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