Bingyang Wu

Bingyang Wu

Ph.D. Candidate

Peking University

I am a Ph.D. candidate in the School of Computer Science at Peking University, advised by Xin Jin. Before that, I received my B.S. degree (Summa Cum Laude) in computer science from Turing Class, Peking University. My research interests include machine learning systems, video conferencing, and cloud computing.

Education

  • Peking University

    Ph.D. in Computer Software and Theory

    2022 - Present

  • Peking University

    B.S. (Summa Cum Laude) in Computer Science and Technology

    2018 - 2022

Experience

  • Meituan

    Research Intern, Jun. 2024 - Oct. 2024

  • Shanghai AI Lab, NDS Group

    Research Intern, Oct. 2023 - Jun. 2024

  • Alibaba, DAMO Academy

    Research Intern, Nov. 2021 - Sept. 2023

  • Tencent, TEG

    Research Intern, Apr. 2021 - Jun. 2021

Publications

LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence Parallelism.
Bingyang Wu, Shengyu Liu, Yinmin Zhong, Peng Sun, Xuanzhe Liu, Xin Jin

In SOSP 2024. Cite

RLHFuse: Efficient RLHF Training for Large Language Models with Inter- and Intra-Stage Fusion.
Yinmin Zhong, Zili Zhang, Bingyang Wu, Shengyu Liu, Yukun Chen, Changyi Wan, Hanpeng Hu, Lei Xia, Ranchen Ming, Yibo Zhu, Xin Jin

In Preprint. PDF Cite

dLoRA: Dynamically Orchestrating Requests and Adapters for LoRA LLM Serving.
Bingyang Wu, Ruidong Zhu, Zili Zhang, Peng Sun, Xuanzhe Liu, Xin Jin

In OSDI 2024. PDF Cite

A Survey of Resource-efficient LLM and Multimodal Foundation Models.
Mengwei Xu, Wangsong Yin, Dongqi Cai, Rongjie Yi, Daliang Xu, Qipeng Wang, Bingyang Wu, Yihao Zhao, Chen Yang, Shihe Wang, Qiyang Zhang, Zhenyan Lu, Li Zhang, Shangguang Wang, Yuanchun Li, Yunxin Liu, Xin Jin, Xuanzhe Liu

In Preprint. PDF Cite DOI

XRON: A Hybrid Elastic Cloud Overlay Network for Video Conferencing at Planetary Scale.
Bingyang Wu, Kun Qian, Bo Li, Yunfei Ma, Qi Zhang, Zhigang Jiang, Jiayu Zhao, Dennis Cai, Ennan Zhai, Xuanzhe Liu, Xin Jin

In SIGCOMM 2023. PDF Cite DOI

Fast Distributed Inference Serving for Large Language Models.
Bingyang Wu, Yinmin Zhong, Zili Zhang, Gang Huang, Xuanzhe Liu, Xin Jin

In Preprint. PDF Cite DOI

Transparent GPU Sharing in Container Clouds for Deep Learning Workloads.
Bingyang Wu, Zili Zhang, Zhihao Bai, Xuanzhe Liu, Xin Jin

In NSDI 2023. PDF Cite

AMOS: Enabling Automatic Mapping for Tensor Computations On Spatial Accelerators with Hardware Abstraction.
Size Zheng, Renze Chen, Anjiang Wei, Yicheng Jin, Qin Han, Liqiang Lu, Bingyang Wu, Xiuhong Li, Shengen Yan, Yun Liang

In ISCA 2022. PDF Cite DOI

NeoFlow: A Flexible Framework for Enabling Efficient Compilation for High Performance DNN Training.
Size Zheng, Renze Chen, Yicheng Jin, Anjiang Wei, Bingyang Wu, Xiuhong Li, Shengen Yan, Yun Liang

In TPDS 2021. PDF Cite DOI