Composing graph theory and deep neural networks to evaluate SEU type soft error effects
author
Balakrishnan, Aneesh
Lange, Thomas
Glorieux, Maximilien
Alexandrescu, Dan
Jenihhin, Maksim
statement of authorship
Aneesh Balakrishnan, Thomas Lange, Maximilien Glorieux, Dan Alexandrescu, Maksim Jenihhin
source
9th Mediterranean Conference on Embedded Computing (MECO'2020), Budva, Montenegro, 8-11 June 2020
location of publication
Danvers
publisher
IEEE
year of publication
2020
conference name, date
9th Mediterranean Conference on Embedded Computing (MECO'2020), 8-11 June 2020
conference location
Budva, Montenegro
url
https://doi.org/10.1109/MECO49872.2020.9134279
subject term
tehisnärvivõrgud
diagnostika (tehnika)
veaavastus
keyword
GraphSAGE (Graph Based Neural Network)
gate-level circuit abstraction
deep neural networks
Functional Failure Rate (FFR)
Single Event Upset (SEU)
Single Event Transient (SET) and Soft Errors
notes
Bibliogr.: 10 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
3.1
TalTech department
arvutisüsteemide instituut
language
inglise
Reserch Group
Centre for trustworthy and efficient computing hardware (TECH)
Centre of dependable computing systems