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Heterogeneous Approximation of DNN HW Accelerators based on Channels Vulnerability

author
statement of authorship
Natalia Cherezova, Salvatore Pappalardo, Mahdi Taheri, Mohammad Hasan Ahmadilivani, Bastien Deveautour, Alberto Bosio, Jaan Raik, Maksim Jenihhin
source
2024 IFIP/IEEE 32nd International Conference on Very Large Scale Integration (VLSI-SoC)
publisher
year of publication
pages
4 p. : ill
conference name, date
IFIP/IEEE 32nd International Conference on Very Large Scale Integration (VLSI-SoC), 06-09 October 2024
conference location
Tanger, Morocco
url
ISSN
2324-8440
ISBN
979-8-3315-3967-2
notes
Bibliogr.: 12 ref
scientific publication
teaduspublikatsioon
TalTech department
language
inglise
subject term
keyword
deep neural networks
data-flow architecture
hardware accelerator
approximate computing
circuit design
HW Accelerators based on Channels Vulnerability
Cherezova, N., Pappalardo, S., Taheri, M., Ahmadilivani, M.H., Deveautour, B., Bosio, A., Raik, J., Jenihhin, M. Heterogeneous Approximation of DNN HW Accelerators based on Channels Vulnerability // 2024 IFIP/IEEE 32nd International Conference on Very Large Scale Integration (VLSI-SoC). : IEEE, 2024. 4 p. : ill. https://doi.org//10.1109/VLSI-SoC62099.2024.10767798