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MPress: Democratizing Billion-Scale Model Training on Multi..:
, In:
2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA)
,
Zhou, Quan
;
Wang, Haiquan
;
Yu, Xiaoyan
... - p. 556-569 , 2023
Link:
https://doi.org/10.1109/HPCA56546.2023.10071077
RT T1 <cTitle>2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA)</cTitle>: T1 <Title>MPress: Democratizing Billion-Scale Model Training on Multi-GPU Servers via Memory-Saving Inter-Operator Parallelism</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10071077&Exemplar=1&LAN=DE A1 Zhou, Quan A1 Wang, Haiquan A1 Yu, Xiaoyan A1 Li, Cheng A1 Bai, Youhui A1 Yan, Feng A1 Xu, Yinlong YR 2023 SN 2378-203X K1 Training K1 Performance evaluation K1 Tensors K1 Costs K1 Computational modeling K1 Graphics processing units K1 Parallel processing K1 Inter-Operator Parallelism K1 DNN Training K1 Swap K1 Recomputation SP 556 OP 569 LK http://dx.doi.org/https://doi.org/10.1109/HPCA56546.2023.10071077 DO https://doi.org/10.1109/HPCA56546.2023.10071077 SF ELIB - SuUB Bremen
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