南方科技大学知识苑(SUSTech KC): A low-power charge-based integrate-and-fire circuit for binarized-spiking neural network

题名	A low-power charge-based integrate-and-fire circuit for binarized-spiking neural network
作者	Duong, Quang-Manh 1; Trinh, Quang-Kien 1; Nguyen, Van-Tinh 1; Dao, Dinh-Ha 1; Luong, Duy-Manh 1; Hoang, Van-Phuc 2; Lin, Longyang3 ; Deepu, John 4
通讯作者	Trinh, Quang-Kien
发表日期	2023-02-01
DOI	10.1002/cta.3573
发表期刊	INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS 影响因子和分区
ISSN	0098-9886
EISSN	1097-007X
卷号	51 期号:7页码:3404-3414
摘要	This paper presents a charge-based integrate-and-fire (IF) circuit for in-memory binary spiking neural networks (BSNNs). The proposed IF circuit can mimic both addition and subtraction operations that permit better incorporation with in-memory XNOR-based synapses to implement the BSNN processing core. To evaluate the proposed design, we have developed a framework that incorporates the circuit's imperfections effects into the system-level simulation. The array circuits use 2T-2J Spin-Transfer-Torque Magnetoresistive RAM (STT-MRAM) based on a 65-nm commercial CMOS and a fitted magnetic tunnel junction (MTJ). The system model has been described in Pytorch to best fit the extracted parameters from circuit levels, including the cover of device nonidealities and process variations. The simulation results show that the proposed design can achieve a performance of 5.10 fJ/synapse and reaches 82.01% classification accuracy for CIFAR-10 under process variation.
关键词	binary spiking neural networks in-memory computing neuromorphic computing STT-MRAM
相关链接	[来源记录]
收录类别	SCI ; EI
语种	英语
学校署名	其他
资助项目	Vietnam National Foundation for Science and Technology Development (NAFOSTED)[102.01-2018.310] ; Microelectronic Circuit Centre Ireland[MCCI-2020-07]
WOS研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic
WOS记录号	WOS:000940208600001
出版者	WILEY
EI入藏号	20231013674992
EI主题词	Computing power ; Low power electronics ; Magnetic recording ; MRAM devices ; Timing circuits ; Tunnel junctions
EI分类号	Pulse Circuits:713.4 ; Data Storage, Equipment and Techniques:722.1 ; Computer Peripheral Equipment:722.2 ; Digital Computers and Systems:722.4 ; Computer Software, Data Handling and Applications:723
ESI学科分类	ENGINEERING
来源库	Web of Science
引用统计	被引频次[WOS]：2
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/502139
专题	工学院_深港微电子学院
作者单位	1.Le Quy Don Tech Univ, Fac Radioelect Engn, Hanoi, Vietnam 2.Le Quy Don Tech Univ, Inst Syst Integrat, Hanoi, Vietnam 3.Southern Univ Sci & Technol, Sch Microelect, Shenzhen, Peoples R China 4.Univ Coll Dublin, Sch Elect & Elect Engn, Dublin, Ireland
推荐引用方式 GB/T 7714	Duong, Quang-Manh,Trinh, Quang-Kien,Nguyen, Van-Tinh,et al. A low-power charge-based integrate-and-fire circuit for binarized-spiking neural network[J]. INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS,2023,51(7):3404-3414.
APA	Duong, Quang-Manh.,Trinh, Quang-Kien.,Nguyen, Van-Tinh.,Dao, Dinh-Ha.,Luong, Duy-Manh.,...&Deepu, John.(2023).A low-power charge-based integrate-and-fire circuit for binarized-spiking neural network.INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS,51(7),3404-3414.
MLA	Duong, Quang-Manh,et al."A low-power charge-based integrate-and-fire circuit for binarized-spiking neural network".INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS 51.7(2023):3404-3414.