| Aligraph: A comprehensive graph neural network platform R Zhu, K Zhao, H Yang, W Lin, C Zhou, B Ai, Y Li, J Zhou arXiv preprint arXiv:1902.08730, 2019 | 374* | 2019 |
| {MLaaS} in the wild: Workload analysis and scheduling in {Large-Scale} heterogeneous {GPU} clusters Q Weng, W Xiao, Y Yu, W Wang, C Wang, J He, Y Li, L Zhang, W Lin, ... 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2022 | 165 | 2022 |
| {AntMan}: Dynamic scaling on {GPU} clusters for deep learning W Xiao, S Ren, Y Li, Y Zhang, P Hou, Z Li, Y Feng, W Lin, Y Jia 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2020 | 151 | 2020 |
| M6: A chinese multimodal pretrainer J Lin, R Men, A Yang, C Zhou, M Ding, Y Zhang, P Wang, A Wang, ... arXiv preprint arXiv:2103.00823, 2021 | 126 | 2021 |
| GraphScope: a unified engine for big graph processing W Fan, T He, L Lai, X Li, Y Li, Z Li, Z Qian, C Tian, L Wang, J Xu, Y Yao, ... Proceedings of the VLDB Endowment 14 (12), 2879-2892, 2021 | 39 | 2021 |
| Fleetrec: Large-scale recommendation inference on hybrid gpu-fpga clusters W Jiang, Z He, S Zhang, K Zeng, L Feng, J Zhang, T Liu, Y Li, J Zhou, ... Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 33 | 2021 |
| Flash-llm: Enabling cost-effective and highly-efficient large generative model inference with unstructured sparsity H Xia, Z Zheng, Y Li, D Zhuang, Z Zhou, X Qiu, Y Li, W Lin, SL Song arXiv preprint arXiv:2309.10285, 2023 | 13 | 2023 |
| Structure enhanced graph neural networks for link prediction B Ai, Z Qin, W Shen, Y Li arXiv preprint arXiv:2201.05293, 2022 | 12 | 2022 |
| ugrapher: High-performance graph operator computation via unified abstraction for graph neural networks Y Zhou, J Leng, Y Song, S Lu, M Wang, C Li, M Guo, W Shen, Y Li, W Lin, ... Proceedings of the 28th ACM International Conference on Architectural …, 2023 | 11 | 2023 |
| Accl: Architecting highly scalable distributed training systems with highly efficient collective communication library J Dong, S Wang, F Feng, Z Cao, H Pan, L Tang, P Li, H Li, Q Ran, Y Guo, ... IEEE Micro 41 (5), 85-92, 2021 | 7 | 2021 |
| Goldminer: Elastic scaling of training data pre-processing pipelines for deep learning H Zhao, Z Yang, Y Cheng, C Tian, S Ren, W Xiao, M Yuan, L Chen, K Liu, ... Proceedings of the ACM on Management of Data 1 (2), 1-25, 2023 | 3 | 2023 |
| 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 | | 2023 |
| Whale: Scaling Deep Learning Model Training to the Trillions Z Zheng, X Liu, W Lin | | |
Wencong XiaoAlibaba GroupVerified email at alibaba-inc.com
