2 papers
cs.CL2024
AquilaMoE: Efficient Training for MoE Models with Scale-Up and Scale-Out Strategies
Bo-Wen Zhang, Liangdong Wang, Ye Yuan +24
In recent years, with the rapid application of large language models across various fields, the scale of these models has gradually increased, and the resources required for their…
cs.DC2021
End-to-end Adaptive Distributed Training on PaddlePaddle
Yulong Ao, Zhihua Wu, Dianhai Yu +10
Distributed training has become a pervasive and effective approach for training a large neural network (NN) model with processing massive data. However, it is very challenging to s…