cupynumeric-hdf5
cupynumeric-hdf5 is an agent skill published by nvidia, listed under deploy & operate. It lives in the NVIDIA/skills repository, which has 3,735 GitHub stars and is licensed under Apache-2.0; we last read it on 2026-09-16.
Reads and writes large cuPyNumeric arrays to HDF5 using Legate's parallel, distributed HDF5 I/O. Requires a cuPyNumeric array for saving to an .h5/.hdf5 file and a distributed cuPyNumeric array for loading from an HDF5 dataset.
Install
skills is a generic installer for any repository of Claude agent skills -- it reads NVIDIA/skills’s own structure rather than assuming one, the same way this page reads the skill’s own SKILL.md rather than assuming a format.
npx skills add NVIDIA/skills
Maintenance
Read and write large cuPyNumeric arrays to HDF5 with Legate's parallel, distributed HDF5 I/O (legate.io.hdf5: to_file, from_file, from_file_batched). Use when a developer needs to save a cuPyNumeric array to an .h5/.hdf5 file, load an HDF5 dataset into a distributed cuPyNumeric array, read a large HDF5 dataset in chunks, hand arrays to an HPC pipeline as a single file, or accelerate HDF5 disk I/O with GPUDirect Storage (GDS). Do not use it for Parquet/cuDF/raw-binary or other sharded/custom layouts (see the cupynumeric-parallel-data-load skill), Zarr or object-store/S3 output, .npz or pickled archives, plain h5py without cuPyNumeric, or pure array compute such as FFT, matmul, or reductions.
cupynumeric-hdf5 compared with similar skills
| Skill | Publisher | What it does | Repo stars | Last update |
|---|---|---|---|---|
| cupynumeric-hdf5 (this page) | nvidia | Read and write large cuPyNumeric arrays to HDF5 with Legate's parallel, distributed HDF5 I/O (legate.io.hdf5:… | 3,735 | 2026-10-26 |
| amc-setup-calibration-stack(same repository) | nvidia | Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says… | 3,735 | 2026-10-26 |
| cuopt-install(same repository) | nvidia | Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from… | 3,735 | 2026-10-26 |
| data-designer(same repository) | nvidia | Use when the user wants to create a dataset, generate synthetic data, or build a data generation pipeline. | 3,735 | 2026-10-26 |
| deepstream-generate-pipeline(same repository) | nvidia | Build DeepStream GStreamer pipelines interactively. Use when the user asks about pipelines for video/image in… | 3,735 | 2026-10-26 |
| deepstream-import-vision-model(same repository) | nvidia | Use this skill to bring a supported object-detection vision model from HuggingFace or NVIDIA NGC into an NVID… | 3,735 | 2026-10-26 |
| deepstream-profile-pipeline(same repository) | nvidia | Profile a DeepStream pipeline with Nsight Systems and derive its configs from the measurement. Use when the u… | 3,735 | 2026-10-26 |
Skills from the same repository first, then others for this job by repository stars. Figures are from each repository when we last read it.
Common questions about cupynumeric-hdf5
- What does cupynumeric-hdf5 do?
- Reads and writes large cuPyNumeric arrays to HDF5 using Legate's parallel, distributed HDF5 I/O. Requires a cuPyNumeric array for saving to an .h5/.hdf5 file and a distributed cuPyNumeric array for loading from an HDF5 dataset.
- How do I install cupynumeric-hdf5?
- Run npx skills add NVIDIA/skills. The skills installer reads the repository’s own structure, so it works for any repository of agent skills.
- Who publishes cupynumeric-hdf5?
- nvidia.
- Is cupynumeric-hdf5 maintained, and what licence does it use?
- Its repository has 3,735 GitHub stars and its state in our directory is listed. Its last commit we recorded was on 2026-10-26. The repository declares the Apache-2.0 licence.
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