deepspeedai / deepspeedai/DeepSpeed
[REQUEST] Support for CUDA Graphs
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enhancement
- Dominant language
- Python
- Stars
- 43.1k
- Forks
- 5k
- Avg merge
- 4d 15h
- Merged PRs (30d)
- 112
Description
Does DeepSpeed support Pytorch code with CUDA Graphs? If not, do think it may be helpful to DeepSpeed users for further speedups?
Context: I am trying to optimize my training code that can benefit from launching multiple kernels together.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the linked PyTorch CUDA Graphs documentation and the DeepSpeed integration points used by the reported training code. Determine whether CUDA Graphs are currently supported and define the DeepSpeed changes and validation needed for kernel-capture speedups; the issue provides no specific files or tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning, performance
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100