Characterizing a Neutron-Induced Fault Model for Deep Neural Networks-Reference-Cited by-同舟云学术

Characterizing a Neutron-Induced Fault Model for Deep Neural Networks

Published:2023-04 Issue:4 Volume:70 Page:370-380
ISSN:0018-9499
Container-title:IEEE Transactions on Nuclear Science
language:
Short-container-title:IEEE Trans. Nucl. Sci.

Author:

Santos Fernando Fernandes dos¹^ORCID,Kritikakou Angeliki¹^ORCID,Condia Josie E. Rodriguez²^ORCID,Guerrero-Balaguera Juan-David²^ORCID,Reorda Matteo Sonza²^ORCID,Sentieys Olivier¹^ORCID,Rech Paolo³^ORCID

Affiliation:

1. INRIA, University of Rennes 1, Rennes, France

2. Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Turin, Italy

3. Department of Industrial Engineering, University of Trento, Trento, Italy

Funder

European Union’s Horizon 2020 Research and Innovation Program within the Marie Sklodowska-Curie

The Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Brazil

BIENVENÜE Bienvenue Fellowship MSCA Co-Funded Program

ANR RE-TRUSTING

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Nuclear Energy and Engineering,Nuclear and High Energy Physics

Link

http://xplorestaging.ieee.org/ielx7/23/10103954/09963710.pdf?arnumber=9963710

Reference63 articles.

1. Evaluating and Mitigating Neutrons Effects on COTS EdgeAI Accelerators

2. Threads Distribution Effects on Graphics Processing Units Neutron Sensitivity

3. Soft errors in DNN accelerators: A comprehensive review

4. Kayotee: A fault injection-based system to assess the safety and reliability of autonomous vehicles to faults and errors;jha;arXiv 1907 01024,2019

5. GPU Behavior on a Large HPC Cluster

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