aws / aws/sagemaker-python-sdk
Add ml.p5e.48xlarge to EFA instance lists in sagemaker-train and sagemaker-core
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- Python
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Description
# Add ml.p5e.48xlarge to EFA instance lists in sagemaker-train and sagemaker-core
## Description
The `SM_EFA_NCCL_INSTANCES` and `SM_EFA_RDMA_INSTANCES` lists in the sagemaker-python-sdk are missing `ml.p5e.48xlarge`, causing NCCL hangs during distributed training initialization on P5e instances when using the SDK's container drivers.
Additionally, `ml.p5.48xlarge` is missing from `SM_EFA_RDMA_INSTANCES` (it's only in `SM_EFA_NCCL_INSTANCES`).
## Current State
```python
SM_EFA_NCCL_INSTANCES = [
"ml.g4dn.8xlarge",
"ml.g4dn.12xlarge",
"ml.g5.48xlarge",
"ml.p3dn.24xlarge",
"ml.p4d.24xlarge",
"ml.p4de.24xlarge",
"ml.p5.48xlarge",
"ml.trn1.32xlarge",
]
SM_EFA_RDMA_INSTANCES = [
"ml.p4d.24xlarge",
"ml.p4de.24xlarge",
"ml.trn1.32xlarge",
]
```
## Expected State
```python
SM_EFA_NCCL_INSTANCES = [
"ml.g4dn.8xlarge",
"ml.g4dn.12xlarge",
"ml.g5.48xlarge",
"ml.p3dn.24xlarge",
"ml.p4d.24xlarge",
"ml.p4de.24xlarge",
"ml.p5.48xlarge",
"ml.p5e.48xlarge", # ADD
"ml.trn1.32xlarge",
]
SM_EFA_RDMA_INSTANCES = [
"ml.p4d.24xlarge",
"ml.p4de.24xlarge",
"ml.p5.48xlarge", # ADD
"ml.p5e.48xlarge", # ADD
"ml.trn1.32xlarge",
]
```
## Impact
Without these entries, the SDK's container drivers don't set the required EFA environment variables (`FI_PROVIDER=efa`, `FI_EFA_USE_DEVICE_RDMA=1`, `RDMAV_FORK_SAFE=1`) for P5e instances, causing NCCL to hang during collective initialization in multi-node distributed training.
## Related
- sagemaker-training-toolkit issue: https://github.com/aws/sagemaker-training-toolkit/issues/240
- sagemaker-training-toolkit PR: https://github.com/aws/sagemaker-training-toolkit/pull/241
- P5e instances use EFA with RDMA support, same as P4d/P4de/P5
## Questions
1. Is there a specific process for testing EFA/instance-specific changes on actual hardware before merging?
2. Should integration tests be added for P5e EFA configuration, or are unit tests sufficient?
Guide de contribution
Ouvrir le guide de contribution
Piste de recherche
Commencez par localiser les définitions de SM_EFA_NCCL_INSTANCES et SM_EFA_RDMA_INSTANCES dans les composants sagemaker-train et sagemaker-core. Comparez les deux listes avec l’état attendu dans cette issue, puis vérifiez la couverture des tests unitaires concernés ; c’est terminé lorsque les deux instances P5 sont représentées dans les listes EFA appropriées.
Rédigé par le modèle d'indexation à partir du texte de l'issue.
Évaluation
- Stack technique
- aws, python
- Domaine
- cloud, machine-learning
- Type d'issue
- Bug
- Difficulté
- 2/5
- Temps estimé
- 1-3 heures
- Activité
- À l'abandon
- Clarté
- Clairement spécifiée
- Accessibilité débutants
- 58/100