täiskirje prindi

Modeling gate-level abstraction hierarchy using graph convolutional neural networks to predict functional de-rating factors

autor
vastutusandmed
Aneesh Balakrishnan, Thomas Lange, Maximilien Glorieux, Dan Alexandrescu, Maksim Jenihhi
allikas
2019 NASA/ESA conference on adaptive hardware and systems AHS 2019 : proceedings
kirjastus/väljaandja
ilmumisaasta
leheküljed
p. 72-78 : ill
konverentsi nimetus, aeg
The 2019 NASA/ESA Conference on Adaptive Hardware and Systems (AHS 2019), 22-24 July 2019
konverentsi toimumispaik
Colchester, United Kingdom
leitav
märkused
Bibliogr.: 7 ref
TTÜ struktuuriüksus
keel
inglise
märksõna
võtmesõna
Probabilistic Graph Model (PGM)
Graph Convolutional Neural Network (GCN)
functional de-rating
Single Event Upset (SEU)
gate-level netlist
Graph Modeling Language (GML)
Balakrishnan, A., Lange, T., Glorieux, M., Alexandrescu, D., Jenihhin, M. Modeling gate-level abstraction hierarchy using graph convolutional neural networks to predict functional de-rating factors // 2019 NASA/ESA conference on adaptive hardware and systems AHS 2019 : proceedings. : IEEE, 2019. p. 72-78 : ill. https://doi.org/10.1109/AHS.2019.00007