Go wider instead of deeper F Xue, Z Shi, F Wei, Y Lou, Y Liu, Y You AAAI'22, 2021 | 79 | 2021 |
Whale: Efficient Giant Model Training over Heterogeneous GPUs X Jia, L Jiang, A Wang, W Xiao, Z Shi, J Zhang, X Li, Y Li, Z Zheng, X Liu, ... USENIX Annual Technical Conference 2022 (ATC'22), 2022 | 53 | 2022 |
A Collision-Free Path Planning Algorithm for Unmanned Aerial Vehicle Delivery Z Shi, WK Ng International Conference on Unmanned Aircraft Systems, 2018 | 23 | 2018 |
Domain adaptation for degraded remote scene classification J Yang, H Chen, Y Xu, Z Shi, R Luo, L Xie, R Su 2020 16th International Conference on Control, Automation, Robotics and …, 2020 | 14 | 2020 |
Auto-parallelizing large models with rhino: A systematic approach on production ai platform S Zhang, L Diao, S Wang, Z Cao, Y Gu, C Si, Z Shi, Z Zheng, C Wu, W Lin arXiv preprint arXiv:2302.08141, 2023 | 5 | 2023 |
TAP: Efficient Derivation of Tensor Parallel Plans for Large Neural Networks Z Shi, L Jiang, A Wang, J Zhang, X Jia, Y Li, C Wu, J Li, W Lin Architecture and System Support for Transformer Models (ASSYST@ ISCA 2023), 0 | 2* | |
ParaGAN: A Scalable Distributed Training Framework for Generative Adversarial Networks Z Shi, J Li, Y You ACM Symposium on Cloud Computing (SoCC’24), 2024 | 1 | 2024 |
ROAM: memory-efficient large DNN training via optimized operator ordering and memory layout H Shu, A Wang, Z Shi, H Zhao, Y Li, L Lu arXiv preprint arXiv:2310.19295, 2023 | 1 | 2023 |