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Liangyu Zhao

赵亮雨

Ph.D. Student
Paul G. Allen School of Computer Science & Engineering
University of Washington
[myfirstname]@cs.washington.edu


About Me

I am a fourth-year Ph.D. student in the Paul G. Allen School of Computer Science & Engineering at the University of Washington, advised by Prof. Arvind Krishnamurthy. I also completed my undergraduate studies at the University of Washington, earning a B.S. in Computer Science and a B.S. in Applied & Computational Mathematical Sciences (Discrete Math and Algorithms).

My CV can be found here.

Research Interests

Machine learning systems, distributed systems, collective communications; broadly speaking, I am interested in formulating and solving mathematical problems in computer systems and networking.

News

Publications

  1. ForestColl: Efficient Collective Communications on Heterogeneous Network Fabrics
    Liangyu Zhao, Saeed Maleki, Aashaka Shah, Ziyue Yang, Hossein Pourreza, Arvind Krishnamurthy
    arXiv preprint, in submission
    arXiv PDF Code Slides

  2. NanoFlow: Towards Optimal Large Language Model Serving Throughput
    Kan Zhu, Yilong Zhao, Liangyu Zhao, Gefei Zuo, Yile Gu, Dedong Xie, Yufei Gao, Qinyu Xu, Tian Tang, Zihao Ye, Keisuke Kamahori, Chien-Yu Lin, Stephanie Wang, Arvind Krishnamurthy, Baris Kasikci
    arXiv preprint, in submission
    arXiv PDF Code

  3. Efficient Direct-Connect Topologies for Collective Communications
    Liangyu Zhao, Siddharth Pal, Tapan Chugh, Weiyang Wang, Jason Fantl, Prithwish Basu, Joud Khoury, Arvind Krishnamurthy
    USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2025.
    arXiv PDF Talk Slides

  4. Rethinking Machine Learning Collective Communication as a Multi-Commodity Flow Problem
    Xuting Liu, Behnaz Arzani, Siva Kesava Reddy Kakarla, Liangyu Zhao, Vincent Liu, Miguel Castro, Srikanth Kandula, Luke Marshall
    ACM Special Interest Group on Data Communication (SIGCOMM), 2024.
    PDF Code

  5. Efficient all-to-all Collective Communication Schedules for Direct-connect Topologies
    Prithwish Basu, Liangyu Zhao, Jason Fantl, Siddharth Pal, Arvind Krishnamurthy, Joud Khoury
    International Symposium on High-Performance Parallel and Distributed Computing (HPDC), 2024.
    PDF

  6. AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly
    Yuchen Jin, Tianyi Zhou, Liangyu Zhao, Yibo Zhu, Chuanxiong Guo, Marco Canini, Arvind Krishnamurthy
    International Conference on Learning Representations (ICLR), 2021.
    PDF Code

  7. Nexus: A GPU Cluster Engine for Accelerating DNN-Based Video Analysis
    Haichen Shen, Lequn Chen, Yuchen Jin, Liangyu Zhao, Bingyu Kong, Matthai Philipose, Arvind Krishnamurthy, Ravi Sundaram
    ACM Symposium on Operating Systems Principles (SOSP), 2019.
    PDF Code

Recorded Talks

  1. Efficient Direct-Connect Topologies for Collective Communications
    FOCI Annual Symposium
    University of Washington, October 2023
    Video Slides


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