deepspeedai / deepspeedai/DeepSpeed
How zero3 releases the GPU memory occupied by parameters?
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Description
I would like to know how zero3 releases the GPU memory occupied by parameters after forward ends. From the code, it seems that _post_forward_module_hook will call release_sub_module to partition param and release param by param.data = torch.empty(0). Param.data is indeed modified to 0. However, I found that GPU memory did not decrease. When I release the GPU memory occupied by parameters through register_full_backward_hook after backward ends with the same operation, the GPU memory does decrease. Is this due to reference counting? I would like to know how deepspeed solves this problem. Thank you very much.
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Research direction
Start with the _post_forward_module_hook and release_sub_module entry points mentioned in the issue, then compare their parameter handling with the reported register_full_backward_hook path. Trace references around param.data = torch.empty(0) and document the observed difference in GPU memory release; done means a clear explanation backed by the relevant DeepSpeed behavior.
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Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning, performance
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100