the power consumption and computing time increase while the energy consumption decreases. Specifically, the power consumption performance of a MESO neuron is about 10 µW and improved approximately three orders of magnitude compared to a 45 nm CMOS neuron.
期刊介绍:
IEEE Magnetics Letters is a peer-reviewed, archival journal covering the physics and engineering of magnetism, magnetic materials, applied magnetics, design and application of magnetic devices, bio-magnetics, magneto-electronics, and spin electronics. IEEE Magnetics Letters publishes short, scholarly articles of substantial current interest.
IEEE Magnetics Letters is a hybrid Open Access (OA) journal. For a fee, authors have the option making their articles freely available to all, including non-subscribers. OA articles are identified as Open Access.