Dockerfiles with rolling-release Lambda Stack, designed for use with nvidia-container-toolkit
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Ensure that you have a docker version > 19.03. On Ubuntu, you can simply run
sudo apt-get install docker.io
. On a different OS, or if you prefer to use upstream docker, follow Docker's installation instructions -
If using Lambda Stack on your host machine, install nvidia-container-toolkit with
sudo apt-get install nvidia-container-toolkit
. Otherwise, follow NVIDIA's installation instructions
Build the image with the appropriate command for the distribution you wish to use.
sudo docker build -t lambda-stack:18.04 -f Dockerfile.bionic .
sudo docker build -t lambda-stack:20.04 -f Dockerfile.focal .
sudo docker build -t lambda-stack:22.04 -f Dockerfile.jammy .
Note that building these docker images requires acceptance of the cuDNN license agreement
Here's a simple PyTorch test to make sure that your GPUs are usable in your docker images
$ sudo docker run --gpus 2 lambda-stack:22.04 python3 -c "import torch; print(torch.cuda.device_count())"
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