Review of candidate devices for neuromorphic applications

被引:4
|
作者
Lee, Jong-Ho [1 ]
Woo, Sung Yun
Lee, Sung-Tae
Lim, Suhwan
Kang, Won-Mook
Seo, Young-Tak
Lee, Soochang
Kwon, Dongseok
Oh, Seongbin
Noh, Yoohyun
Kim, Hyeongsu
Kim, Jangsaeng
Bae, Jong-Ho
机构
[1] Seoul Natl Univ, Dept Elect & Comp Engn, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
neuromorphic systems; neural networks; synaptic devices; emerging memories; flash memories; SYNAPSE DEVICE; RRAM; MEMORY; ARRAY;
D O I
10.1109/essderc.2019.8901694
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Artificial intelligence technology has attracted much attention in recent years, and technological progress of this technology is anticipated with the development of semiconductor technology. This talk focuses on synaptic mimic devices to realize artificial intelligence with semiconductor memory technology. These synaptic devices affect cognitive accuracy along with conductance quantization and architecture. Therefore, we will first discuss from the architectural point of view and examine the characteristics of candidates for various synapse devices being reported. In particular, we concentrate on synaptic imitation devices that creatively use the functions of several flash memory devices. Finally, we discuss device variation and IR drop along metal wires as common challenges for synaptic devices, and how neuromorphic technology will evolve.
引用
收藏
页码:22 / 27
页数:6
相关论文
共 50 条
  • [1] Optoelectronic neuromorphic devices and their applications
    Shen Liu-Feng
    Hu Ling-Xiang
    Kang Feng-Wen
    Ye Yu-Min
    Zhuge Fei
    ACTA PHYSICA SINICA, 2022, 71 (14)
  • [2] Neuromorphic devices for electronic skin applications
    Patil, Chandrashekhar S.
    Ghode, Sourabh B.
    Kim, Jungmin
    Kamble, Girish U.
    Kundale, Somnath S.
    Mannan, Abdul
    Ko, Youngbin
    Noman, Muhammad
    Saqib, Qazi Muhammad
    Patil, Swapnil R.
    Bae, Seo Yeong
    Kim, Jin Hyeok
    Park, Jun Hong
    Bae, Jinho
    MATERIALS HORIZONS, 2025, 12 (07)
  • [3] Organic Memristive Devices for Neuromorphic Applications
    Silvia Battistoni
    BioNanoScience, 2021, 11 : 227 - 231
  • [4] Organic Memristive Devices for Neuromorphic Applications
    Battistoni, Silvia
    BIONANOSCIENCE, 2021, 11 (01) : 227 - 231
  • [5] Advances in neuromorphic devices for the hardware implementation of neuromorphic computing systems for future artificial intelligence applications: A critical review
    Ajayan, J.
    Nirmal, D.
    Jebalin, Binola K.
    Sreejith, S.
    MICROELECTRONICS JOURNAL, 2022, 130
  • [6] Stochastic memristive devices for computing and neuromorphic applications
    Gaba, Siddharth
    Sheridan, Patrick
    Zhou, Jiantao
    Choi, Shinhyun
    Lu, Wei
    NANOSCALE, 2013, 5 (13) : 5872 - 5878
  • [7] Piezotronic neuromorphic devices: principle, manufacture, and applications
    Lin, Xiangde
    Feng, Zhenyu
    Xiong, Yao
    Sun, Wenwen
    Yao, Wanchen
    Wei, Yichen
    Wang, Zhong Lin
    Sun, Qijun
    INTERNATIONAL JOURNAL OF EXTREME MANUFACTURING, 2024, 6 (03)
  • [8] Memristive Devices for Neuromorphic Applications: Comparative Analysis
    Victor Erokhin
    BioNanoScience, 2020, 10 : 834 - 847
  • [9] Memory Devices for Flexible and Neuromorphic Device Applications
    Kim, Dongshin
    Kim, Ik-Jyae
    Lee, Jang-Sik
    ADVANCED INTELLIGENT SYSTEMS, 2021, 3 (05)
  • [10] Memristive Devices for Neuromorphic Applications: Comparative Analysis
    Erokhin, Victor
    BIONANOSCIENCE, 2020, 10 (04) : 834 - 847