Show HN: Agentic CUDA Kernel Optimizer

The Agentic CUDA Kernel Optimizer is a new open-source project designed to automate the complex process of optimizing CUDA kernels for high-performance computing. By leveraging agentic AI workflows, the tool assists developers in identifying performance bottlenecks and generating optimized code structures that better utilize GPU resources. This approach aims to reduce the manual effort typically required for low-level performance tuning in machine learning and scientific computing tasks. The project is hosted on GitHub and provides a framework for iterative kernel refinement, allowing users to experiment with different optimization strategies through an automated agent. As GPU-accelerated workloads continue to grow in complexity, such tools represent a significant step toward streamlining MLOps and hardware-level performance engineering. Developers can integrate the optimizer into their existing pipelines to improve throughput and efficiency in compute-intensive applications, marking a shift toward AI-assisted systems programming.