About Me

I'm a Ph.D. student at Zhiyuan Honors Program at Shanghai Jiao Tong University , majored in Computer Science. I am a member of APEX Lab, advised by Prof. Weinan Zhang and Prof. Yong Yu.

I am a PMC member of Apache TVM, working closely with Tianqi Chen. I am working on TVM and MLC-LLM, enabling deploy LLMs on diverse hardware backends.

My research interests include machine learning compiler and machine learning system.

Education

Shanghai Jiao Tong University

Ph.D. in Computer Science 2020 - Present

Ph.D. Candidates in Computer Science at School of Electronic, Information and Electrical Engineering

Research Area: Machine Learning System, Machine Learning Compiler

University of Washington

Research Intern 2019

Research Intern at SAMPL advised by Prof. Tianqi Chen and Prof. Luis Ceze

Shanghai Jiao Tong University

B.Sc. in Computer Science 2016 - 2020

I'm a member of ACM Honors Class, Zhiyuan Collage.

Zhiyuan Collage is a collage for training outstanding students in the basic sciences, while ACM Honors Class is an elite CS program for top 5% talented students.

Publications

Relax: Composable Abstractions for End-to-End Dynamic Machine Learning

Priprint 2023 [arXiv]

Ruihang Lai*, Junru Shao*, Siyuan Feng*, Steven S. Lyubomirsky*, Bohan Hou, Wuwei Lin, Zihao Ye, Hongyi Jin, Yuchen Jin, Jiawei Liu, Lesheng Jin, Yaxing Cai, Ziheng Jiang, Yong Wu, Sunghyun Park, Prakalp Srivastava, Jared Roesch, Todd C. Mowry, Tianqi Chen

TensorIR: An Abstraction for Automatic Tensorized Program Optimization

ASPLOS 2023 2023 [Paper]

Siyuan Feng*, Bohan Hou*, Hongyi Jin, Wuwei Lin, Junru Shao, Ruihang Lai, Zihao Ye, Lianmin Zheng, Cody Hao Yu, Yong Yu, Tianqi Chen

Effectively Scheduling Computational Graphs of Deep Neural Networks toward Their Domain-Specific Accelerators

OSDI 2023 2023 [Paper]

Jie Zhao, Siyuan Feng, Xiaoqiang Dan, Fei Liu, Chengke Wang, Sheng Yuan, Wenyuan Lv, Qikai Xie

Tensor Program Optimization with Probabilistic Programs

NeurIPS 2022 2022 [arXiv]

Junru Shao, Xiyou Zhou, Siyuan Feng, Bohan Hou, Ruihang Lai, Hongyi Jin, Wuwei Lin, Masahiro Masuda, Cody Hao Yu, and Tianqi Chen.

CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

WWW 2019 Demo May 2019 [arXiv]

Huichu Zhang, Siyuan Feng, Chang Liu, Yaoyao Ding, Yichen Zhu, Zihan Zhou, Weinan Zhang, Yong Yu, Haiming Jin, Zhenhui Li

Teaching

MLC: Machine Learning Compilation

Open Source Online Course Summer 2022 Course Page

  • One of the TAs of this course, while Tianqi Chen is the instructor.
  • The course teaches machine learning compilation with TVM Unity framework.

Apache TVM

https://github.com/apache/tvm

  • Open source machine learning compiler, enabling deployment models on diverse hardware backends
  • Leading TensorIR project, the next generation Tensor-level IR for tensor hardware
  • Co-leading TVM Unity/Relax project, the next generation Graph-level IR for dynamic models
  • Contributing to several key features: TVMScript, Meta-Schudule, runtime, frontend
  • Serving in Apache TVM Program Management Committee (PMC)

MLC-LLM

https://github.com/mlc-ai/mlc-llm

  • Compile LLMs and depoly models natively on every device
  • Supported hardware: NVIDIA GPU, AMD GPU, Apple GPU, mobile GPUs and Intel iGPU
  • Supported runtime: CUDA, ROCm, Metal, Vulkan, OpenCL, WebGPU
  • Support distributed inference for large models on CUDA and ROCm
  • Support LLM serving with OpenAI API compatibility

Web-LLM

https://github.com/mlc-ai/web-llm

  • Bringing large-language models and chat to web browsers with local GPU capabilities.
  • Leverage emerging WebGPU API to run LLMs inside the browser
  • Serving as a backend runtime of MLC-LLM