From 1337470a8bc99d7b850b9e592a69a378d0006a5f Mon Sep 17 00:00:00 2001 From: Jacob Tomlinson Date: Wed, 17 Dec 2025 14:21:54 +0000 Subject: [PATCH 1/2] Update SageMaker AI instructions --- source/cloud/aws/sagemaker.md | 18 +++++------------- source/conf.py | 8 ++++---- 2 files changed, 9 insertions(+), 17 deletions(-) diff --git a/source/cloud/aws/sagemaker.md b/source/cloud/aws/sagemaker.md index 095c1614..74b91851 100644 --- a/source/cloud/aws/sagemaker.md +++ b/source/cloud/aws/sagemaker.md @@ -8,7 +8,7 @@ RAPIDS can be used in a few ways with [AWS SageMaker](https://aws.amazon.com/sag ## SageMaker Notebooks -To get started head to [the SageMaker console](https://console.aws.amazon.com/sagemaker/) and create a [new SageMaker Notebook Instance](https://console.aws.amazon.com/sagemaker/home#/notebook-instances/create). +To get started head to [the SageMaker AI console](https://console.aws.amazon.com/sagemaker/) and create a [new SageMaker Notebook Instance](https://console.aws.amazon.com/sagemaker/home#/notebook-instances/create). Choose `Applications and IDEs > Notebooks > Create notebook instance`. @@ -17,8 +17,8 @@ Choose `Applications and IDEs > Notebooks > Create notebook instance`. If a field is not mentioned below, leave the default values: - **Notebook instance name** = Name of the notebook instance -- **Notebook instance type** = Type of notebook instance. Select a RAPIDS-compatible GPU ([see the RAPIDS docs](https://docs.rapids.ai/install#system-req)) as the SageMaker Notebook instance type (e.g., `ml.p3.2xlarge`). -- **Platform identifier** = 'Amazon Linux 2, Jupyter Lab 4' +- **Notebook instance type** = Type of notebook instance. Select a RAPIDS-compatible GPU ([see the RAPIDS docs](https://docs.rapids.ai/install#system-req)) as the SageMaker Notebook instance type (e.g., `ml.g6.xlarge`). +- **Platform identifier** = 'Amazon Linux 2023, Jupyter Lab 4' ![Screenshot of the create new notebook screen with a ml.p3.2xlarge selected](../../images/sagemaker-create-notebook-instance.png) @@ -41,11 +41,9 @@ set -e sudo -u ec2-user -i <<'EOF' -mamba create -y -n rapids -c rapidsai -c conda-forge -c nvidia rapids=24.12 python=3.12 cuda-version=12.4 \ - boto3 \ - ipykernel \ - 'sagemaker-python-sdk>=2.239.0' +eval "$(conda shell.bash hook)" +conda create -y -n rapids {{ rapids_conda_channels }} {{ rapids_sagemaker_conda_packages }} boto3 ipykernel sagemaker-python-sdk conda activate rapids python -m ipykernel install --user --name rapids @@ -53,12 +51,6 @@ echo "kernel install completed" EOF ``` -```{warning} -RAPIDS `>24.12` will not be installable on SageMaker Notebook Instances until those instances support -Amazon Linux 2023 or other Linux distributions with GLIBC of at least 2.28. -For more details, see [rapidsai/deployment#520](https://github.com/rapidsai/deployment/issues/520). -``` - Set the volume size to at least `15GB`, to accommodate the conda environment. Then launch the instance. diff --git a/source/conf.py b/source/conf.py index b466f964..0ab09144 100644 --- a/source/conf.py +++ b/source/conf.py @@ -31,13 +31,13 @@ "rapids_container": f"nvcr.io/nvidia/rapidsai/base:{stable_version}-cuda12-py3.13", "rapids_notebooks_container": f"nvcr.io/nvidia/rapidsai/notebooks:{stable_version}-cuda12-py3.13", "rapids_conda_channel": "rapidsai", - "rapids_conda_channels": "-c rapidsai -c conda-forge -c nvidia", + "rapids_conda_channels": "-c rapidsai -c conda-forge", "rapids_conda_packages": f"rapids={stable_version} python=3.13 'cuda-version>=12.0,<=12.9'", "rapids_pip_index": "https://pypi.nvidia.com", "rapids_pip_version": stable_version, # SageMaker Notebook Instance examples need to stay pinned to an older RAPIDS until this is resolved: # https://github.com/rapidsai/deployment/issues/520 - "rapids_sagemaker_conda_packages": "rapids=24.12 python=3.12 cuda-version=12.5", + "rapids_sagemaker_conda_packages": f"rapids={stable_version} python=3.12 cuda-version=13", }, "nightly": { "rapids_version": f"{nightly_version}", @@ -45,13 +45,13 @@ "rapids_container": f"rapidsai/base:{nightly_version + 'a'}-cuda12-py3.13", "rapids_notebooks_container": f"rapidsai/notebooks:{nightly_version + 'a'}-cuda12-py3.13", "rapids_conda_channel": "rapidsai-nightly", - "rapids_conda_channels": "-c rapidsai-nightly -c conda-forge -c nvidia", + "rapids_conda_channels": "-c rapidsai-nightly -c conda-forge", "rapids_conda_packages": f"rapids={nightly_version} python=3.13 'cuda-version>=12.0,<=12.9'", "rapids_pip_index": "https://pypi.anaconda.org/rapidsai-wheels-nightly/simple", "rapids_pip_version": f"{nightly_version}.*,>=0.0.0a0", # SageMaker Notebook Instance examples need to stay pinned to an older RAPIDS until this is resolved: # https://github.com/rapidsai/deployment/issues/520 - "rapids_sagemaker_conda_packages": "rapids=24.12 python=3.12 cuda-version=12.5", + "rapids_sagemaker_conda_packages": f"rapids={nightly_version} python=3.12 cuda-version=13", }, } rapids_version = ( From 3f7dbbcbf2963b2259e65c92e2e1c81ecfc687d2 Mon Sep 17 00:00:00 2001 From: Jacob Tomlinson Date: Wed, 17 Dec 2025 14:25:53 +0000 Subject: [PATCH 2/2] Add SageMaker AI branding --- source/cloud/aws/sagemaker.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/source/cloud/aws/sagemaker.md b/source/cloud/aws/sagemaker.md index 74b91851..097f47b8 100644 --- a/source/cloud/aws/sagemaker.md +++ b/source/cloud/aws/sagemaker.md @@ -6,7 +6,7 @@ review_priority: "p0" RAPIDS can be used in a few ways with [AWS SageMaker](https://aws.amazon.com/sagemaker/). -## SageMaker Notebooks +## SageMaker AI Notebooks To get started head to [the SageMaker AI console](https://console.aws.amazon.com/sagemaker/) and create a [new SageMaker Notebook Instance](https://console.aws.amazon.com/sagemaker/home#/notebook-instances/create). @@ -71,7 +71,7 @@ Then in Jupyter select the `rapids` kernel when working with a new notebook. Once inside JupyterLab you should be able to upload the [Running RAPIDS hyperparameter experiments at scale](/examples/rapids-sagemaker-higgs/notebook) example notebook and continue following those instructions. -## SageMaker Estimators +## SageMaker AI Estimators RAPIDS can also be used in [SageMaker Estimators](https://sagemaker.readthedocs.io/en/stable/api/training/estimators.html). Estimators allow you to launch training jobs on ephemeral VMs which SageMaker manages for you.