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1 Ergebnisse
1
Enabling High-Quality Uncertainty Quantification in a PIM D..:
, In:
2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA)
,
Li, Xingchen
;
Wu, Bingzhe
;
Sun, Guangyu
... - p. 1043-1055 , 2022
Link:
https://doi.org/10.1109/HPCA53966.2022.00080
RT T1 <cTitle>2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA)</cTitle>: T1 <Title>Enabling High-Quality Uncertainty Quantification in a PIM Designed for Bayesian Neural Network</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9773213&Exemplar=1&LAN=DE A1 Li, Xingchen A1 Wu, Bingzhe A1 Sun, Guangyu A1 Zhang, Zhe A1 Yuan, Zhihang A1 Wang, Runsheng A1 Huang, Ru A1 Niu, Dimin A1 Zheng, Hongzhong A1 Lu, Zhichao A1 Zhao, Liang A1 Chang, Meng-Fan Marvin A1 Guan, Tianchan A1 Si, Xin YR 2022 SN 2378-203X K1 Uncertainty K1 Computational modeling K1 Neural networks K1 Computer architecture K1 Throughput K1 Hardware K1 Energy efficiency K1 ReRAM K1 Bayesian Neural Network K1 Analog Computing K1 Noise SP 1043 OP 1055 LK http://dx.doi.org/https://doi.org/10.1109/HPCA53966.2022.00080 DO https://doi.org/10.1109/HPCA53966.2022.00080 SF ELIB - SuUB Bremen
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