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cs.LG2023
Cuttlefish: Low-Rank Model Training without All the Tuning
Hongyi Wang, Saurabh Agarwal, Pongsakorn U-chupala +3
Recent research has shown that training low-rank neural networks can effectively reduce the total number of trainable parameters without sacrificing predictive accuracy, resulting…
cs.LG2018
Massively Distributed SGD: ImageNet/ResNet-50 Training in a Flash
Hiroaki Mikami, Hisahiro Suganuma, Pongsakorn U-chupala +2
Scaling the distributed deep learning to a massive GPU cluster level is challenging due to the instability of the large mini-batch training and the overhead of the gradient synchro…