LeiWang1999

Introduction

He is currently a second year postgraduate student in University of Chinese Academy of Sciences UCAS, Institute of Computing Technology ICT. He is also a full-time research intern in System Research Group of Microsoft Research Asia(MSRA), advised by Dr. Jilong Xue and Dr. Lingxiao Ma.

And he is now focusing on :

• Sparse Tensor Computation
• on-device llm inference
• Opensoure Accelerator System Design
• CPU Fallback based on Tengine [slides] [recording]

He also enjoys writing technical posts and contributes to various open-source communities, including Microsoft NNFusion, Apache TVM, and Tengine etc.

LeiWang1999's Github Chart

Education

• University of Chinese Academy of Science
  Institute of Computing Technology
  Master in Computer Science(Aug. 2021 - Present)
  
• Nanjing Tech University
  Bachor in Electronic Engineering(Aug. 2017 - Jun. 2021)
  Overall GPA: 3.95/4.00
  Ranking: 1/59
  

Awards & Honors

• 2018 Chinese National Scholarship(Top 0.3%)
• 2021 Excellent New Student Award of Chinese Academy of Science
• Njtech Person of Year 2020

• First Price of 2019 NUEDC (Top 0.5%) (全国大学生电子设计竞赛)
• First Price of 2018 Electronic Design Competition of Province
• Third Price of Integrated Circuit Innovation and Entrepreneurship Competition (FPGA hardware Accelerator for digital recognition)
• Third prize of National FPGA Competition (FPGA based FOSDA Alogrithom Implementation)

Experience

• Netease Intelligent Hardware R&D Department
  Bei Jing, China
  NPU Development intern. (Sep. 2021 - Oct. 2021)
  
• Microsoft Research Asia
  Bei Jing, China
  Systems Research intern. (April. 2022 - now)
  

Publications

• Lin Bin*; Zheng Ningxin*; Wang Lei*; Cao Shijie; Ma Lingxiao; Zhang Quanlu; Zhu Yi; Cao Ting; Xue Jilong; Yang Yuqing; et al. Efficient GPU Kernels for N: M-Sparse Weights in Deep Learning. Proceedings of Machine Learning and Systems, MLSYS, 2023. (* represents co-first author) [paper]
• Sun Xiaotian; Wang Xinyu; Li Wanqian; Wang Lei; Han Yinhe; Chen Xiaoming. PIMCOMP: A Universal Compilation Framework for Crossbar-based PIM DNN Accelerators. 60th. Design Automation Conference, DAC, 2023. [paper]
• Lei Wang; Lingxiao Ma; Shijie Cao; Ningxin Zheng; Quanlu Zhang. Ladder: Efficient Tensor Compilation on Customized Data Format. 17th USENIX Symposium on Operating Systems Design and Implementation (Poster), OSDI, 2023.
• Yuetao Chen; Kun Li; Yuhao Wang; Donglin Bai; Lei Wang; Lingxiao Ma; Liang Yuan; Yunquan Zhang; Ting Cao; Mao Yang; ConvStencil: Transform Stencil Computation to Matrix Multiplication on Tensor Cores. Symposium on Principles and Practice of Parallel Programming, PPoPP, 2024.

Projects

• FPGA Accelerator for Digital Recognition, 2020

  Utilizing FPGA technology, this project aims to provide accelerated digital analysis during the time when convolutional neural networks began to gain prominence. This enhancement allowed for faster and more efficient digital recognition processes.
  [ Watch the Video ]

• FPGA Accelerator for Beam Forming, 2020

  With the aim of identifying sound location, this FPGA accelerator leverages a tetragonal microphone array to enhance sounds from specific points, we named the project FOSDA.
  [ Watch the Video ]

• Full Stack FPGA Implementation of NVDLA, 2021

  This project involved a full-stack FPGA implementation of the open-source Deep Learning Accelerator Framework, NVDLA. To enhance the utility of this accelerator, he designed a new compiler and runtime framework. This allowed networks to do transition between CPU fallbacks and hardware acceleration, ensuring optimal performance and usability.
  [ Read the Post: DLA Deploy ] [ Read the Post: Compiler Design ] [ View Github ]

• Opensource Contributions [Github]

  Familar with Microsoft NNFusion, Apache TVM, Tengine, etc.