Docker Open Source GPU
These are the steps to install OmniSci as a Docker container on an Ubuntu machine running with NVIDIA Kepler or Pascal series GPU cards.
Prepare your host by installing NVIDIA drivers, Docker, and NVIDIA runtime.
To install NVIDIA drivers, open a terminal window on the host. Run
apt update
and apt upgrade
to ensure that you are using the latest operating system software.sudo apt update
sudo apt upgrade
Use
apt-get
to install required utilities.sudo apt-get install \
apt-transport-https \
ca-certificates \
curl \
gnupg-agent \
software-properties-common
Reboot your system to activate all of your changes.
sudo reboot
Verify that the gcc compiler is installed with the following command.
gcc --version
If no version information returns, run the following command.
sudo apt install gcc
To install the CUDA package.
- 2.Select the target platform by selecting the operating system (Linux), architecture (based on your environment), distribution (Ubuntu), version (based on your environment), and installer type (OmniSci recommends deb (network)).
- 3.Install the CUDA package using the installation instructions on the NVIDIA web site.
- 4.Reboot your system to ensure that all changes are active:sudo reboot
Remove any existing Docker installs and the legacy NVIDIA docker runtime.
sudo docker volume ls -q -f driver=nvidia-docker | xargs -r -I{} -n1 docker ps -q -a -f volume={} | xargs -r docker rm -f
sudo apt-get purge nvidia-docker
Remove Docker.
sudo apt-get remove docker docker-engine docker.io containerd runc
Update with apt-get.
sudo apt-get update
Use
curl
to download the latest Docker version.sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
Add Docker to your Apt repository.
sudo add-apt-repository \
"deb [arch=amd64] https://download.docker.com/linux/ubuntu \
$(lsb_release -cs) \
stable"
Update your repository.
sudo apt-get update
Install Docker, the command line interface, and the container runtime.
sudo apt-get install docker-ce docker-ce-cli containerd.io
Optional: Run the following
usermod
command so that docker command execution does not require sudo privilege. Log out and log back in for the changes to take effect.sudo usermod -aG docker $USER
Verify your Docker installation.
sudo docker run hello-world
Use
curl
to add a gpg key:curl -s -L https://nvidia.github.io/nvidia-container-runtime/gpgkey | \
sudo apt-key add -
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
Update your sources list:
curl -s -L https://nvidia.github.io/nvidia-container-runtime/$distribution/nvidia-container-runtime.list | \
sudo tee /etc/apt/sources.list.d/nvidia-container-runtime.list
Update apt-get and install nvidia-container-runtime:
sudo apt-get update
sudo apt-get install -y nvidia-container-runtime
Edit /etc/docker/daemon.json to add the following, and save the changes:
{
"default-runtime": "nvidia",
"runtimes": {
"nvidia": {
"path": "/usr/bin/nvidia-container-runtime",
"runtimeArgs": []
}
}
}
Restart the Docker daemon:
sudo pkill -SIGHUP dockerd
Checkpoint
Verify Docker and NVIDIA runtime work together.
sudo docker run --runtime=nvidia --rm nvidia/cuda:10.0-runtime-ubuntu18.04 nvidia-smi
Standard NVIDIA-SMI output shows the GPUs in your instance.

Download OmniSci from DockerHub and Start OmniSci in Docker.
sudo docker run --runtime=nvidia \
-d --runtime=nvidia \
-v /var/lib/omnisci:/omnisci-storage \
-p 6273-6280:6273-6280 \
omnisci/omnisci-ee-cuda:v5.4.2
On startup, you receive the following error:
config file does not exist, ignoring --config /omnisci-storage/omnisci.conf
This is expected behavior, because OmniSci does not ship with a default omnisci.conf file.
To use OmniSci with the capabilities enabled by omnisci.conf:
- 1.Stop OmniSci.
- 2.
- 3.Restart OmniSci.
You can access the command line in the Docker image to perform configuration and run OmniSci utilities.
You need to know the
container-id
to access the command line. Use the command below to list the running containers.sudo docker container ls
You see output similar to the following.
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
9e01e520c30c omnisci/omnisci-ee-cpu "/bin/sh -c '/omnisci..." 3 days ago Up 3 days 0.0.0.0:6273-6280->6273-6280/tcp confident_neumann
Once you have your container ID, you can access the command line using the Docker exec command. For example, here is the command to start a Bash session in the Docker instance listed above. The
-it
switch makes the session interactive.sudo docker exec -it 9e01e520c30c bash
You can end the Bash session with the
exit
command.Note | On Ubuntu, nvidia-docker has a dependency on nvidia-modprobe . If you receive the message: Error: Could not load UVM kernel module. Is nvidia-modprobe installed? you can install nvidia-modprobe using the following commands. |
On Ubuntu,
nvidia-docker
has a dependency on nvidia-modprobe
. If you receive the message: Error: Could not load UVM kernel module. Is nvidia-modprobe installed?
you can install nvidia-modprobe
using the following commands.sudo apt-add-repository multiverse
sudo apt update
sudo apt install nvidia-modprobe
To verify that all systems are go, load some sample data and perform an
omnisql
query.OmniSci ships with two sample datasets of airline flight information collected in 2008, and one dataset of New York City census information collected in 2015. To install the sample data, run the following command.
sudo docker exec -it <container-id> ./insert_sample_data
Where <container-id> is the container in which OmniSci is running.
When prompted, choose whether to insert dataset 1 (7,000,000 rows), dataset 2 (10,000 rows), or dataset 3 (683,000 rows). The examples below use dataset 2.
Enter dataset number to download, or 'q' to quit:
# Dataset Rows Table Name File Name
1) Flights (2008) 7M flights_2008_7M flights_2008_7M.tar.gz
2) Flights (2008) 10k flights_2008_10k flights_2008_10k.tar.gz
3) NYC Tree Census (2015) 683k nyc_trees_2015_683k nyc_trees_2015_683k.tar.gz
Connect to OmniSciDB by entering the following command (default password is HyperInteractive):
docker exec -it <container-id> /omnisci/bin/omnisql
password: ••••••••••••••••
Enter a SQL query such as the following:
omnisql> SELECT origin_city AS "Origin", dest_city AS "Destination", AVG(airtime) AS
"Average Airtime" FROM flights_2008_10k WHERE distance < 175 GROUP BY origin_city,
dest_city;
The results should be similar to the results below.
Origin|Destination|Average Airtime
Austin|Houston|33.055556
Norfolk|Baltimore|36.071429
Ft. Myers|Orlando|28.666667
Orlando|Ft. Myers|32.583333
Houston|Austin|29.611111
Baltimore|Norfolk|31.714286
Last modified 1yr ago