| DAPPLE: A pipelined data parallel approach for training large models S Fan, Y Rong, C Meng, Z Cao, S Wang, Z Zheng, C Wu, G Long, J Yang, ... Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of …, 2021 | 235 | 2021 |
| Efficient pipeline planning for expedited distributed dnn training Z Luo, X Yi, G Long, S Fan, C Wu, J Yang, W Lin IEEE INFOCOM 2022-IEEE Conference on Computer Communications, 340-349, 2022 | 17 | 2022 |
| Auto-MAP: A DQN framework for exploring distributed execution plans for DNN workloads S Wang, Y Rong, S Fan, Z Zheng, LS Diao, G Long, J Yang, X Liu, W Lin arXiv preprint arXiv:2007.04069, 2020 | 8 | 2020 |
| Parallelizing machine learning optimization algorithms on distributed data-parallel platforms with parameter server R Gu, S Fan, Q Hu, C Yuan, Y Huang 2018 IEEE 24th International Conference on Parallel and Distributed Systems …, 2018 | 8 | 2018 |
| Optimizing DNN compilation for distributed training with joint OP and tensor fusion X Yi, S Zhang, L Diao, C Wu, Z Zheng, S Fan, S Wang, J Yang, W Lin IEEE Transactions on Parallel and Distributed Systems 33 (12), 4694-4706, 2022 | 5 | 2022 |
| iPLAR: Towards Interactive Programming with Parallel Linear Algebra in R Z Wang, S Fan, R Gu, C Yuan, Y Huang Algorithms and Architectures for Parallel Processing: 15th International …, 2015 | 1 | 2015 |
| Upcycling Large Language Models into Mixture of Experts BC Ethan He, Abhinav Khattar, Ryan Prenger, Vijay Korthikanti, Zijie Yan ... https://arxiv.org/abs/2410.07524, 2024 | | 2024 |
Chuan WuProfessor of Computer Science, The University of Hong KongПідтверджена електронна адреса в cs.hku.hk
