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…

cupynumericdataloadparallel

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---
name: cupynumeric-parallel-data-load
description: 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.
license: CC-BY-4.0 OR Apache-2.0
compatibility: linux-x86_64, linux-aarch64, darwin-aarch64, wsl-x86_64
metadata:
  version: "1.0.0"
  author: "NVIDIA Corporation <legate@nvidia.com>"
  upstream: https://github.com/nv-legate/cupynumeric
  docs: https://docs.nvidia.com/cupynumeric/latest/
  tags:
    - cupynumeric
    - legate
    - data-loading
    - io
    - distributed
    - parallel
    - gpu
    - sharded-data
---

# Parallel sharded data -> cupynumeric load

**Why this skill exists.** cupynumeric mirrors NumPy's array API,
including `cupynumeric.load` for a single `.npy` file. Beyond that,… load the full skill through Skill Me