针对尖峰神经网络使用 Ge-source TFET 的高能效漏整合与发射神经元:仿真分析

IF 2.6 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY Physica Scripta Pub Date : 2024-09-15 DOI:10.1088/1402-4896/ad76ea
Shreyas Tiwari, Rajesh Saha and Tarun Varma
{"title":"针对尖峰神经网络使用 Ge-source TFET 的高能效漏整合与发射神经元:仿真分析","authors":"Shreyas Tiwari, Rajesh Saha and Tarun Varma","doi":"10.1088/1402-4896/ad76ea","DOIUrl":null,"url":null,"abstract":"The basic building block of neural network is a device, which can mimic the neural behavior. The spiking neural network (SNN) is an efficient methodology in terms of power and area. Due to the excess energy consumption and larger area, various spintronic neural devices are unfit for neuron applications. In this article, we have implemented Ge source based Tunnel FET (TFET) for ultralow energy spike generation using TCAD simulator. It is seen that Ge source TFET has signature spiking frequency in THz range versus input voltage curve of an artificial biological neuron. The simulated device deploy the leaky integrate and fire (LIF) technique for generation of neurons. The simulation result highlights that the energy of device is 1.08 aJ/spike, which is several order less than existing neural based FET devices in literature.","PeriodicalId":20067,"journal":{"name":"Physica Scripta","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An energy efficient leaky integrate and fire neuron using Ge-source TFET for spiking neural network: simulation analysis\",\"authors\":\"Shreyas Tiwari, Rajesh Saha and Tarun Varma\",\"doi\":\"10.1088/1402-4896/ad76ea\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The basic building block of neural network is a device, which can mimic the neural behavior. The spiking neural network (SNN) is an efficient methodology in terms of power and area. Due to the excess energy consumption and larger area, various spintronic neural devices are unfit for neuron applications. In this article, we have implemented Ge source based Tunnel FET (TFET) for ultralow energy spike generation using TCAD simulator. It is seen that Ge source TFET has signature spiking frequency in THz range versus input voltage curve of an artificial biological neuron. The simulated device deploy the leaky integrate and fire (LIF) technique for generation of neurons. The simulation result highlights that the energy of device is 1.08 aJ/spike, which is several order less than existing neural based FET devices in literature.\",\"PeriodicalId\":20067,\"journal\":{\"name\":\"Physica Scripta\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physica Scripta\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.1088/1402-4896/ad76ea\",\"RegionNum\":3,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PHYSICS, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physica Scripta","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1088/1402-4896/ad76ea","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

神经网络的基本构件是一个可以模拟神经行为的设备。就功率和面积而言,尖峰神经网络(SNN)是一种高效的方法。由于能耗过高、面积较大,各种自旋电子神经器件都不适合神经元应用。在本文中,我们利用 TCAD 仿真器实现了基于 Ge 源的隧道场效应晶体管 (TFET),用于产生超低能量的尖峰脉冲。结果表明,Ge 源 TFET 具有太赫兹范围内的特征尖峰频率与人工生物神经元的输入电压曲线。仿真设备采用了漏电集成和点火(LIF)技术来生成神经元。模拟结果表明,该器件的能量为 1.08 aJ/尖峰,比文献中现有的基于神经的场效应晶体管器件低几个数量级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
An energy efficient leaky integrate and fire neuron using Ge-source TFET for spiking neural network: simulation analysis
The basic building block of neural network is a device, which can mimic the neural behavior. The spiking neural network (SNN) is an efficient methodology in terms of power and area. Due to the excess energy consumption and larger area, various spintronic neural devices are unfit for neuron applications. In this article, we have implemented Ge source based Tunnel FET (TFET) for ultralow energy spike generation using TCAD simulator. It is seen that Ge source TFET has signature spiking frequency in THz range versus input voltage curve of an artificial biological neuron. The simulated device deploy the leaky integrate and fire (LIF) technique for generation of neurons. The simulation result highlights that the energy of device is 1.08 aJ/spike, which is several order less than existing neural based FET devices in literature.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Physica Scripta
Physica Scripta 物理-物理:综合
CiteScore
3.70
自引率
3.40%
发文量
782
审稿时长
4.5 months
期刊介绍: Physica Scripta is an international journal for original research in any branch of experimental and theoretical physics. Articles will be considered in any of the following topics, and interdisciplinary topics involving physics are also welcomed: -Atomic, molecular and optical physics- Plasma physics- Condensed matter physics- Mathematical physics- Astrophysics- High energy physics- Nuclear physics- Nonlinear physics. The journal aims to increase the visibility and accessibility of research to the wider physical sciences community. Articles on topics of broad interest are encouraged and submissions in more specialist fields should endeavour to include reference to the wider context of their research in the introduction.
期刊最新文献
Exceptional anisotropic superhydrophobicity of sword-lily striated leaf surface and soft lithographic biomimicking using polystyrene replica Improving bidirectional controlled remote preparation of arbitrary number of qudits in noisy environment A study on the synthesis of superheavy element Mc (Z = 115) using lead, bismuth and actinide targets Comparative study of structural, opto-electronic properties of Cs2TiX6-based single halide double perovskite solar cells: computational and experimental approach Zn-MOF as a saturable absorber for thulium/holmium-doped fiber laser
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1