Ziming Liu 🚀
Ziming Liu 子铭刘

Ph.D. Candidate

National University of Singapore

About Me

Hi, I am a second-year CS Ph.D. candidate at NUS, supervised by Prof. Yang You and work as a member of HPC-AI lab. I received my bachelor’s degree of computer science and engineering at Peking University in 2020, supervised by Prof. Tong Yang. Previously I was an intern at Microsoft Research, supervised by Dr. Zhenhua Han and Dr. Yuqing Yang.

My research interest is machine learning system and high performance computing. I have been working on pipeline parallelism and sequence parallelism in deep learning training, and I am currently digging into sparse inference and training of deep learning models. I am looking forward to collaborations and research internship opportunities, so please feel free to reach out to me if you are interested in my research.

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Interests
  • Machine Learning System
  • High Performance Computing
  • Distributed Training & Inference
  • Sparse Inference & Training
Education

  • PhD Computer Science

    National University of Singapore

  • Msc Artificial Intelligence

    National University of Singapore

  • BSc Computer Science

    Peking University

Recent News

2024.12.09 Awarded the "Stars of Tomorrow" Certificate from MSRA (top 10% intern).

2024.11.12 One paper accepted by PPoPP 2025.

2024.10.03 One paper accepted by ASPLOS '25.

2024.06.27 Awarded the SoC Teaching Fellowship (3 out of all NUS CS PhD).

2024.04.30 Joined Microsoft Research as a research intern.

2024.02.16 One paper accepted by MLSYS 2024.

2024.01.15 One paper accepted by ICLR '24.

2023.06.17 One paper accepted by SC '23.

2023.01.07 Started my PhD career.

Experience

  1. Research Intern

    Microsoft Research
    Working on sparse inference and training of text-to-image and text-to-video models. Supervised by Dr. Zhenhua Han and Dr. Yuqing Yang. Awarded the “Stars of Tomorrow” Certificate from MSRA (top 10% intern).

  2. Research Intern

    HPC-AI Tech

    Responsibilities include:

    • Developing the efficient LLM inference system EnergonAI.
    • Optimizing the implementation of ColossalAI.

  3. Machine Learning Engineer

    ByteDance
    NLP algorithm engineer at Lark, ByteDance.

Education

  1. PhD Computer Science

    National University of Singapore
    Working on Machine Learning System, supervised by Presidential Young Professor Yang You.

  2. Msc Artificial Intelligence

    National University of Singapore

  3. BSc Computer Science

    Peking University
    Bacholor’s degree of computer science and engineering. Supervised by Prof. Tong Yang.
Featured Publications
WeiPipe: Weight Pipeline Parallelism for Communication-Effective Long-Context Large Model Training
WallFacer: Harnessing Multi-dimensional Ring Parallelism for Efficient Long Sequence Model Training
Hanayo: Harnessing Wave-like Pipeline Parallelism for Enhanced Large Model Training Efficiency
Recent Publications
Junfeng Lin*, Ziming Liu*, Yang You, Jun Wang, Weihao Zhang, Rong Zhao (2024). WeiPipe: Weight Pipeline Parallelism for Communication-Effective Long-Context Large Model Training. To appear on PPoPP 2025. *:Equal Contribution.
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Shenggan Cheng, Shengjie Lin, Lansong Diao, Hao Wu, Siyu Wang, Chang Si, Ziming Liu, Xuanlei Zhao, Jiangsu Du, Wei Lin, Yang You (2024). Concerto: Automatic Communication Optimization and Scheduling for Large-Scale Deep Learning. To appear on ASPLOS 2025.
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Ziming Liu, Shaoyu Wang, Shenggan Cheng, Zhongkai Zhao, Kai Wang, Xuanlei Zhao, James Demmel, Yang You (2024). WallFacer: Harnessing Multi-dimensional Ring Parallelism for Efficient Long Sequence Model Training. Arxiv Preprint.
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Xuanlei Zhao, Bin Jia, Haotian Zhou, Ziming Liu, Shenggan Cheng, Yang You (2024). HeteGen: Efficient Heterogeneous Parallel Inference for Large Language Models on Resource-Constrained Devices. In MLSys 2024, Proceedings of Machine Learning and Systems.
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Xuanlei Zhao, Shenggan Cheng, Guangyang Lu, Jiarui Fang, Haotian Zhou, Bin Jia, Ziming Liu, Yang You (2024). AutoChunk: Automated Activation Chunk for Memory-Efficient Long Sequence Inference. In ICLR 2024, International Conference on Learning Representations.
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Xuanlei Zhao, Shenggan Cheng, Zangwei Zheng, Zheming Yang, Ziming Liu, Yang You (2024). DSP: Dynamic Sequence Parallelism for Multi-Dimensional Transformers. Arxiv Preprint.
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Ziming Liu*, Shenggan Cheng*, Haotian Zhou, Yang You (2023). Hanayo: Harnessing Wave-like Pipeline Parallelism for Enhanced Large Model Training Efficiency. In SC ‘23, Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. *:Equal Contribution.
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Shenggan Cheng, Ziming Liu, Jiangsu Du, Yang You (2023). ATP: Adaptive Tensor Parallelism for Foundation Models. Arxiv Preprint.
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Jiangsu Du, Ziming Liu, Jiarui Fang, Shenggui Li, Yongbin Li, Yutong Lu, Yang You (2022). EnergonAI: An Inference System for 10-100 Billion Parameter Transformer Models. Arxiv Preprint.
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