Invited talks and presentations
Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism.
- ChinaSys Fall, Online, China, December 2022
- Jiqizhixin, Online, China, January 2023
When Sparsity Meets Distributed DL System: Efficient and Scalable Huge Embedding Model Training.
- Catalyst Group Meeting, Pittsburgh, USA, October 2022
- Tencent, Online, China, September 2022
- Baidu, OPPO, MetaX, Online, China, April 2022
- Jiqizhixin, Online, China, January 2022
Hetu: An Automatic Parallel Distributed Deep Learning Framework for Huge Model.
- BAAI Conference, Beijing, China, June 2022
- MSRA, Beijing, China, November 2021
- NDBC, Kunming, China, December 2019
HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework.
- VLDB, Sydney, Australia, September 2022
- ChinaSys Winter, Xiamen, China, December 2021
- Huawei, Alibaba, ByteDance, October 2021
Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce.
- SIGMOD, Xiaan, China, June 2021
DeGNN: Improving Graph Neural Networks with Graph Decomposition.
- SIGKDD, Online, August 2021