Xupeng Miao

Selected Publications

1. ASPLOS

   SpotServe: Serving Generative Large Language Models on Preemptible Instances (Distinguished Artifact Award)

   Xupeng Miao, Chunan Shi, Jiangfei Duan,  Xiaoli Xi and 3 more authors

   Proceedings of ASPLOS Conference 2024

   arXiv Bib

   @article{miao24spotserve,
     title = {SpotServe: Serving Generative Large Language Models on Preemptible Instances},
     author = {Miao, Xupeng and Shi, Chunan and Duan, Jiangfei and Xi, Xiaoli and Lin, Dahua and Cui, Bin and Jia, Zhihao},
     journal = {Proceedings of ASPLOS Conference},
     year = {2024},
   }

2. ASPLOS

   SpecInfer: Accelerating Generative Large Language Model Serving with Speculative Inference and Token Tree Verification

   Xupeng Miao, Gabriele Oliaro, Zhihao Zhang,  Xinhao Cheng and 10 more authors

   Proceedings of ASPLOS Conference 2024

   arXiv Bib

   @article{miao23specinfer,
     title = {SpecInfer: Accelerating Generative Large Language Model Serving with Speculative Inference and Token Tree Verification},
     author = {Miao, Xupeng and Oliaro, Gabriele and Zhang, Zhihao and Cheng, Xinhao and Wang, Zeyu and Wong, Rae Ying Yee and Zhu, Alan and Yang, Lijie and Shi, Xiaoxiang and Shi, Chunan and Chen, Zhuoming and Arfeen, Daiyaan and Abhyankar, Reyna and Jia, Zhihao},
     journal = {Proceedings of ASPLOS Conference},
     year = {2024},
     doi = {10.48550/arXiv.2305.09781},
   }

3. NSDI

   Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances

   Jiangfei Duan¹, Ziang Song¹,  Xupeng Miao¹,  Xiaoli Xi and 4 more authors

   Proceedings of NSDI Conference 2024

   arXiv Bib

   @article{nsdi24parcae,
     title = {Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances},
     author = {Duan, Jiangfei and Song, Ziang and Miao, Xupeng and Xi, Xiaoli and Lin, Dahua and Xu, Harry and Zhang, Minjia and Jia, Zhihao},
     journal = {Proceedings of NSDI Conference},
     cofirst = {true},
     year = {2024},
   }

4. VLDB

   SDPipe: A Semi-Decentralized Framework for Heterogeneity-aware Pipeline-parallel Training

   Xupeng Miao, Yining Shi, Zhi Yang,  Bin Cui and 1 more author

   Proc. VLDB Endow. 2023

   Bib

   @article{miao2023sdpipe,
     title = {SDPipe: A Semi-Decentralized Framework for Heterogeneity-aware Pipeline-parallel Training},
     author = {Miao, Xupeng and Shi, Yining and Yang, Zhi and Cui, Bin and Jia, Zhihao},
     journal = {Proc. {VLDB} Endow.},
     volume = {16},
     year = {2023},
     publisher = {VLDB Endowment},
   }

5. VLDB

   Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism

   Xupeng Miao, Yujie Wang, Youhe Jiang,  Chunan Shi and 3 more authors

   Proc. VLDB Endow. 2023

   Bib PDF

   @article{miao2023galvatron,
     title = {Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism},
     author = {Miao, Xupeng and Wang, Yujie and Jiang, Youhe and Shi, Chunan and Nie, Xiaonan and Zhang, Hailin and Cui, Bin},
     journal = {Proc. {VLDB} Endow.},
     volume = {16},
     number = {3},
     pages = {470--479},
     year = {2023},
     doi = {10.14778/3570690.3570697},
     publisher = {VLDB Endowment},
   }

6. VLDB

   HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework (Best Scalable Data Science Paper Award)

   Xupeng Miao, Hailin Zhang, Yining Shi,  Xiaonan Nie and 3 more authors

   Proc. VLDB Endow. 2022

   Bib PDF

   @article{miao2021het,
     title = {{HET:} Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework},
     author = {Miao, Xupeng and Zhang, Hailin and Shi, Yining and Nie, Xiaonan and Yang, Zhi and Tao, Yangyu and Cui, Bin},
     journal = {Proc. {VLDB} Endow.},
     volume = {15},
     number = {2},
     pages = {312--320},
     year = {2022},
     publisher = {VLDB Endowment},
   }

7. SIGMOD

   HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training

   Xupeng Miao, Yining Shi, Hailin Zhang,  Xin Zhang and 3 more authors

   In Proceedings of SIGMOD Conference 2022

   Bib PDF

   @inproceedings{miao2022hetgmp,
     author = {Miao, Xupeng and Shi, Yining and Zhang, Hailin and Zhang, Xin and Nie, Xiaonan and Yang, Zhi and Cui, Bin},
     title = {{HET-GMP:} {A} Graph-based System Approach to Scaling Large Embedding Model Training},
     booktitle = {Proceedings of SIGMOD Conference},
     pages = {470--480},
     publisher = {{ACM}},
     year = {2022},
     doi = {10.1145/3514221.3517902},
   }

8. SIGMOD

   Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce

   Xupeng Miao, Xiaonan Nie, Yingxia Shao,  Zhi Yang and 3 more authors

   In Proceedings of SIGMOD Conference 2021

   Bib PDF

   @inproceedings{DBLP:conf/sigmod/MiaoNSYJM021,
     author = {Miao, Xupeng and Nie, Xiaonan and Shao, Yingxia and Yang, Zhi and Jiang, Jiawei and Ma, Lingxiao and Cui, Bin},
     title = {Heterogeneity-Aware Distributed Machine Learning Training via Partial
                    Reduce},
     booktitle = {Proceedings of SIGMOD Conference},
     pages = {2262--2270},
     publisher = {{ACM}},
     year = {2021},
     doi = {10.1145/3448016.3452773},
   }