During April 2025, LSY developed a compute optimization feature for the deepseek-ai/FlashMLA repository, focusing on enhancing performance for compute-bound workloads. Leveraging C++ and CUDA, LSY introduced targeted kernel-level improvements that increased throughput and resource utilization across FlashMLA operations. The work involved detailed performance profiling and the implementation of maintainable code changes, resulting in faster compute and more efficient kernel execution. By addressing bottlenecks in the library’s core routines, LSY’s contribution enabled more effective machine learning workloads on GPU hardware. The depth of the optimization reflected strong skills in GPU programming and performance engineering within a production codebase.