Xiaonan Nie

Orcid: 0000-0001-6766-757X

According to our database1, Xiaonan Nie authored at least 13 papers between 2021 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2023
Hetu: a highly efficient automatic parallel distributed deep learning system.
Sci. China Inf. Sci., January, 2023

Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent.
Proc. VLDB Endow., 2023

FlexMoE: Scaling Large-scale Sparse Pre-trained Model Training via Dynamic Device Placement.
Proc. ACM Manag. Data, 2023

Improving Automatic Parallel Training via Balanced Memory Workload Optimization.
CoRR, 2023

OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022
Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism.
Proc. VLDB Endow., 2022

OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning.
CoRR, 2022

HetuMoE: An Efficient Trillion-scale Mixture-of-Expert Distributed Training System.
CoRR, 2022

HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training.
Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

TSPLIT: Fine-grained GPU Memory Management for Efficient DNN Training via Tensor Splitting.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021
HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework.
Proc. VLDB Endow., 2021

Dense-to-Sparse Gate for Mixture-of-Experts.
CoRR, 2021

Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021


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