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GPU-accelerate Python code using CuPy, Numba CUDA, Warp, cuDF, cuML, cuGraph, KvikIO, cuCIM, cuxfilter, cuVS, cuSpatial, and RAFT.
Passed 23 of 24 test cases with the skill, and 18 of 24 without it.
and 3 more in the full report
5 fixed19 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
We are building a vector database retrieval pipeline for a RAG application with high-dimensional embeddings and need fast nearest-neighbor similarity searches using GPU acceleration. Please write a Python code example showing how to build the index and execute queries on the GPU.
| Checked | Without skill | With skill |
|---|---|---|
| The solution uses cuVS (or cuvs) for GPU vector search. | Missed | Passed |
| The code imports the cuvs module instead of faiss. | Missed | Passed |
The instructions your model reads when the skill loads.
|-------------|
| references/cupy.md | User has NumPy/SciPy code, or needs array operations on GPU |
| references/numba.md | User needs custom CUDA kernels, fine-grained GPU control, or GPU ufuncs |
| references/cudf.md | User has pandas code, or needs dataframe operations on GPU |
| references/cuml.md | User has scikit-learn code, or needs ML training/inference/preprocessing on GPU |
| references/cugraph.md | User has NetworkX code, or needs graph analytics on GPU |
| references/warp.md | User needs GPU simulation, spatial computing, mesh/volume queries, differentiable programming, or robotics |
| references/kvikio.md | User needs high-performance file IO to/from GPU, GPUDirect Storage, reading S3/HTTP to GPU, or Zarr on GPU |
| references/cuxfilter.md | User wants GPU-accelerated interactive dashboards, cross-filtering, or EDA visualization |
| references/cucim.md | User has scikit-image code, or needs image processing, digital pathology, or WSI reading on GPU |
| references/cuvs.md | User needs vector search, nearest neighbors, similarity search, or RAG retrieval on GPU |
| references/cuspatial.md | User has GeoPandas/shapely code, or needs spatial joins, distance calculations, or trajectory analysis on GPU |
| references/raft.md | User needs sparse eigensolvers, device memory management, or multi-GPU primitives |
Read the specific reference before writing code — they contain detailed API patterns, optimization techniques, and pitfalls specific to each library.
test cases passed, vs 18 / 24 without
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