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PhysicsNeMo Secured Feature Branch

PhysicsNeMo Secured Feature Branch

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Associated Products
Features
Description
NVIDIA PhysicsNeMo is an open-source framework for building, training, and fine-tuning Physics-ML models. 
Publisher
NVIDIA
Latest Tag
25.06.01
Modified
July 24, 2025
Compressed Size
16.78 GB
Multinode Support
No
Multi-Arch Support
Yes
25.06.01 (Latest) Security Scan Results

Linux / arm64

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Linux / amd64

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What is PhysicsNeMo?

NVIDIA PhysicsNeMo is a toolkit for developing AI enabled physics-ML applications.

With NVIDIA PhysicsNeMo, we aim to provide researchers and industry specialists, with various tools that will help accelerate your development of such models for the scientific discipline of your need.

This is the NVAIE container of PhysicsNeMo. For opensource container, refer: https://catalog.ngc.nvidia.com/orgs/nvidia/teams/physicsnemo/containers/physicsnemo

Visit NVIDIA PhysicsNeMo for more information.

Visit PhysicsNeMo Documentation for documentation.

Running PhysicsNeMo Using Docker

If you have Docker 19.03 or later, a typical command to launch the container with an interactive bash terminal is:

docker run --gpus all --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 --runtime nvidia --rm -it nvidia/physicsnemo/physicsnemo-sfb:xx.xx bash

Where xx.xx is the container version. For example, 25.06.

Once inside the container, you can clone the PhysicsNeMo repositories from GitHub and use the samples and examples provided to get started with PhysicsNeMo. Refer the Getting Started Guide for more details.

PhysicsNeMo on DGX Cloud (Base Command Platform)

Jobs using the PhysicsNeMo NGC Container on Base Command Platform clusters can be launched either by using the NGC CLI tool or by using the Base Command Platform Web UI. To use the NGC CLI tool, configure the Base Command Platform user, team, organization, and cluster information using the ngc config command as described here.

An example command to launch the container on a single-GPU instance is:

ngc batch run --name "My-1-GPU-Modulus-job" --instance dgxa100.80g.1.norm --commandline "sleep 30" --result /results --image "nvidia/physicsnemo/physicsnemo-sfb:xx.xx"

For details on running Modulus in Multi-GPU/Multi-Node configuration, refer this Technical Blog and Modulus Documentation

For more details on running on DGX Cloud, please refer NVIDIA BCP User Guide

PhysicsNeMo on Public Cloud instances (AWS, GCP, and Azure)

PhysicsNeMo can be used on public cloud instances like AWS, GCP, and Azure. To run PhysicsNeMo,

  1. Get your GPU instance on AWS, GCP, or Azure.
  2. Use the NVIDIA GPU-Optimized VMI on the cloud instance. For detailed instructions on setting up VMI refer NGC Certified Public Clouds.
  3. Once the instance spins up, follow the above instructions to load the PhysicsNeMo Docker container.

For key features, refer NVIDIA PhysicsNeMo Release Notes

Security Vulnerabilities in Open Source Packages

Please review the Security Scanning tab to view the latest security scan results. For certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.

Compatible Infrastructure Software Versions

For optimal performance, deploy the supported NVIDIA AI Enterprise Infrastructure software with this container.

  1. NVIDIA AI Enterprise Infrastructure 6

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NVIDIA AI Enterprise Documentation

Visit the NVIDIA AI Enterprise Documentation Hub for release documentation, deployment guides and more.

License

This container is licensed under the NVIDIA AI Product Agreement. By pulling and using this container, you accept the terms and conditions of this license.

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