Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

how to use gpu in sagemaker instance #126

Open
haiderasad opened this issue May 31, 2022 · 1 comment
Open

how to use gpu in sagemaker instance #126

haiderasad opened this issue May 31, 2022 · 1 comment

Comments

@haiderasad
Copy link

hi i am going with a custom docker image with all the cuda cudnn installed and also tested locally gpu is being utilized. but when upload to ecr and create endpoint it does not create endpoint and says kindly make sure docker serve command is valid , from debugging i came to found out that inference toolkit is needed inside image for the image to see if sagemaker gpu is avail or not, but there is no sample dockerfile from which i can understand , kindly tell
1)how to enable cuda support in custom built docker images for sagemaker
2)will using prebuilt images e.g accountnum.aws.amazon.com/pytorch:1.10-cuda113-py3 directly use cuda/gpu of sagemaker instance?

@holopekochan
Copy link

holopekochan commented Oct 2, 2022

For inference endpoint, probably, you can use GPU instance in SingleModel mode,
As I tried MultiModel mode with
763104351884.dkr.ecr.$REGION.amazonaws.com/pytorch-inference:1.12.1-gpu-py38-cu113-ubuntu20.04-sagemaker

It shows error ClientError: An error occurred (ValidationException) when calling the CreateEndpointConfig operation: MultiModel mode is not supported for instance type ml.g4dn.xlarge.
from here, it said GPU instance is not supported aws/sagemaker-python-sdk#1323

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants