Lightning-AI / Lightning-AI/pytorch-lightning
Revamp Async Checkpointing to Use PyTorch Distributed Checkpoint (DCP) async_save
@deependujha is already working on this.
Since Feb 27, 2026.
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Description
### Description & Motivation
PyTorch Lightning’s current async checkpointing implementation predates PyTorch’s Distributed Checkpoint (DCP) API and feels outdated.
This issue proposes evaluating and migrating Lightning’s async checkpoint logic to leverage `torch.distributed.checkpoint` (DCP), specifically `async_save`, to:
* Align with upstream PyTorch checkpointing APIs
* Improve robustness and maintainability
* Better support distributed and sharded training setups
* Reduce custom logic that duplicates upstream functionality
### Pitch
Use [PyTorch DCP's async_save](https://docs.pytorch.org/docs/stable/distributed.checkpoint.html#torch.distributed.checkpoint.state_dict_saver.async_save)
### Alternatives
_No response_
### Additional context
https://docs.pytorch.org/docs/stable/distributed.checkpoint.html#distributed-checkpoint-torch-distributed-checkpoint
cc @lantiga
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