Amazon Deep Learning AMI GPU TensorFlow 2.16 (Amazon Linux 2)
For help getting started, see Getting started with DLAMI.
AMI name format
Deep Learning Proprietary Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) ${YYYY-MM-DD}
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) ${YYYY-MM-DD}
Supported EC2 instances
Please refer to Important changes to DLAMI.
Deep Learning with OSS Nvidia Driver supports G4dn, G5, G6, Gr6, G6e, P4d, P4de, P5, P5e, P5en.
Deep Learning with Proprietary Nvidia Driver supports G3 (G3.16x not supported), P3, P3dn
The AMI includes the following:
Supported Amazon Service: EC2
Operating System: Amazon Linux 2
Compute Architecture: x86
Python: /opt/tensorflow/bin/python3.10
TensorFlow version: 2.16
NVIDIA Driver:
OSS Nvidia driver: 550.144.03
Proprietary Nvidia driver: 550.144.03
NVIDIA CUDA12 stack:
CUDA, NCCL and cuDDN installation path: /usr/local/cuda-12.2/
EFA Installer: 1.34.0
Amazon CLI v2 as aws2 and Amazon CLI v1 as aws
EBS volume type: gp3
Query AMI-ID with SSM Parameter (example region is us-east-1):
OSS Nvidia Driver:
aws ssm get-parameter --name /aws/service/deeplearning/ami/x86_64/oss-nvidia-driver-gpu-tensorflow-2.16-amazon-linux-2/latest/ami-id --region us-east-1 --query "Parameter.Value" --output text
Proprietary Nvidia Driver:
aws ssm get-parameter --name /aws/service/deeplearning/ami/x86_64/proprietary-nvidia-driver-gpu-tensorflow-2.16-amazon-linux-2/latest/ami-id --region us-east-1 --query "Parameter.Value" --output text
Query AMI-ID with AWSCLI (example region is us-east-1):
OSS Nvidia Driver:
aws ec2 describe-images --region us-east-1 --owners amazon --filters 'Name=name,Values=Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) ????????' 'Name=state,Values=available' --query 'reverse(sort_by(Images, &CreationDate))[:1].ImageId' --output text
Proprietary Nvidia Driver:
aws ec2 describe-images --region us-east-1 --owners amazon --filters 'Name=name,Values=Deep Learning Proprietary Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) ????????' 'Name=state,Values=available' --query 'reverse(sort_by(Images, &CreationDate))[:1].ImageId' --output text
Notice
NVIDIA Container Toolkit 1.17.4
In Container Toolkit version 1.17.4 the mounting of CUDA compat libraries is now disabled. In order to ensure compatibility with multiple CUDA versions on container workflows, please ensure you update your LD_LIBRARY_PATH to include your CUDA compatibility libraries as shown in under the "If you use a CUDA compatibility layer" tutorial here - https://docs.aws.amazon.com/sagemaker/latest/dg/inference-gpu-drivers.html#collapsible-cuda-compat
Future TensorFlow Operating System Updates
TensorFlow 2.16 will be the last DLAMI that utilizes the Ubuntu 20.04 Operating System. Starting with TensorFlow 2.17 and above, DLAMIs will begin to utilize Ubuntu 22.04 as the base Operating System. For customers looking to upgrade to these new versions, please ensure your workflows are ready for this upgrade.
