Install on Ubuntu with GPUs

Open a Terminal and ssh to the machine that will run Driverless AI. Once you are logged in, perform the following steps.

  1. Retrieve the Driverless AI package from https://www.h2o.ai/driverless-ai-download/.
  2. Install Docker on Ubuntu (if not already installed):
# Install Docker on Ubuntu
add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
apt-get update
apt-get install docker-ce
  1. Install nvidia-docker on Ubuntu (if not already installed):
# Install nvidia-docker on Ubuntu
wget -P /tmp https://github.com/NVIDIA/nvidia-docker/releases/download/v1.0.1/nvidia-docker_1.0.1-1_amd64.deb
dpkg -i /tmp/nvidia-docker*.deb
rm /tmp/nvidia-docker*.deb
  1. Verify that the NVIDIA driver is up and running. If the driver is not up and running, log on to http://www.nvidia.com/Download/index.aspx?lang=en-us to get the latest NVIDIA Tesla V/P/K series driver.
nvidia-smi
  1. Load the Driverless AI Docker image, replacing X.Y.Z below with your Driverless AI Docker image version (for example, 1.0.16).
# Load the Driverless AI docker image
docker load < driverless-ai-docker-runtime-rel-X.Y.Z.gz
  1. Set up the data, log, and license directories on the host machine:
# Set up the data, log, license, and tmp directories on the host machine
mkdir data
mkdir log
mkdir license
mkdir tmp
  1. At this point, you can copy data into the data directory on the host machine. The data will be visible inside the Docker container.
  2. Start the Driverless AI Docker image with nvidia-docker:
# Start the Driverless AI Docker image
nvidia-docker run \
    --rm \
    -u `id -u`:`id -g` \
    -p 12345:12345 \
    -p 54321:54321 \
    -p 9090:9090 \
    -v `pwd`/data:/data \
    -v `pwd`/log:/log \
    -v `pwd`/license:/license \
    -v `pwd`/tmp:/tmp \
    opsh2oai/h2oai-runtime

Driverless AI will begin running:

---------------------------------
Welcome to H2O.ai's Driverless AI
---------------------------------
   version: X.Y.Z

- Put data in the volume mounted at /data
- Logs are written to the volume mounted at /log/YYYYMMDD-HHMMSS
- Connect to Driverless AI on port 12345 inside the container
- Connect to Jupyter notebook on port 8888 inside the container
  1. Connect to Driverless AI with your browser:
http://Your-Driverless-AI-Host-Machine:12345

Install on Ubuntu with CPUs

This section describes how to install and start the Driverless AI Docker image on Ubuntu. Note that this uses Docker EE and not NVIDIA Docker. GPU support will not be available.

  1. Open a Terminal and ssh to the machine that will run Driverless AI. Once you are logged in, perform the following steps.
  2. Retrieve the Driverless AI package from https://www.h2o.ai/driverless-ai-download/.
  3. Install Docker on Ubuntu (if not already installed):
# Install Docker on Ubuntu
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -sudo apt-key fingerprint 0EBFCD88`
add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
apt-get update
apt-get install docker-ce
  1. Load the Driverless AI Docker image, replacing X.Y.Z below with your Driverless AI Docker image version (for example, 1.0.16):
# Load the Driverless AI Docker image
docker load < driverless-ai-docker-runtime-rel-X.Y.Z.gz
  1. Set up the data, log, license, and tmp directories on the host machine:
# Set up the data, log, license, and tmp directories
mkdir data
mkdir log
mkdir license
mkdir tmp
  1. At this point, you can copy data into the data directory on the host machine. The data will be visible inside the Docker container.
  2. Start the Driverless AI Docker image:
# Start the Driverless AI Docker image
docker run \
    --rm \
    -u `id -u`:`id -g` \
    -p 12345:12345 \
    -p 9090:9090 \
    -v `pwd`/data:/data \
    -v `pwd`/log:/log \
    -v `pwd`/license:/license \
    -v `pwd`/tmp:/tmp \
    opsh2oai/h2oai-runtime

Driverless AI will begin running:

---------------------------------
Welcome to H2O.ai's Driverless AI
---------------------------------
   version: X.Y.Z

- Put data in the volume mounted at /data
- Logs are written to the volume mounted at /log/YYYYMMDD-HHMMSS
- Connect to Driverless AI on port 12345 inside the container
- Connect to Jupyter notebook on port 8888 inside the container
  1. Connect to Driverless AI with your browser:
http://Your-Driverless-AI-Host-Machine:12345