Deep Learning AMI GPU TensorFlow 2.18 (Ubuntu 22.04)
For help getting started, see Getting started with DLAMI.
AMI name format
Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.18 (Ubuntu 22.04) ${YYYY-MM-DD}
Supported EC2 instances
Deep Learning with OSS Nvidia Driver supports G4dn, G5, G6, Gr6, G6e, P4d, P4de, P5, P5e, P5en.
The AMI includes the following:
Supported Amazon Service: Amazon EC2
Operating System: Ubuntu 22.04
Compute Architecture: x86
Python: /opt/tensorflow/bin/python3.12
TensorFlow version: 2.18
NVIDIA Driver:
OSS Nvidia driver: 550.144.03
NVIDIA CUDA12 stack:
CUDA, NCCL and cuDDN installation path: /usr/local/cuda-12.5/
EFA Installer: 1.37.0
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 --regionus-east-1\ --name /aws/service/deeplearning/ami/x86_64/oss-nvidia-driver-gpu-tensorflow-2.18-ubuntu-22.04/latest/ami-id \ --query "Parameter.Value" \ --output text
Query AMI-ID with AWSCLI (example Region is us-east-1):
OSS Nvidia Driver:
aws ec2 describe-images --regionus-east-1\ --owners amazon --filters 'Name=name,Values=Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.18 (Ubuntu 22.04) ????????' 'Name=state,Values=available' \ --query 'reverse(sort_by(Images, &CreationDate))[:1].ImageId' \ --output text
Release Date: 2025-02-17
AMI name: Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.18 (Ubuntu 22.04) 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 the If you use a CUDA compatibility layer tutorial.
Removed
Removed user space libraries cuobj and nvdisasm provided by NVIDIA CUDA toolkit
to address CVEs present in the NVIDIA CUDA Toolkit Security Bulletin for February 18, 2025
Release Date: 2025-01-20
AMI name: Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.18 (Ubuntu 22.04) 20250118
Updated
Upgraded Nvidia driver from version 550.90.07 to 550.127.05 to address CVEs present in the NVIDIA GPU Display Driver Security Bulletin for January 2025
Release Date: 2024-12-09
AMI name: Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.18 (Ubuntu 22.04) 20241206
Added
Initial release of the Deep Learning OSS Nvidia Driver AMI GPU TensorFlow 2.18 (Ubuntu 22.04) series.
Software Includes the Following:
"nvidia-driver=550.127.05"
"fabric-manager=550.127.05"
"cuda=12.5"
"cudnn=9.5.1"
"efa=1.37.0"
"nccl=2.23.4"
“aws-nccl-ofi-plugin=v1.13.0-aws“
Tensorflow virtual environment (activation command source /opt/tensorflow/bin/activate) includes the following:
“tensorflow=2.18.0”
Fixed
Due to a change in the Ubuntu kernel to address a defects in the Kernel Address Space Layout Randomization (KASLR) functionality, G4Dn/G5 instances are unable to properly initialize CUDA on the OSS Nvidia driver. In order to mitigate this issue, this DLAMI includes functionality that dynamically loads the proprietary driver for G4Dn and G5 instances. Please allow a brief initialization period for this loading in order to ensure that your instances are able to work properly.
To check the status and health of this service, you can use the following commands:
sudo systemctl is-active dynamic_driver_load.serviceactive