CV

Education

• B.S. in Huazhong University of Science and Technology, 2018
• Ph.D in Shanghai Jiao Tong University, 2023 (expected)

Work experience

• Summer 2020: Research Intern
  • T-Head Alibaba
• Spring 2021: Research Intern
  • Peng Cheng Laboratory
• Summer 2021: Research Intern
  • Qi Zhi Institute
• Summer 2022: Research Intern
  • Alibaba Cloud

Publications

Balancing efficiency and flexibility for DNN acceleration via temporal GPU-systolic array integration

TPUSim: ISA Design and Optimization for Fused Architecture Based Training Accelerator

Characterizing and Demystifying the Implicit Convolution Algorithm on Commercial Matrix-Multiplication Accelerators

Efficient Activation Quantization via Adaptive Rounding Border for Post-Training Quantization

uGrapher: High-performance Graph Operator Computation via Unified Abstraction for Graph Neural Networks

AdaptGear: Accelerating GNN Training via Adaptive Subgraph-Level Kernels on GPUs

DistSim: A performance model of large-scale hybrid distributed DNN training