Xupeng Miao
Email: xupeng@cmu.edu
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.
I’m on the academic job market for 2024. Please feel free to reach out if you have openings.
news
Apr 24, 2024 | We will lanuch a tutorial on efficient LLM serving in ICML 2024. |
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Apr 23, 2024 | I was invited to give a talk at the ASPLOS’24 XTensor workshop. |
Apr 4, 2024 | I was invited to give a talk at the MLSys’24 Young Professionals Symposium. |
Feb 29, 2024 | SpecInfer was accepted by ASPLOS 2024. |
Feb 28, 2024 | SpotServe has been selected for the Distinguished Artifact Award at ASPLOS 2024! |
Feb 2, 2024 | We will lanuch a tutorial on data managment for LLM in SIGMOD 2024. |
Dec 23, 2023 | We announce a survey about efficient generative LLM serving on arXiv. |
Dec 7, 2023 | One paper on distributed training over spot instances was accepted by NSDI 2024. |
Nov 7, 2023 | One paper about LLM serving over preemptive instances was accepted by ASPLOS 2024. |
May 16, 2023 | We announce the first speculative LLM inference engine called SpecInfer. |
May 13, 2023 | Three papers were accepted by VLDB 2023. |
Mar 23, 2023 | One paper was accepted by OSDI 2023. |
Jan 30, 2023 | I was grateful to be awared 2022 ACM China Doctoral Dissertation Award. |
selected publications
- NSDIParcae: Proactive, Liveput-Optimized DNN Training on Preemptible InstancesProceedings of NSDI Conference 2024
- VLDBSDPipe: A Semi-Decentralized Framework for Heterogeneity-aware Pipeline-parallel TrainingProc. VLDB Endow. 2023