Atsuya Okazaki, Pritish Narayanan, Stefano Ambrogio, Kohji Hosokawa, Hsinyu Tsai, Akiyo Nomura, Takeo Yasuda, Charles Mackin, Alexander M. Friz, Masatoshi Ishii, Yasuteru Kohda, Katie Spoon, An Chen, Andrea Fasoli, Malte J. Rasch, Geoffrey W. Burr. Analog-memory-based 14nm Hardware Accelerator for Dense Deep Neural Networks including Transformers. In IEEE International Symposium on Circuits and Systems, ISCAS 2022, Austin, TX, USA, May 27 - June 1, 2022. pages 3319-3323, IEEE, 2022. [doi]
@inproceedings{OkazakiNAHTNYMF22,
title = {Analog-memory-based 14nm Hardware Accelerator for Dense Deep Neural Networks including Transformers},
author = {Atsuya Okazaki and Pritish Narayanan and Stefano Ambrogio and Kohji Hosokawa and Hsinyu Tsai and Akiyo Nomura and Takeo Yasuda and Charles Mackin and Alexander M. Friz and Masatoshi Ishii and Yasuteru Kohda and Katie Spoon and An Chen and Andrea Fasoli and Malte J. Rasch and Geoffrey W. Burr},
year = {2022},
doi = {10.1109/ISCAS48785.2022.9937292},
url = {https://doi.org/10.1109/ISCAS48785.2022.9937292},
researchr = {https://researchr.org/publication/OkazakiNAHTNYMF22},
cites = {0},
citedby = {0},
pages = {3319-3323},
booktitle = {IEEE International Symposium on Circuits and Systems, ISCAS 2022, Austin, TX, USA, May 27 - June 1, 2022},
publisher = {IEEE},
isbn = {978-1-6654-8485-5},
}