activity
20192023
most citedERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation

195 citations · 382 across the 14 of their papers we have counts for

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Showing cs.DCShow all

5 papers · 1 filter

cs.DC2022

Efficient AlphaFold2 Training using Parallel Evoformer and Branch Parallelism

Guoxia Wang, Zhihua Wu, Xiaomin Fang +4

The accuracy of AlphaFold2, a frontier end-to-end structure prediction system, is already close to that of the experimental determination techniques. Due to the complex model archi…

cs.DC2022★ 4 cited

Boosting Distributed Training Performance of the Unpadded BERT Model

Jinle Zeng, Min Li, Zhihua Wu +4

Pre-training models are an important tool in Natural Language Processing (NLP), while the BERT model is a classic pre-training model whose structure has been widely adopted by foll…

cs.DC2022★ 30 cited

HelixFold: An Efficient Implementation of AlphaFold2 using PaddlePaddle

Guoxia Wang, Xiaomin Fang, Zhihua Wu +6

Accurate protein structure prediction can significantly accelerate the development of life science. The accuracy of AlphaFold2, a frontier end-to-end structure prediction system, i…

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…

cs.DC2021★ 6 cited

HeterPS: Distributed Deep Learning With Reinforcement Learning Based Scheduling in Heterogeneous Environments

Ji Liu, Zhihua Wu, Dianhai Yu +6

Deep neural networks (DNNs) exploit many layers and a large number of parameters to achieve excellent performance. The training process of DNN models generally handles large-scale…