Set Up

Expose GPUs on your runner

Use Dotscience for GPU-accelerated workflows

You can use Dotscience with NVIDIA GPU-accelerated workflows. At present, we do not support non-NVIDIA GPUs.

To access your machine’s NVIDIA GPUs from within the Dotscience Docker container that runs on the machine, you need to register NVIDIA GPU-aware container runtime. If you are using NVIDIA DGX servers, this runtime will already be installed. Otherwise, you may need to install it yourself.

There are two versions:

  1. The first generation of NVIDIA GPU-aware container runtime, released in 2016, is nvidia-docker.

  2. The second generation of NVIDIA GPU-aware container runtime is nvidia-container-runtime. This is the latest version.

Which container runtime do I have?

If you don’t know which container runtime is available on your system, try the following command:

$ docker run --runtime=nvidia --rm nvidia/cuda:9.0-base nvidia-smi

If this shows you a table with your GPU specifications, you have nvidia-container-runtime. If it instead shows an error, try:

nvidia-docker run --rm nvidia/cuda:9.0-base nvidia-smi

If this shows you a table with your GPU specifications, but the first command did not, then you have nvidia-docker. HOwever, if this command also shows an error, you do not have any NVIDIA container-aware runtime, and should install it.

Which container runtime do I need?

We recommend upgrading your runtime to nvidia-container-runtime if you can. Instructions for upgrading your container runtime are provided by NVIDIA here. However, both versions of the runtime are supported by Dotscience.

Expose your runner’s GPUs

1./ If you do not have any container runtime, install nvidia-container-runtime by following the NVIDIA documentation for an Ubuntu machine.

2./ On the Dotscience Runners page, under Settings select the runner type GPU (nvidia runtime) or GPU (nvidia docker) corresponding to your container runtime.