Worked on the ROCm/aiter repository to deliver GFX1250 architecture support for DeepGEMM FP8 paged MQA logits, enabling AMD’s latest GPU hardware to utilize FP8 MQA computations with improved compatibility and potential performance gains. The technical approach involved refactoring architecture handling by replacing a boolean constexpr with a flexible ARCH string, reducing code branching and simplifying future architecture expansion. Additional work included targeted code cleanup to remove redundant comments, enhancing maintainability and readability. The project leveraged Python, CUDA, and deep learning expertise, focusing on GPU programming and performance optimization to address evolving hardware requirements in deep learning workloads.