Modeling gate-level abstraction hierarchy using graph convolutional neural networks to predict functional de-rating factors
statement of authorship
Aneesh Balakrishnan, Thomas Lange, Maximilien Glorieux, Dan Alexandrescu, Maksim Jenihhi
source
2019 NASA/ESA conference on adaptive hardware and systems AHS 2019 : proceedings
publisher
year of publication
pages
p. 72-78 : ill
conference name, date
The 2019 NASA/ESA Conference on Adaptive Hardware and Systems (AHS 2019), 22-24 July 2019
conference location
Colchester, United Kingdom
notes
Bibliogr.: 7 ref
TTÜ department
language
inglise
subject term
keyword
Probabilistic Graph Model (PGM)
Graph Convolutional Neural Network (GCN)
functional de-rating
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.