PyTorch CUDA 11.7 - 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 11.7 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

CHANGELOG

All notable changes to this image are documented here

[1.0.1] - 2023-10-18

• First draft of image, based on nvidia/cuda:11.7.0-devel-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:

NVIDIA Responsibilities

1. Updating base environment images with a newer tag in case a critical or high CVE is discovered.
2. 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

1. 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.