Classification of neural network hardware

被引:0
|
作者
Computer Engineering Dep Eastern, Mediterranean Univ, Magosa, Cyprus [1 ]
机构
来源
Neural Network World | / 1卷 / 11-27期
关键词
Classification (of information) - Computer hardware - Electronic equipment;
D O I
暂无
中图分类号
学科分类号
摘要
There is a need for studies to classify Neural Network hardware according to some generally accepted criteria to make it easier to understand the basic properties of newly proposed neurochips. This paper aims at putting forward a new proposal for the classification of Neural Network hardware. For this purpose, first the basic components and architecture of a neurochip are described. Then attributes are selected and outlined for the classification, and possible values they may take are discussed. A number of well-known Neural Network chips are then classified using the suggested method.
引用
收藏
相关论文
共 50 条
  • [31] A NEURAL NETWORK HARDWARE MODEL FOR IMAGE THINNING
    Peng Zhiping Zhang Liming (E.E.Dept.
    Journal of Electronics(China), 1992, (04) : 376 - 383
  • [32] A Hardware Implementation of SOM Neural Network Algorithm
    Yi, Qian
    2018 INTERNATIONAL CONFERENCE ON SENSOR NETWORKS AND SIGNAL PROCESSING (SNSP 2018), 2018, : 508 - 511
  • [33] Parallelism hardware computation for Artificial Neural Network
    Marwa, G. A. M.
    Mohamed, Boubaker
    Najoua, Chalbi
    Hedi, Bedoui Mohamed
    2017 IEEE/ACS 14TH INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS (AICCSA), 2017, : 1049 - 1055
  • [34] Hardware design and the competency awareness of a neural network
    Ding, Yukun
    Jiang, Weiwen
    Lou, Qiuwen
    Liu, Jinglan
    Xiong, Jinjun
    Hu, Xiaobo Sharon
    Xu, Xiaowei
    Shi, Yiyu
    NATURE ELECTRONICS, 2020, 3 (09) : 514 - 523
  • [35] Hardware Aspects of Parallel Neural Network Implementation
    Kouretas, I
    Paliouras, V
    2021 10TH INTERNATIONAL CONFERENCE ON MODERN CIRCUITS AND SYSTEMS TECHNOLOGIES (MOCAST), 2021,
  • [36] DeepHardMark: Towards Watermarking Neural Network Hardware
    Clements, Joseph
    Lao, Yingjie
    THIRTY-SIXTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FOURTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE / THE TWELVETH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2022, : 4450 - 4458
  • [37] Function approximation by hardware spiking neural network
    Farsa, Edris Zaman
    Nazari, Soheila
    Gholami, Morteza
    JOURNAL OF COMPUTATIONAL ELECTRONICS, 2015, 14 (03) : 707 - 716
  • [38] Evolvable hardware chips for neural network applications
    Kajitani, I
    Murakawa, M
    Kajihara, N
    Iwata, M
    Sakanashi, H
    Higuchi, T
    ARTIFICIAL NEURAL NETS AND GENETIC ALGORITHMS, 1999, : 127 - 134
  • [39] A Novel Reconfigurable Hardware Architecture of Neural Network
    Khalil, Kasem
    Eldash, Omar
    Dey, Bappaditya
    Kumar, Ashok
    Bayoumi, Magdy
    2019 IEEE 62ND INTERNATIONAL MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS (MWSCAS), 2019, : 618 - 621
  • [40] Spiking Neural Network Design for Neuromorphic Hardware
    Balaji, Adarsha
    2024 IEEE WORKSHOP ON MICROELECTRONICS AND ELECTRON DEVICES, WMED, 2024, : XVI - XVI