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Tools for diagnostics of training problems

Hanging processes

To track down the culprit of a hung process dumping the stack traces of the training processes.

pgrep -f pretrain_gpt | xargs -i /path/to/py-spy dump --pid {} > /networked/path/unique/for/node

Given the dumps of a hung 3D trainer, the node with issues usually get stuck in a different part of the training pipeline. Pipelines with no issues will be waiting at an all-reduce before step, whereas the problematic pipeline usually hangs somewhere in the training microbatches. We often see the pipeline-adjacent processes stuck on a pipe send/recv from the problematic node(s).

If py-spy isn't already installed, do:

pip install py-spy

Malfunctioning GPUs

Usually these require a reboot as once a problem happens on a hardware level, the recovery is not possible w/o a reboot.

For example if a GPU can't allocate memory because it has a hardware issue, as simple test could be:

python -c "import torch; torch.ones(1).cuda()"