{"slug":"nvidia-cupynumeric-parallel-data-load","source_name":"nvidia/cupynumeric-parallel-data-load","name":"Nvidia/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.","version":1,"lift":{"pass_rate_delta_pts":59.09,"pass_rate_pct":81.8,"total_cases":22,"passed_cases":18,"tokens_delta_pct":149,"turns_delta_pct":0,"verdict":"mixed","benchmark_model":"gemini-3.6-flash","grading_method":"judged","completed_at":"2026-08-12T07:49:46.579404+00:00"},"skill_score":null,"benchmark_models":[{"model":"gemini-3.6-flash","headline":true,"delta_pts":59.09,"with_pass_pct":81.8,"without_pass_pct":22.7,"tokens_delta_pct":149,"turns_delta_pct":0,"total_cases":22,"cases_aggregated":21,"verdict":"mixed","never_hurt":true,"completed_at":"2026-08-12T07:49:46.579404+00:00","run_id":"9b15ea01-b0f4-4967-8c80-642b35a6c84a","version_number":1,"is_latest_version":true,"gate":null}],"trust":{"skill_safety":"passed","safety_status":"clean","intent_verdict":"safe","content_status":"clean","indexable":true},"license":"CC-BY-4.0 OR Apache-2.0","install_count":0,"manifest_hash":"75fcb28353a1a5672addd37db79d091c3cedeebd01f8517051d1dc0b1a9128c4","raw_url":"https://app.decimal.ai/s/nvidia-cupynumeric-parallel-data-load/SKILL.md","scorecard_url":"https://app.decimal.ai/skills/nvidia-cupynumeric-parallel-data-load"}