@inproceedings{1a6c3814d64f4e639aac61d394931121,
title = "Approximate computation based on NAND-SPIN MRAM for CNN on-chip training",
abstract = "Approximate computation is a widely used method to accelerate CNN training. In this work, the stochastic switching mechanism of the NAND-SPIN MRAM is utilized to perform the approximate update and storage of the synaptic weight. By reducing the programming time of the NAND-SPIN MTJs from 3 ns to 1 ns, more than 67\% speedup and nearly 70\% energy saving have been achieved with less than 1\% accuracy loss.",
keywords = "CNN, NAND-SPIN, approximate computation, on-chip training",
author = "Zhengyi Hou and Luyao Shi and Bi Wang and Zhaohao Wang",
note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 17th ACM International Symposium on Nanoscale Architectures, NANOARCH 2022 ; Conference date: 07-12-2022 Through 09-12-2022",
year = "2022",
month = dec,
day = "7",
doi = "10.1145/3565478.3572537",
language = "英语",
series = "Proceedings of the 17th ACM International Symposium on Nanoscale Architectures, NANOARCH 2022",
publisher = "Association for Computing Machinery, Inc",
booktitle = "Proceedings of the 17th ACM International Symposium on Nanoscale Architectures, NANOARCH 2022",
}