[Feature Request] Add `hugepages` support to hyp-pytorch-job config
Nobody has claimed this yet.
Assessment
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Newbie friendliness
- 55/100
Research direction
Start by locating the hyp-pytorch-job template and the CLI configuration entry point that builds its pod resource requests and limits. Compare the generated pod spec with the issue's hugepages-2Mi example, then check existing template tests or generated-output checks; done means both suggested fields produce the requested values.
Written by the indexing model from the issue text.
Description
The hyp-pytorch-job template doesn't support requesting hugepages. EFA's RDMA stack uses hugepages (2Mi) to reduce TLB misses during DMA transfers for inter-node NCCL communication. Without this, users have to bypass the CLI and write raw YAML.
HyperPod nodes already pre-allocate hugepages (e.g. ~10562Mi on ml.p4d.24xlarge), but the CLI template has no way to request them in the pod spec. The official SageMaker docs for HyperPodPyTorchJob show hugepages-2Mi: 5120Mi in the example job spec, confirming this is an expected resource to configure.
Suggested config fields:
hugepages_2mi: 5120
hugepages_2mi_limit: 5120
Which would generate:
resources:
requests:
hugepages-2Mi: 5120Mi
limits:
hugepages-2Mi: 5120Mi
- Dominant language
- Python
- Stars
- 41
- Forks
- 95
- Avg merge
- 14h 48m
- Merged PRs (30d)
- 5
Getting set up
- No Dockerfile or Docker Compose file
- Has a pull request template
- Read the contributing 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.
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