Checkpoint Save/Restore Gathering Timeout
NCCL timeout occurs while gathering the state dictionary or broadcasting during a checkpoint save or restore operation.
NCCL timeout occurs while gathering the state dictionary or broadcasting during a checkpoint save or restore operation.
What this failure is
Checkpoint Save/Restore Gathering Timeout is a Distributed Training failure seen during ML training runs. NCCL timeout occurs while gathering the state dictionary or broadcasting during a checkpoint save or restore operation. Common tags: Checkpoint, Timeout, Nccl, Fsdp.
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Why it happens (the mechanism)
Gathering the full model state to a single rank (rank 0) exceeds the memory capacity of the rank or takes longer than the NCCL watchdog timeout. Network congestion during the massive many-to-one broadcast/gather. Taken together, these mechanisms explain why the failure is reproducible, why it tends to surface on specific workloads or scales, and why generic mitigation attempts often fall short without addressing the underlying cause.
What you'll observe
- Training hangs during checkpointing
- NCCL watchdog timeout
Common symptoms and what they mean
| Symptom | Why it happens |
|---|---|
| NCCL timeout during gather_state_dict | Gathering the full model state to a single rank (rank 0) exceeds the memory capacity of the rank or takes longer than the NCCL watchdog timeout. |
| Timeout waiting for rank 0 to broadcast | Network congestion during the massive many-to-one broadcast/gather. |
| Process stuck in torch.save() | Gathering the full model state to a single rank (rank 0) exceeds the memory capacity of the rank or takes longer than the NCCL watchdog timeout. |
Which systems are affected
- PyTorch FSDP
- DeepSpeed
- Large scale distributed training
How to confirm this is the problem
Use this checklist to test the hypothesis against a small reproduction. No single line proves the root cause, so preserve the preceding events and compare one variable at a time.
- ✓Reproduce the failure from a clean checkpoint/seed: the symptom must appear without warm-up state from a previous run.
- ✓Verified signal present: NCCL timeout during gather_state_dict
- ✓Verified signal present: Timeout waiting for rank 0 to broadcast
- ✓Verified signal present: Process stuck in torch.save()
- ✓A targeted fix from the "How to fix it" section eliminates or substantially reduces the symptom within one validation pass.
The fix and the prevention pattern
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Diagnose this failure in VS Code
Select the traceback or open the failed terminal, then run Denpex locally to see the initiating rank, collateral failures, exact fix, and verification command without uploading the log.
Install the free VS Code extensionNCCL errors in context
NCCL is where a distributed job reports failure, which is not the same as where it failed. The hub lists every common NCCL error next to what it actually indicates, and the environment variables that tell them apart.
Compare every nccl error side by sideRelated failures to investigate next
Root cause
- Gathering the full model state to a single rank (rank 0) exceeds the memory capacity of the rank or takes longer than the NCCL watchdog timeout.
- Network congestion during the massive many-to-one broadcast/gather.
The fix and how to prevent it
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