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.
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New here? These commands run inside Claude Code, Anthropic's terminal-based coding assistant — not your regular shell. Open a terminal, type claude to start a session, then paste the two lines below inside it.
npx skills add nvidia/skills --skill "cupynumeric-parallel-data-load" -a claude-code -g -yPaste into a Claude Code session. This only adds/installs the plugin — nothing runs automatically.
O, si ya vinculaste skillcat-sync, envíalo directamente — te pedirá confirmar antes de tocar nada.
This listing is sourced from nvidia/skills. The security badge above comes from a third-party audit (skills.sh) — we haven't independently executed or reviewed this code ourselves. Review the source before installing.
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