docs: add data loading best practices for large-scale training - #4236
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Add documentation for configuring Megatron data pipeline at 256-512+ node scale, covering index building architecture, cache pre-warming, and the key flags (--dataloader-fast-cache-load, --dataloader-defer-npy-index-mmap, --per-dataset-sequences-path). Includes troubleshooting section and guidance on consolidating small dataset files.
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svcnvidia-nemo-ci
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April 9, 2026 17:05
asolergi-nv
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April 15, 2026 08:34
asolergi-nv
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Apr 16, 2026
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/ok to test 2c68e70 |
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🔄 Merge queue validation started! You can track the progress here: https://github.com/NVIDIA/Megatron-LM/actions/runs/24787979470 |
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…A#4236) Co-authored-by: Antoni-Joan Solergibert <asolergibert@nvidia.com>
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…A#4236) Co-authored-by: Antoni-Joan Solergibert <asolergibert@nvidia.com> Signed-off-by: yhgalaxy <yhgalaxy@outlook.com>
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…A#4236) Co-authored-by: Antoni-Joan Solergibert <asolergibert@nvidia.com> Signed-off-by: Jon Barker <jbarker@aws-cmh-slurm-1-vscode-02.cm.cluster>
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…A#4236) Co-authored-by: Antoni-Joan Solergibert <asolergibert@nvidia.com>
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What does this PR do ?
Adds a user guide for large-scale data loading that explains cache preparation, startup optimizations, and troubleshooting guidance for training.
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