Pulling And Running NVIDIA AI Enterprise Containers

Pulling NVIDIA AI Enterprise Containers

NVIDIA AI Enterprise 2.0 or later

To get started with NVIDIA AI Enterprise in the Cloud, you will need to pull the necessary NVIDIA AI Enterprise containers, based on your use case, from the Enterprise Catalog on NGC. Instructions for pulling NVIDIA AI Enterprise containers can found in the Installing AI and Data Science Applications and Frameworks of the Virtualization Deployment Guide. The following container pull commands for cloud VMI’s are indicated below:

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            docker pull nvcr.io/nvaie/nvidia-rapids-<NVAIE-MAJOR-VERSION>:<NVAIE-CONTAINER-TAG>
docker pull nvcr.io/nvaie/pytorch-<NVAIE-MAJOR-VERSION>:<NVAIE-CONTAINER-TAG>
docker pull nvcr.io/nvaie/tao-toolkit-lm-<NVAIE-MAJOR-VERSION>:<NVAIE-CONTAINER-TAG>
docker pull nvcr.io/nvaie/tao-toolkit-pyt-<NVAIE-MAJOR-VERSION>:<NVAIE-CONTAINER-TAG>
docker pull nvcr.io/nvaie/tao-toolkit-tf-<NVAIE-MAJOR-VERSION>:<NVAIE-CONTAINER-TAG>
docker pull nvcr.io/nvaie/tensorflow-<NVAIE-MAJOR-VERSION>:<NVAIE-CONTAINER-TAG>
docker pull nvcr.io/nvaie/tensorrt-<NVAIE-MAJOR-VERSION>:<NVAIE-CONTAINER-TAG>
docker pull nvcr.io/nvaie/tritonserver-<NVAIE-MAJOR-VERSION>:<NVAIE-CONTAINER-TAG>

Note

OCI VMI’s and instances are supported with NVIDIA AI Enterprise 3.0 or later.

Preparing To Run Containers

To ensure your cloud instance is GPU accelerated, use docker run –gpus to run NVIDIA AI Enterprise containers in your cloud VMI instance.

Example using all GPUs

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            $ docker run --gpus all

Example using two GPUs

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            $ docker run --gpus 2

Example using specific GPUs

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            $ docker run --gpus "device=1,2" ... $ docker run --gpus "device=UUID-ABCDEF,1"

Running An NVIDIA AI Enterprise Container

To run NVIDA AI Enterprise containers in your cloud VMI, refer to the Enterprise Catalog on NGC for the correct pull tag to use for a specific container, then enter the following docker images:

Example: MNIST Training Run Using PyTorch Container

Log in to your cloud VMI instance via a terminal to run the MNIST example.

Note that the PyTorch example will download the MNIST dataset from the web.

Pull and run the PyTorch container:

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            docker pull nvcr.io/nvaie/pytorch-2-0:22.02-nvaie-2.0-py3

docker run --gpus all --rm -it nvcr.io/nvaie/pytorch-2-0:22.02-nvaie-2.0-py3

Run the MNIST example:

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            cd /workspace/examples/upstream/mnist

python main.py