Worked on NVIDIA/Megatron-LM to deliver a feature focused on optimizing CUDA stream management within the SharedExpertMLP class. Refactored the handling of shared expert streams to reduce their number, aiming to improve resource management and potentially increase throughput in multi-expert deep learning scenarios. This work involved in-depth use of PyTorch and Python, leveraging knowledge of deep learning and machine learning systems. The approach targeted more efficient utilization of GPU resources by streamlining how CUDA streams are allocated and managed, contributing to technical improvements in the repository’s multi-expert model infrastructure. No bug fixes were recorded during this period.