Reliability evaluation of Convolutional Neural Network's basic operations on a RISC-V processor

Autor: Fernandes dos Santos, Fernando, Kritikakou, Angeliki, Sentieys, Olivier

Publikováno v: NSREC 2023-IEEE Nuclear & Space Radiation Effects Conference
NSREC 2023-IEEE Nuclear & Space Radiation Effects Conference, IEEE Nuclear and Plasma Sciences Society (NPSS), Jul 2023, Kansas City, MO, United States. pp.1-6

International audience; Thanks to RISC-V open-source Instruction Set Architecture, researchers and developers can efficiently propose new solutions at a low-cost and low-power consumption. RISC-Vbased architectures can, then, be customized to run Mac

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::3ef50d510f4c6b17a3577ae5bb240fd3
https://inria.hal.science/hal-04047058/document

TA05-100: CHAracterizing Neutron Induced Errors on Ultra Low Power RISC-V SoCs for Deep Neural Networks (CHANEL-V)

Autor: Fernandes dos Santos, Fernando

RADNEXT Transnational Access Summary Report

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c65e6da933dec386d198c1fdb2dc74a

Kernel and layer vulnerability factor to evaluate object detection reliability in GPUs.

Autor: Fernandes dos Santos, Fernando¹ (AUTHOR) ffsantos@inf.ufrgs.br, Carro, Luigi¹ (AUTHOR), Rech, Paolo¹ (AUTHOR)

Publikováno v: IET Computers & Digital Techniques (Wiley-Blackwell). May2019, Vol. 13 Issue 3, p178-186. 9p.