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Cupynumeric Parallel Data Load

Category: General  ·  Sub-category: general-misc  ·  Last updated:
Load a sharded, on-disk dataset (sharded .npy, Parquet/Arrow, raw binary, sharded HDF5, custom layouts) into a distributed cuPyNumeric ndarray via a manual partition + leaf @task launch with CPU/OMP/GPU variants. Use when no single-call loader fits, including when per-shard row counts differ across files. Prefer cupynumeric.load or legate.io.hdf5.from_file when they apply.

About this skill (catalog notes)

Cupynumeric Parallel Data Load includes worked examples; pricing or quota commentary; 11 code blocks for direct copy-paste. At roughly 2,357 words the SKILL.md is on the longer end of the catalog distribution.

Source
docs.nvidia.com/skills
Original author
NVIDIA
Indexed lastmod
Catalog position
General · general-misc
Indexed related skills
10

How Cupynumeric Parallel Data Load fits the catalog

Cupynumeric Parallel Data Load sits in the General category under the general-misc sub-topic in the ClaudSkills catalog. There are 10 related skills indexed alongside it; comparing a few before installing usually reveals which fits your workflow best.

These notes are auto-generated from features detected in the SKILL.md file and from this catalog's structure — they aren't part of the source repository.

From the source SKILL.md

Why this skill exists. cupynumeric mirrors NumPy's array API, including cupynumeric.load for a single .npy file. Beyond that, file loading lives in Legate, not cupynumeric:

What this skill does

Cupynumeric Parallel Data Load is a community-contributed Claude Code skill in the general-misc sub-category. It ships as a SKILL.md file that Claude Code auto-discovers under ~/.claude/skills/cupynumeric-parallel-data-load/ and loads when your prompt matches the skill's trigger.

When to invoke it: Use when no single-call loader fits, including when per-shard row counts differ across files. Prefer cupynumeric.

Who uses this skill

The Cupynumeric Parallel Data Load Claude Code skill is built for Claude Code users and developers across all disciplines looking for general-purpose AI assistance. It's part of ClaudSkills (also referred to as Claude Skills or Claude Code Skills) — the open community-curated registry of 119,000+ SKILL.md files for Anthropic's Claude Code agent and the wider Claude ecosystem (Claude API, Claude Agent SDK).

How to install

Free

Manual install (2 steps)

mkdir -p ~/.claude/skills/cupynumeric-parallel-data-load
curl -L https://claudskills.com/skills/cupynumeric-parallel-data-load/SKILL.md \
  -o ~/.claude/skills/cupynumeric-parallel-data-load/SKILL.md

Or just download SKILL.md directly and drop it into ~/.claude/skills/cupynumeric-parallel-data-load/. Claude Code auto-discovers it on next session.

Skills live at ~/.claude/skills/cupynumeric-parallel-data-load/SKILL.md on macOS/Linux, or %USERPROFILE%\.claude\skills\cupynumeric-parallel-data-load\SKILL.md on Windows. See the full install guide for step-by-step instructions.

Telegram

📱 Install from your phone or desktop Telegram

Open @claudskills_bot on Telegram, tap Open Desktop App, and the desktop app installs this skill for you. Or share the bot link with a colleague — they get the same one-tap install. Learn more →

Pro

One-click install via the desktop app

The ClaudSkills desktop app installs any skill directly into ~/.claude/skills/ with one click — no terminal required. Pro starts at $9/mo or $149 lifetime.

Pro

For the full experience including quality scoring and one-click install features for each skill — upgrade to Pro.

Frequently asked questions

How do I install the Cupynumeric Parallel Data Load Claude Code skill?
Install via the ClaudSkills desktop app (one click) or copy SKILL.md from the source repository to ~/.claude/skills/cupynumeric-parallel-data-load/SKILL.md and restart Claude Code. Both flows are detailed at claudskills.com/install/.
What does the Cupynumeric Parallel Data Load skill do?
Load a sharded, on-disk dataset (sharded .npy, Parquet/Arrow, raw binary, sharded HDF5, custom layouts) into a distributed cuPyNumeric ndarray via a manual partition + leaf @task launch with CPU/OMP/GPU variants. Use when no single-call loader fits, including when per-shard row counts differ across files. Prefer cupynumeric.load or legate.io.hdf5.from_file when they apply.
Is this skill free to install?
Yes. ClaudSkills is an open registry — every skill keeps its source repository's license, and manual install via copy is free. ClaudSkills Pro ($9/mo, $79/yr, or $149 one-time) adds one-click install via the desktop app and a multi-signal Quality Score.
When should I use the Cupynumeric Parallel Data Load skill?
Use Cupynumeric Parallel Data Load when your Claude Code task falls under the General category — specifically in the general misc area. Claude Code auto-discovers installed skills and invokes the right one based on the task description, so you can also ask Claude directly (e.g. "use Cupynumeric Parallel Data Load" or describe the task and let Claude pick). Browse related skills at /category/general/.
What is a Claude Code skill and how does the Cupynumeric Parallel Data Load skill fit in?
A Claude Code skill is a SKILL.md file that lives under ~/.claude/skills/<name>/ and tells the Claude Code CLI agent how to perform a specific task (instructions, prompts, allowed tools). Skills are auto-discovered at session start. Cupynumeric Parallel Data Load is one of 67,000+ skills indexed in the open ClaudSkills catalog, classified under the General category. Learn more at /learn/what-is-a-claude-skill/.

Attribution & license

Cite this skill

If you reference this skill in a blog post, paper, or documentation, you can cite it as:

APA
NVIDIA. (2026). Cupynumeric Parallel Data Load [Claude Code skill]. ClaudSkills. https://claudskills.com/skills/cupynumeric-parallel-data-load/
BibTeX
@misc{cupynumeric-parallel-data-load-2026,
  author    = {NVIDIA},
  title     = {Cupynumeric Parallel Data Load [Claude Code skill]},
  year      = {2026},
  publisher = {ClaudSkills},
  url       = {https://claudskills.com/skills/cupynumeric-parallel-data-load/}
}

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