What is Modulus?

NVIDIA Modulus is an open-source framework for building, training, and fine-tuning Physics-ML models.

With NVIDIA Modulus, 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. Whether you are exploring the use of Neural operators like Fourier Neural Operators or interested in Physics informed Neural Networks or a hybrid approach in between, Modulus provides you with the optimized stack that will enable you to train your models at real world scale.

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

Visit the NVIDIA Modulus for more information. Modulus Documentation

Getting Started with Modulus

Running Modulus 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/modulus/modulus:xx.xx bash

Where xx.xx is the container version. For example, 24.01.

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

Modulus on DGX Cloud (Base Command Platform)

Jobs using the Modulus 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/modulus/modulus:24.01"

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

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

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

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 Modulus Docker container.

For key features, refer NVIDIA Modulus Release Notes

Modulus Resources

Modulus GitHub

Modulus Documentation

Modulus reference applications

Compatible Infrastructure Software Versions

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

• NVIDIA AI Enterprise Infrastructure 5

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.

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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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