The NVIDIA Container Toolkit is required in order to use GPUs inside Docker containers.

Install Docker and NVIDIA Container Toolkit:

• https://docs.docker.com/engine/installation/
  • Be sure to use Docker's repositories for the latest version of Docker.
• https://github.com/NVIDIA/nvidia-docker/blob/master/README.md

The Dockerfile assumes a copy of the OmniSci tarball is in the same directory as the Dockerfile and is named omnisci-latest-Linux-x86_64.tar.gz.

To build the container, run:

mv omnisci-5.2.1-*-render.tar.gz omnisci-latest-Linux-x86_64.tar.gz
tar -xvf omnisci-latest-Linux-x86_64.tar.gz --strip-components=2 --no-anchored "docker/Dockerfile"
docker build .

where omnisci-5.2.1-*-render.tar.gz is the path to the OmniSci tarball.

The container image id will be output on the last line of the build step. To assign a custom name and tag:

docker build -t omnisci/omnisci:v5.2.1 .

which will assign the name omnisci/omnisci and the tag v5.2.1 to the image.

The data directory is at /omnisci-storage/data.

The config file lives at /omnisci-storage/omnisci.conf.

docker run -d \
  --gpus all \
  -p 6273:6273 \
  --name omnisci \
  -v /path/to/omnisci-storage:/omnisci-storage \
  omnisci/omnisci:v5.2.1

This starts OmniSciDB inside a container named omnisci, and exposes the Immerse visualization client on port 6273..

Data will be persisted to the host directory /path/to/omnisci-storage.