During September 2025, Peng Chen contributed to the pytorch/FBGEMM repository by migrating the grouped_gemm.py script to the new device TMA API, focusing on improving maintainability and future extensibility. This work involved updating tensor descriptor creation and storage to align with the revised API, ensuring compatibility and reducing technical debt. Peng also addressed code quality by performing lint cleanup, removing unused variables to streamline the codebase. Utilizing C++, Python, and CUDA, Peng’s efforts enhanced the stability and maintainability of the grouped_gemm workflow. The depth of the migration work reflects a strong understanding of deep learning optimization and GPU programming best practices.