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?
Contributor guide
Research direction
Start by locating the SM_EFA_NCCL_INSTANCES and SM_EFA_RDMA_INSTANCES definitions in the sagemaker-train and sagemaker-core components. Compare both lists with the expected state in this issue, then check the relevant unit-test coverage; done means both P5 instances are represented in the appropriate EFA lists.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, python
- Domain
- cloud, machine-learning
- Issue type
- Bug
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 58/100