DeepAxe : a framework for exploration of approximation and reliability trade-offs in DNN accelerators

statement of authorship
Mahdi Taheri, Mohammad Riazati, Mohammad Hasan Ahmadilivani, Maksim Jenihhin, Masoud Daneshtalab, Jaan Raik, Mikael Sjodin, Bjorn Lisper
source
publisher
journal volume number month
arXiv:2303.08226
year of publication
pages
8 p. : ill
notes
This paper is accepted at the 24th International Symposium on Quality Electronic Design (ISQED) 2023
scientific publication
teaduspublikatsioon
classifier
3.1
TTÜ department
language
inglise
Taheri, M., Riazati, M., Ahmadilivani, M.H., Jenihhin, M., Daneshtalab, M., Raik, J., Sjödin, M., Lisper, B. DeepAxe : a framework for exploration of approximation and reliability trade-offs in DNN accelerators // arXiv.org (2023) arXiv:2303.08226, 8 p. : ill. https://doi.org/10.48550/arXiv.2303.0822