This is a comprehensive GPU acceleration skill that transforms CPU-bound Python code to run on NVIDIA GPUs, often delivering 10x to 1000x speedups. It covers the full RAPIDS ecosystem (cuDF, cuML, cuGraph) plus CuPy, Numba CUDA, and Warp for physics simulation and differentiable rendering. The skill intelligently picks the right tool based on your workload: CuPy for NumPy array operations, cuDF for pandas dataframes, cuML for scikit-learn pipelines, and Warp for particle systems and mesh operations. It handles everything from vector search and geospatial analysis to medical imaging and GPUDirect Storage file I/O. The decision framework is solid, and it triggers proactively when it spots CPU-bound code that would benefit from GPU acceleration, even if you didn't explicitly ask for it.
npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill optimize-for-gpu