I am a Software Engineer at NVIDIA Corporation. Previously, I obtained PhD degree in Computer Science at University of California, Riverside. Prior to the PhD study in Computer Science, I obtained MS and BS degrees from Duke University and University of Science and Technology of China, both in Chemistry.

I am currently focusing on performance optimization for math libraries on CPUs, GPUs and heterogeneous platforms. I have interned with the XPU Architecture Research team at Intel Corporation working on GPU-accelerated homomorphic encryption. In 2022 Spring, I have been with the Machine Learning System team at ByteDance US as a Research Intern. In 2022 Summer, I was with the Fast Kernels team at NVIDIA Corporation as an engineering intern.

News

• June. 2023: I obtained my PhD degree in Computer Science and returned to the CUTLASS team at NVIDIA as a software engineer.
• June. 2023: I was invited to give a talk at Biren Technology.
• April. 2023: A paper was accepted at International Conference on Supercomputing 2023.
• Mar. 2023: The IPDPS’23 paper - ByteTransformer - was selected as Best Paper Finalist of the main conference.
• Jan. 2023: The internship paper with ByteDance and NVIDIA was accepted at IPDPS’23.
• Sept. 2022: I accepted a full-time offer from the Fast Kernels team at NVIDIA.
• Jan. 2022: Received an internship offer from the Machine Learning System (AML-MLsys) team at ByteDance USA.
• Jan. 2022: The summer internship paper with Intel was accepted at IPDPS’22.
• Oct. 2021: I accepted an internship offer from the Fast Kernels team at NVIDIA.
• June. 2021: I open-sourced four GEMM/GEMV tutorials.
• March. 2021: A paper was accepted at International Conference on Supercomputing 2021.
• Nov. 2020: I participated SC’20 as a student volunteer.
• Oct. 2020: I accepted an internship offer from the XPU architecture research team at Intel.
• June. 2020: I gave a talk at SIAM CSE’20.
• June. 2020: I passed the PhD qualifying exam.