| Characterization and Prediction of Deep Learning Workloads in Large-Scale GPU Datacenters Q Hu, P Sun, S Yan, Y Wen, T Zhang Proceedings of the International Conference for High Performance Computing …, 2021 | 137 | 2021 |
| Deep learning workload scheduling in gpu datacenters: Taxonomy, challenges and vision W Gao, Q Hu, Z Ye, P Sun, X Wang, Y Luo, T Zhang, Y Wen arXiv preprint arXiv:2205.11913, 2022 | 35 | 2022 |
| Characterization of large language model development in the datacenter Q Hu, Z Ye, Z Wang, G Wang, M Zhang, Q Chen, P Sun, D Lin, X Wang, ... 21st USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2024 | 32 | 2024 |
| Longvila: Scaling long-context visual language models for long videos F Xue, Y Chen, D Li, Q Hu, L Zhu, X Li, Y Fang, H Tang, S Yang, Z Liu, ... arXiv preprint arXiv:2408.10188, 2024 | 29 | 2024 |
| Lucid: A non-intrusive, scalable and interpretable scheduler for deep learning training jobs Q Hu, M Zhang, P Sun, Y Wen, T Zhang Proceedings of the 28th ACM International Conference on Architectural …, 2023 | 25 | 2023 |
| Deep learning workload scheduling in gpu datacenters: A survey Z Ye, W Gao, Q Hu, P Sun, X Wang, Y Luo, T Zhang, Y Wen ACM Computing Surveys 56 (6), 1-38, 2024 | 21 | 2024 |
| Deltazip: Multi-tenant language model serving via delta compression X Yao, A Klimovic arXiv preprint arXiv:2312.05215, 2023 | 11 | 2023 |
| Loongtrain: Efficient training of long-sequence llms with head-context parallelism D Gu, P Sun, Q Hu, T Huang, X Chen, Y Xiong, G Wang, Q Chen, S Zhao, ... arXiv preprint arXiv:2406.18485, 2024 | 10 | 2024 |
| Hydro:{Surrogate-Based} Hyperparameter Tuning Service in Datacenters Q Hu, Z Ye, M Zhang, Q Chen, P Sun, Y Wen, T Zhang 17th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2023 | 9 | 2023 |
| FedDSE: Distribution-aware Sub-model Extraction for Federated Learning over Resource-constrained Devices H Wang, Y Jia, M Zhang, Q Hu, H Ren, P Sun, Y Wen, T Zhang Proceedings of the ACM on Web Conference 2024, 2902-2913, 2024 | 7 | 2024 |
| Internevo: Efficient long-sequence large language model training via hybrid parallelism and redundant sharding Q Chen, D Gu, G Wang, X Chen, YT Xiong, T Huang, Q Hu, X Jin, Y Wen, ... arXiv preprint arXiv:2401.09149, 2024 | 7 | 2024 |
| Boosting distributed full-graph gnn training with asynchronous one-bit communication M Zhang, Q Hu, P Sun, Y Wen, T Zhang arXiv preprint arXiv:2303.01277, 2023 | 7 | 2023 |
| Efficient training of large language models on distributed infrastructures: a survey J Duan, S Zhang, Z Wang, L Jiang, W Qu, Q Hu, G Wang, Q Weng, H Yan, ... arXiv preprint arXiv:2407.20018, 2024 | 5 | 2024 |
| Primo: Practical Learning-Augmented Systems with Interpretable Models Q Hu, H Nori, P Sun, Y Wen, T Zhang 2022 USENIX Annual Technical Conference (USENIX ATC 22), 519-538, 2022 | 4 | 2022 |
| Sylvie: 3d-adaptive and universal system for large-scale graph neural network training M Zhang, Q Hu, C Wan, H Wang, P Sun, Y Wen, T Zhang 2024 IEEE 40th International Conference on Data Engineering (ICDE), 3823-3836, 2024 | 2 | 2024 |
| AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning Q Chen, Q Hu, Z Ye, G Wang, P Sun, Y Wen, T Zhang arXiv preprint arXiv:2311.00257, 2023 | 1 | 2023 |
| TorchGT: A Holistic System for Large-Scale Graph Transformer Training M Zhang, J Sun, Q Hu, P Sun, Z Wang, Y Wen, T Zhang SC24: International Conference for High Performance Computing, Networking …, 2024 | | 2024 |
| Lins: Reducing Communication Overhead of ZeRO for Efficient LLM Training Q Chen, Q Hu, G Wang, Y Xiong, T Huang, X Chen, Y Gao, H Yan, Y Wen, ... 2024 IEEE/ACM 32nd International Symposium on Quality of Service (IWQoS), 1-10, 2024 | | 2024 |
| Building efficient and practical machine learning systems Q Hu Nanyang Technological University, 2023 | | 2023 |
| Understanding the Workload Characteristics of Large Language Model Development Q Hu, P Sun, T Zhang | | |
Tianwei ZhangNanyang Technological UniversityVerified email at ntu.edu.sg