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Power and Performance Costs of Radiation-Hardened ML Infere..:
, In:
2023 36th SBC/SBMicro/IEEE/ACM Symposium on Integrated Circuits and Systems Design (SBCCI)
,
Abich, Geancarlo
;
Silva, Anderson Ignacio
;
Gava, Jonas
... - p. 1-6 , 2023
Link:
https://doi.org/10.1109/SBCCI60457.2023.10261657
RT T1 <cTitle>2023 36th SBC/SBMicro/IEEE/ACM Symposium on Integrated Circuits and Systems Design (SBCCI)</cTitle>: T1 <Title>Power and Performance Costs of Radiation-Hardened ML Inference Models Running on Edge Devices</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10261657&Exemplar=1&LAN=DE A1 Abich, Geancarlo A1 Silva, Anderson Ignacio A1 Gava, Jonas A1 Susin, Altamiro Amadeu A1 Reis, Ricardo A1 Ost, Luciano YR 2023 K1 Performance evaluation K1 Analytical models K1 Costs K1 Power demand K1 Computational modeling K1 Memory management K1 Machine learning K1 Power K1 Performance K1 Mitigation K1 Machine Learning K1 Edge Devices K1 Reliability K1 Radiation Effects SP 1 OP 6 LK http://dx.doi.org/https://doi.org/10.1109/SBCCI60457.2023.10261657 DO https://doi.org/10.1109/SBCCI60457.2023.10261657 SF ELIB - SuUB Bremen
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