Keras version pinned to 2.0 instead of 3.0
With the latest TF2.16 release, Keras has been upgraded from major version 2 to major version 3.0. This Keras version is a complete rewrite of the Keras package (please see the Keras 3 documentation
source /opt/tensorflow/bin/activate unset TF_USE_LEGACY_KERAS
Release Date: 2025-02-17
AMI Names:
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20250215
Deep Learning Proprietary Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20250215
Updated
Updated NVIDIA Container Toolkit from version 1.17.3 to version 1.17.4
Please see the release notes page here for more information: https://github.com/NVIDIA/nvidia-container-toolkit/releases/tag/v1.17.4
In Container Toolkit version 1.17.4, the mounting of CUDA compat libraries is now disabled. In order to ensure compatibility with multiple CUDA versions on container workflows, please ensure you update your LD_LIBRARY_PATH to include your CUDA compatibility libraries as shown in under the "If you use a CUDA compatibility layer" tutorial here - https://docs.aws.amazon.com/sagemaker/latest/dg/inference-gpu-drivers.html#collapsible-cuda-compat
Removed
Removed user space libraries cuobj and nvdisasm provided by NVIDIA CUDA toolkit
to address CVE's present in the NVIDIA CUDA Toolkit Security Bulletin for February 18, 2025
Release Date: 2025-01-20
AMI Names:
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20250120
Deep Learning Proprietary Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20250118
Updated
Upgraded Nvidia driver from version 550.127.05 to 550.144.03 to address CVE's present in the NVIDIA GPU Display Driver Security Bulletin for January 2025
Release Date: 2024-10-23
AMI Names:
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20241022
Deep Learning Proprietary Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20241023
Updated
Upgraded Nvidia driver from version 550.90.07 to 550.127.05 to address CVE's present in the NVIDIA GPU Display Security Bulletin for October 2024
Release Date: 2024-09-28
AMI Names:
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20240928
Deep Learning Proprietary Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20240928
Updated
Upgraded Nvidia Container Toolkit from version 1.16.1 to 1.16.2, addressing the security vulnerability CVE-2024-0133
.
Release Date: 2024-09-21
AMI Names:
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20240921
Deep Learning Proprietary Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20240921
Updated
Upgraded Nvidia driver and Fabric Manager from version 535.183.01 to 550.90.07
Upgraded EFA Version from 1.32.0 to 1.34.0
Updated PyTorch version from version 2.3.0 to 2.3.1
Added
Added support for P5e EC2 Instance on OSS Nvidia Driver Images.
Release Date: 2024-08-19
AMI Names:
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20240817
Added
Added support for G6e EC2 instance
.
Version 2.16.2 - Release Date: 2024-07-26
AMI Names:
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20240725
Updated
Updated TensorFlow patch version from version 2.16.1 to 2.16.2
Resolved incorrect TensorFlow minor version in DLAMI released on 2024-07-17
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20240717 release inadvertently contained TensorFlow minor version 2.17 rather than 2.16. Please ensure workflows reliant on TensorFlow 2.16 are upgrading to the latest DLAMI.
Version 2.16.1 - Release Date: 2024-06-10
AMI Names:
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20240607
Deep Learning Proprietary Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20240610
Updated
Updated Nvidia driver version to 535.183.01 from 535.161.08
Release Date: 2024-05-10
Please refer to Important changes to DLAMI
AMI Names:
Deep Learning Proprietary Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20240510
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) 20240510
Added
Initial release of:
Deep Learning Proprietary Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) series.
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.16 (Amazon Linux 2) series.
Software Includes the Following:
"nvidia-driver=535.161.08"
"fabric-manager=535.161.08"
"cuda=12.3"
"cudnn=8.9.7"
"efa=1.32.0"
"nccl=2.21.5"
"aws-nccl-ofi-plugin=v1.9.1-aws"
Added tensorflow virtual environment (activation command source /opt/tensorflow/bin/activate). This environment includes the following:
"tensorflow=2.16.1"
NOTE
Starting with TF2.16, the tf.estimator API is removed.
To continue using tf.estimator, you will need to use TF 2.15 or an earlier version. Please see the TensorFlow 2.16.1 release notes
for more information
To ensure compatibility with customer workflows, we have pinned Keras versions to 2.0 using the environment variable TF_USE_LEGACY_KERAS=1. If your workflows require usage of Keras 3.0, please remove this environment variable from your TensorFlow virtual environment /opt/tensorflow using the following script:
source /opt/tensorflow/bin/activate unset TF_USE_LEGACY_KERAS