Xupeng Miao

Email: xupeng@cmu.edu

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Xupeng Miao is currently a Post Doctoral Fellow working with Prof. Zhihao Jia and Prof. Tianqi Chen in Catalyst Group and Parallel Data Lab at Computer Science Department of Carnegie Mellon University. He is broadly interested in machine learning systems, data management and distributed computing. He is the creator of Hetu, a highly efficient distributed deep learning system, and continuously leading the team development, welcome to join us!

Before that, he received his Ph.D. degree in computer science from Peking University in June 2022, supervised by Prof. Bin Cui. He was a research intern in System Research Group of Microsoft Research Asia (MSRA), supervised by Dr. Jilong Xue. Besides, he has accumulated for more than 5 years industrial internship experience at the Machine Learning & Data Platform Department of Tencent.

news

Mar 23, 2023 One paper was accepted by OSDI 2023. :tada:
Mar 17, 2023 One paper was accepted by VLDB 2023. :tada:
Jan 30, 2023 I was grateful to be awared 2022 ACM China Doctoral Dissertation Award. :confetti_ball:
Oct 16, 2022 One paper was accepted by VLDB 2023. :tada:
Oct 10, 2022 One paper was accepted by VLDBJ. :tada:

selected publications

  1. 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
  2. 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
  3. SCIS
    Hetu: A highly efficient automatic parallel distributed deep learning system
    Xupeng Miao, Xiaonan Nie, Hailin Zhang,  Tong Zhao and 1 more author
    Sci. China Inf. Sci. 2022
  4. VLDB
    HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework (Best Scalable Data Science Paper)
    Xupeng Miao, Hailin Zhang, Yining Shi,  Xiaonan Nie and 3 more authors
    Proc. VLDB Endow. 2022
  5. 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
  6. 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