Deployment Guide for DoMINO-Automotive-Aero NIM#

Use this documentation for details about how to deploy the DoMINO-Automotive-Aero NIM.

Important

Before you can use this documentation, you must satisfy all prerequisites.

View available NIM container information#

Container image tags can be seen with the following command using NGC CLI, similar to other container images on NGC.

ngc registry image info nvcr.io/nim/nvidia/domino-automotive-aero:1.0.0

Pull the container image#

Pull the container image using one of the following commands:

Docker#

docker pull nvcr.io/nim/nvidia/domino-automotive-aero:1.0.0

NGC CLI#

ngc registry image pull nvcr.io/nim/nvidia/domino-automotive-aero:1.0.0

Run the Container#

As in the quickstart guide, you can run the following command to start the CorrDiff NIM:

export NGC_API_KEY=<NGC API Key>

docker run --rm --name domino-automotive-aero --runtime=nvidia --gpus 1 --shm-size 2g \
    -p 8000:8000 \
    -e NGC_API_KEY \
    -t nvcr.io/nim/nvidia/domino-automotive-aero:1.0.0

The following is an overview of the command and its options as well as others available at NIM startup:

  • docker run — This is the command to run a new container from a Docker image.

  • --rm — This flag tells Docker to automatically remove the container when it exits. This property is useful for one-off runs or testing, as it prevents the container from being left behind.

  • --name domino-automotive-aero — This flag gives the container the name “domino-automotive-aero”.

  • --runtime=nvidia — This flag specifies the runtime to use for the container. In this case, it is set to “nvidia,” which is used for GPU acceleration.

  • --gpus 1 — Allocate one GPU from the host machine to the container, allowing NIM to use that GPU for processing.

  • --shm-size 2g — Allocate host memory for Triton to use. You might need to increase this depending on deployment.

  • -p 8000:8000 — This flag maps port 8000 on the host machine to port 8000 in the container. This allows you to access the container’s services from the host machine.

  • -e NGC_API_KEY — This passes the NGC_API_KEY environment variable (and the value set in the parent terminal) to the container. This is used for authentication with NVIDIA’s NGC (NVIDIA GPU Cloud) service, including downloading the model data.

Note

If you encounter I/O permission errors when downloading models, you can add the -u $(id -u) flag to the docker run command. This uses the same user as your system user inside the NIM container to avoid permission mismatches when downloading models in your local cache directory.

Checking the status of the CorrDiff NIM#

You can view running docker containers on your system by using the following command:

docker ps

This returns output that looks like the following if the NIM is running:

CONTAINER ID   IMAGE                 COMMAND                  CREATED          STATUS          PORTS                                                                                                          NAMES
71af90daa69d   domino-automotive-aero   "/bin/bash -c $SERVE…"   About an hour ago   Up About an hour   0.0.0.0:8000->8000/tcp, :::8000->8000/tcp, 0.0.0.0:8080->8080/tcp, :::8080->8080/tcp   test

The first column in the output is the docker container ID, which can be useful for interacting with the container. The remaining fields described the image the container is running, the command (in this case, the NIM server software), when the container was built, its status, how long it has been running, any open ports, and finally its name (given by the startup command).

To check that the NIM is fully started and healthy, use the health API which returns a 200 response if NIM is ready:

curl -X 'GET' \
    'http://localhost:8000/v1/health/ready' \
    -H 'accept: application/json'

Stop a running container#

If for some reason your container has entered a state in which you cannot interact with it, or for any reason it must be stopped, you can use the kill command with the ID obtained from the docker ps command. This immediately terminates the running container.

Note

Any in-flight requests are canceled, and data might be lost.

The following example stops the running container using the ID from the previous example.

docker kill 71af90daa69d
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