During December 2025, MidnightSun114514 developed a kernel-based sampling optimization for the vllm-project/vllm-ascend repository, replacing the existing PyTorch sampling implementation with custom Triton kernels. This work focused on deep learning and GPU programming, leveraging Python and Triton to achieve higher throughput and lower latency in production sampling workloads. The new kernels maintained full API compatibility, ensuring seamless integration for users while improving backend efficiency. By collaborating with other contributors, MidnightSun114514 delivered a scalable solution that aligned with the vLLM v0.11.2 release, demonstrating depth in GPU-accelerated optimization and robust release practices, though no major bugs were addressed during this period.