J
J. Aribido
Publications - 3
Citations - 11
J. Aribido is an academic researcher. The author has contributed to research in topics: Computer science. The author has an hindex of 2, co-authored 3 publications receiving 11 citations.
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Proceedings ArticleDOI
Test, Reliability and Functional Safety Trends for Automotive System-on-Chip
Francesco Angione,D. Appello,J. Aribido,Jyotika Athavale,N. Bellarmino,Paolo Bernardi,Riccardo Cantoro,Corrado De Sio,T. Foscale,G. Gavarini,J. Guerrero,Martin Huch,G. Iaria,T. Kilian,Rafael Grau Mariani,Ralph Martone,Annachiara Ruospo,Erwing R. Sanchez,Ulf Schlichtmann,Giovanni Squillero,Matteo Sonza Reorda,Luca Sterpone,V. Tancorre,R. Ugioli +23 more
TL;DR: In this article , three contributions by industry professionals and university researchers describe different trends in automotive products, including both manufacturing test and run-time reliability strategies, from optimizing the final test before shipment to market to in-field reliability during operative life.
Proceedings ArticleDOI
Assessing Convolutional Neural Networks Reliability through Statistical Fault Injections
Annachiara Ruospo,G. Gavarini,Corrado De Sio,J. Guerrero,Luca Sterpone,Matteo Sonza Reorda,Ernesto Sanchez,J. Aribido,Jyotika Athavale +8 more
TL;DR: In this article , the authors describe how to correctly specify statistical FIs for Convolutional Neural Networks, and propose a data analysis on the CNN parameters that drastically reduces the number of FIs needed to achieve statistically significant results without compromising the validity of the proposed method.
Proceedings ArticleDOI
Image Test Libraries for the on-line self-test of functional units in GPUs running CNNs
Annachiara Ruospo,G. Gavarini,Matteo Sonza Reorda,Ernesto Sanchez,Riccardo Mariani,J. Aribido,Jyotika Athavale +6 more
TL;DR: In this article , an Image Test Library (ITL) is developed targeting the on-line test of GPU functional units, which is able to achieve about 95% of stuck-at test coverage on the floating-point multipliers in a GPU.