PyTorch CUDA 12.2 - NVIDIA AI Workbench Default Container (Beta)
NVIDIA AI Workbench provides a set of default base images, referred to as Base Environments in the application, that can be used as the starting point when creating the container for a new project.
This is a CUDA image with CUDA 12.2 and Python 3.10 and JupyterLab installed. It is based off of https://catalog.ngc.nvidia.com/orgs/nvidia/containers/cuda.
AI Workbench is currently in Beta. To access the software and start using this conatiner, first sign up here: https://developer.nvidia.com/ai-workbench-early-access
All notable changes to this image are documented here
[1.0.1] - 2023-10-18
- First draft of image, based on nvidia/cuda:12.2.0-runtime-ubuntu22.04
- Installed curl git git-lfs python3 gcc python3-dev python3-pip vim
- Installed Jupyterlab 4.0.7
[1.0.3] - 2023-12-11
- Re-built with updated base image
Shared Responsibility Model
NVIDIA AI Workbench employs a shared responsibility model. The subset of responsibilities related to base images are:
- Updating base environment images with a newer tag in case a critical or high CVE is discovered.
- Providing prompt notifications in the case of updates via
- Notifications posted on the program DevZone site
- Email to the accounts registered in the Early Access program on DevZone
End User and Organization Responsibilities
- Following notifications from NVIDIA, ensuring the Default Base Images are updated to the latest versions to mitigate risks associated with vulnerabilities that might impact older images.