GPU Optimization for Python with NVIDIA

Treat GPU acceleration as an evidence-driven optimization, not an automatic rewrite. Preserve the user's numerical and algorithmic contract, measure with representative data, and keep the GPU version only when synchronized end-to-end benchmarks show a useful improvement.

Reviewed against RAPIDS 26.08, CuPy 14.2, Numba-CUDA 0.30.4, and Warp 1.17. The references contain illustrative GPU examples: source/API review is not execution on CUDA hardware. Validate them on the user's target GPU before reporting correctness or speedup. Do not use a moving latest documentation page to infer compatibility with a pinned release.

When This Skill Applies