Session 15 Overview: Compute-in-Memory Processors for Deep Neural Networks Machine Learning Subcommittee

被引:0
|
作者
Deguchi, Jun [1 ]
Liu, Yongpan [2 ]
Li, Yan [3 ]
机构
[1] Kioxia Corporation, Kawasaki, Japan
[2] Tsinghua University, Beijing, China
[3] Western Digital, Milpitas,CA, United States
关键词
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:234 / 235
相关论文
共 50 条
  • [21] 8T XNOR-SRAM based Parallel Compute-in-Memory for Deep Neural Network Accelerator
    Jiang, Hongwu
    Liu, Rui
    Yu, Shimeng
    2020 IEEE 63RD INTERNATIONAL MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS (MWSCAS), 2020, : 257 - 260
  • [22] CIMAT: A Transpose SRAM-based Compute-In-Memory Architecture for Deep Neural Network On-Chip Training
    Jiang, Hongwu
    Peng, Xiaochen
    Huang, Shanshi
    Yu, Shimeng
    MEMSYS 2019: PROCEEDINGS OF THE INTERNATIONAL SYMPOSIUM ON MEMORY SYSTEMS, 2019, : 490 - 496
  • [23] Introduction to Machine Learning, Neural Networks, and Deep Learning
    Choi, Rene Y.
    Coyner, Aaron S.
    Kalpathy-Cramer, Jayashree
    Chiang, Michael F.
    Campbell, J. Peter
    TRANSLATIONAL VISION SCIENCE & TECHNOLOGY, 2020, 9 (02):
  • [24] Design of Current-Mode 8T SRAM Compute-In-Memory Macro for Processing Neural Networks
    Yu, Chengshuo
    Yoo, Taegeun
    Kim, Tony Tae-Hyoung
    Kim, Bongjin
    Chuan, Kevin Chai Tshun
    2020 17TH INTERNATIONAL SOC DESIGN CONFERENCE (ISOCC 2020), 2020, : 175 - 176
  • [25] CMOS-compatible compute-in-memory accelerators based on integrated ferroelectric synaptic arrays for convolution neural networks
    Kim, Min-Kyu
    Kim, Ik-Jyae
    Lee, Jang-Sik
    SCIENCE ADVANCES, 2022, 8 (14)
  • [26] Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited)
    Frank, Martin M.
    Li, Ning
    Rasch, Malte J.
    Jain, Shubham
    Chen, Ching-Tzu
    Muralidhar, Ramachandran
    Han, Jin-Ping
    Narayanan, Vijay
    Philip, Timothy M.
    Brew, Kevin
    Simon, Andrew
    Saraf, Iqbal
    Saulnier, Nicole
    Boybat, Irem
    Wozniak, Stanislaw
    Sebastian, Abu
    Narayanan, Pritish
    Mackin, Charles
    Chen, An
    Tsai, Hsinyu
    Burr, Geoffrey W.
    2023 IEEE INTERNATIONAL RELIABILITY PHYSICS SYMPOSIUM, IRPS, 2023,
  • [27] Advances in Machine Learning and Deep Neural Networks
    Chellappa, Rama
    Theodoridis, Sergios
    van Schaik, Andre
    PROCEEDINGS OF THE IEEE, 2021, 109 (05) : 607 - 611
  • [28] Deep Neural Networks and Explainable Machine Learning
    Maratea, Antonio
    Ferone, Alessio
    FUZZY LOGIC AND APPLICATIONS, WILF 2018, 2019, 11291 : 253 - 256
  • [29] A 65-nm 8T SRAM Compute-in-Memory Macro With Column ADCs for Processing Neural Networks
    Yu, Chengshuo
    Yoo, Taegeun
    Chai, Kevin Tshun Chuan
    Kim, Tony Tae-Hyoung
    Kim, Bongjin
    IEEE JOURNAL OF SOLID-STATE CIRCUITS, 2022, 57 (11) : 3466 - 3476
  • [30] An Energy Efficient All-Digital Time-Domain Compute-in-Memory Macro Optimized for Binary Neural Networks
    Lou, Jie
    Freye, Florian
    Lanius, Christian
    Gemmeke, Tobias
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2024, 71 (01) : 287 - 298