Lightning-AI / Lightning-AI/pytorch-lightning
Add more accelerators for learning
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 31.4k
- Forks
- 3.8k
- Avg merge
- 6d 7h
- Merged PRs (30d)
- 6
Description
### Description & Motivation
Start with xpu support, which torch officially supports.
Then add huawei tpu support. Although it's more likely that you just need to integrate this code.
https://github.com/lyh1028/ascend_npu_for_pytorch_lightning
And then add support for meta accelerators, als and other companies.
### Pitch
_No response_
### Alternatives
_No response_
### Additional context
_No response_
cc @lantiga @borda @justusschock
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
No files, tests, or entry points are named. Start by reviewing the project's existing accelerator support and the linked ascend_npu_for_pytorch_lightning integration, then define the scope for XPU, Huawei TPU, and Meta accelerators. Done means the agreed accelerator integrations are implemented with appropriate validation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100