rapidsai / rapidsai/deployment
Improve HPC documentation beyond SLURM
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Description
xref: https://github.com/rapidsai/docs/issues/572
The HPC docs would benefit of a general update beyond SLURM which will be tackled by https://github.com/rapidsai/deployment/issues/54
and probably include a Troubleshooting section.
Common problem: There is a challenge with installing CUDA-enabled conda packages of PyTorch (and some other libraries) on CPU-only nodes, often HPC login nodes. This does not affect RAPIDS libraries but it comes up often in RAPIDS+PyTorch envs. Therefore documenting this to have an asset to point people to seems reasonable.
cc: @bdice for visibility
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 with the HPC documentation and the linked deployment issue 54, then review the referenced issue 572. Define the broader update beyond SLURM, including a Troubleshooting section covering CUDA-enabled conda packages for PyTorch on CPU-only HPC login nodes; done means the relevant guidance is documented and usable as a support reference.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- pytorch
- Domain
- documentation, hpc
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100