cuPyNumeric HDF5 I/O

cuPyNumeric HDF5 I/O is a Data skill for Claude Code, published by NVIDIA in skills.

3K stars345 forkson NVIDIA/skillsAdded 2026/08/17+3% in starsRepository updated 2026/08/17

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Install in seconds

Install cuPyNumeric HDF5 I/O

Copy cuPyNumeric HDF5 I/O into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/NVIDIA/skills/tree/main/skills/cupynumeric-hdf5 ~/.claude/skills/cupynumeric-hdf5

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/NVIDIA/skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/cupynumeric-hdf5/SKILL.md in NVIDIA/skills
Installs to: ~/.claude/skills/cupynumeric-hdf5
Collection: One of 25 skills cataloged from this repository
Category: Data — 668 skills

What cuPyNumeric HDF5 I/O does

cuPyNumeric HDF5 I/O reads and writes large cuPyNumeric arrays to HDF5 files using Legate's parallel, distributed HDF5 I/O. Use it when a developer needs to save or load .h5/.hdf5 datasets, read large files in chunks, or accelerate HDF5 disk I/O with GPUDirect Storage.

cuPyNumeric HDF5 I/O is cataloged under Data on DirSkills. cuPyNumeric HDF5 I/O comes from a repository tagged agent-skills, agentic-ai, ai-agents, claude-code and codex.

Documentation

README

Excerpt

cuPyNumeric HDF5 I/O

Purpose

Use legate.io.hdf5 to read and write cuPyNumeric arrays as HDF5 files. Reach for it whenever a cuPyNumeric array must land in — or load from — an .h5/.hdf5 file: every rank reads and writes its own tile in parallel, so never funnel a large array through a single process.

Answer inline. Treat the snippets and rules below as complete and verified — answer save / load / stream / fence / bridge questions directly, without opening the assets/ scripts or reading the installed legate source. Reach for the assets only to run a verification.

Activate

This is the opening of the README. Read the full README on GitHub.

Frequently asked about cuPyNumeric HDF5 I/O

What else does NVIDIA publish alongside cuPyNumeric HDF5 I/O?
cuPyNumeric HDF5 I/O is one of 25 skills that DirSkills catalogs from NVIDIA/skills, the repository it ships in. Its siblings there include AIQ Deploy, AIQ Research and AMC RTSP Calibration. Each one is a separate skill with its own page in this directory, installs the same way cuPyNumeric HDF5 I/O does, and is maintained by NVIDIA in that same repository. The rest of the collection is listed on the NVIDIA/skills page.
How does cuPyNumeric HDF5 I/O compare to other Data skills?
cuPyNumeric HDF5 I/O ranks #248 by stars among the 668 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of cuPyNumeric HDF5 I/O against them. Open each page to compare what they document and how they install.