Linux / amd64
Linux / arm64
NVIDIA Modulus is a toolkit for developing AI enabled physics-ML applications.
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.
This is the open source version of Modulus. For enterprise supported NVAIE container, refer: Modulus Secured Feature Branch
Visit the NVIDIA Modulus for more information.
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 nvcr.io/nvidia/modulus/modulus:xx.xx bash
Where xx.xx is the container version. For example, 24.09.
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.
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 "nvcr.io/nvidia/modulus/modulus:24.09"
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 can be used on public cloud instances like AWS, GCP, and Azure. To run Modulus,
For key features, refer NVIDIA Modulus Release Notes
Please visit the Modulus Forum for:
By pulling and using the container, you accept the terms and conditions of this End User License Agreement.