# Cupynumeric Parallel Data Load

> 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.fromfile when they apply.

## Facts
- Page: https://tashan.sh/capability/skill-nvidia-cupynumeric-parallel-data-load
- tashan id: skill:NVIDIA/cupynumeric-parallel-data-load
- Source: https://github.com/NVIDIA/skills
- Type: skill
- Category: other
- tashan score: not scored (catalogued only — too little public evidence)
- Adoption: 9.0
- Upkeep: 96.0
- Freshness: 92.0
- Evidence coverage: 84% of the inputs this score can use
- Health: active
- Instruction depth: not yet graded
- License: Apache-2.0
- Official: no

## Install

```sh
cp -r cupynumeric-parallel-data-load ~/.claude/skills/
```

## Security audit
Not scanned. We audit npm-published capabilities; this one has no npm package we can resolve, or has not reached the queue. This is not a clean bill of health.

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Measured 2026-08-20 by tashan (https://tashan.sh) from public evidence. Scorer s5.