Linux DEBs¶
For Linux machines that will not use the Docker image or RPM, a DEB installation is available for x86_64 Ubuntu 16.04/18.04.
The installation steps assume that you have a license key for Driverless AI. For information on how to obtain a license key for Driverless AI, visit https://www.h2o.ai/products/h2o-driverless-ai/. Once obtained, you will be prompted to paste the license key into the Driverless AI UI when you first log in, or you can save it as a .sig file and place it in the license folder that you will create during the installation process.
Environment¶
Operating System |
Min Mem |
---|---|
Ubuntu with GPUs |
64 GB |
Ubuntu with CPUs |
64 GB |
Requirements¶
Ubuntu 16.04/Ubuntu 18.04
CUDA 10 or later with CUDA drivers and NVIDIA drivers >= 410 (GPU only). CUDA 10 is included in the Driverless AI package. Refer to the following for more information on how to install the CUDA and NVIDIA drivers:
cuDNN >=7.2.1 (Required for TensorFlow support on GPUs.)
OpenCL (Required for LightGBM support on GPUs.)
Driverless AI DEB, available from https://www.h2o.ai/download/
Note: Due to system library incompatibilities, Ubuntu 20.04 is not currently supported for native installations but Driverless AI Docker installation method supports Ubuntu 20.04.
About the Install¶
The ‘dai’ service user is created locally (in /etc/passwd) if it is not found by ‘getent passwd’. You can override the user by providing the DAI_USER environment variable during rpm or dpkg installation.
The ‘dai’ service group is created locally (in /etc/group) if it is not found by ‘getent group’. You can override the group by providing the DAI_GROUP environment variable during rpm or dpkg installation.
Configuration files are put in /etc/dai and owned by the ‘root’ user:
/etc/dai/config.toml: Driverless AI config file (See Using the config.toml File section for details)
/etc/dai/User.conf: Systemd config file specifying the service user
/etc/dai/Group.conf: Systemd config file specifying the service group
/etc/dai/EnvironmentFile.conf: Systemd config file specifying (optional) environment variable overrides
Software files are put in /opt/h2oai/dai and owned by the ‘root’ user
The following directories are owned by the service user so they can be updated by the running software:
/opt/h2oai/dai/home: The application’s home directory (license key files are stored here)
/opt/h2oai/dai/tmp: Experiments and imported data are stored here
/opt/h2oai/dai/log: Log files go here if you are not using systemd (if you are using systemd, then the use the standard journalctl tool)
By default, Driverless AI looks for a license key in /opt/h2oai/dai/home/.driverlessai/license.sig. If you are installing Driverless AI programmatically, you can copy a license key file to that location. If no license key is found, the application will interactively guide you to add one from the Web UI.
systemd unit files are put in /usr/lib/systemd/system
Symbolic links to the configuration files in /etc/dai files are put in /etc/systemd/system
If your environment is running an operational systemd, that is the preferred way to manage Driverless AI. The package installs the following systemd services and a wrapper service:
dai: Wrapper service that starts/stops the other three services
dai-dai: Main Driverless AI process
dai-h2o: H2O-3 helper process used by Driverless AI
dai-procsy: Procsy helper process used by Driverless AI
dai-vis-server: Visualization server helper process used by Driverless AI
If you don’t have systemd, you can also use the provided run script to start Driverless AI.
Starting NVIDIA Persistence Mode (GPU only)¶
If you have NVIDIA GPUs, you must run the following NVIDIA command. This command needs to be run every reboot. For more information: http://docs.nvidia.com/deploy/driver-persistence/index.html.
sudo nvidia-persistenced --persistence-mode
Install OpenCL¶
OpenCL is required in order to run LightGBM on GPUs. Run the following for Ubuntu-based ystems.
sudo apt-get install opencl-headers clinfo ocl-icd-opencl-dev
mkdir -p /etc/OpenCL/vendors && \
echo "libnvidia-opencl.so.1" > /etc/OpenCL/vendors/nvidia.icd
Installing the Driverless AI Linux DEB¶
Run the following commands to install the Driverless AI DEB. Replace VERSION with your specific version.
# Install Driverless AI.
sudo dpkg -i dai_VERSION.deb
By default, the Driverless AI processes are owned by the ‘dai’ user and ‘dai’ group. You can optionally specify a different service user and group as shown below. Replace <myuser> and <mygroup> as appropriate.
# Temporarily specify service user and group when installing Driverless AI.
# dpkg saves these for systemd in the /etc/dai/User.conf and /etc/dai/Group.conf files.
sudo DAI_USER=myuser DAI_GROUP=mygroup dpkg -i dai_VERSION.deb
You may now optionally make changes to /etc/dai/config.toml.
Starting Driverless AI¶
If you have systemd (preferred):
# Start Driverless AI.
sudo systemctl start dai
If you do not have systemd:
# Start Driverless AI.
sudo -H -u dai /opt/h2oai/dai/run-dai.sh
Looking at Driverless AI log files¶
If you have systemd (preferred):
sudo systemctl status dai-dai
sudo systemctl status dai-h2o
sudo systemctl status dai-procsy
sudo systemctl status dai-vis-server
sudo journalctl -u dai-dai
sudo journalctl -u dai-h2o
sudo journalctl -u dai-procsy
sudo journalctl -u dai-vis-server
If you do not have systemd:
sudo less /opt/h2oai/dai/log/dai.log
sudo less /opt/h2oai/dai/log/h2o.log
sudo less /opt/h2oai/dai/log/procsy.log
sudo less /opt/h2oai/dai/log/vis-server.log
Stopping Driverless AI¶
If you have systemd (preferred):
# Stop Driverless AI.
sudo systemctl stop dai
# The processes should now be stopped. Verify.
sudo ps -u dai
If you do not have systemd:
# Stop Driverless AI.
sudo pkill -U dai
# The processes should now be stopped. Verify.
sudo ps -u dai
Upgrading Driverless AI¶
WARNINGS:
This release deprecates experiments and MLI models from 1.7.0 and earlier.
Experiments, MLIs, and MOJOs reside in the Driverless AI tmp directory and are not automatically upgraded when Driverless AI is upgraded. We recommend you take the following steps before upgrading.
Build MLI models before upgrading.
Build MOJO pipelines before upgrading.
Stop Driverless AI and make a backup of your Driverless AI tmp directory before upgrading.
If you did not build MLI on a model before upgrading Driverless AI, then you will not be able to view MLI on that model after upgrading. Before upgrading, be sure to run MLI jobs on models that you want to continue to interpret in future releases. If that MLI job appears in the list of Interpreted Models in your current version, then it will be retained after upgrading.
If you did not build a MOJO pipeline on a model before upgrading Driverless AI, then you will not be able to build a MOJO pipeline on that model after upgrading. Before upgrading, be sure to build MOJO pipelines on all desired models and then back up your Driverless AI tmp directory.
The upgrade process inherits the service user and group from /etc/dai/User.conf and /etc/dai/Group.conf. You do not need to manually specify the DAI_USER or DAI_GROUP environment variables during an upgrade.
Requirements¶
As of 1.7.0, CUDA 9 is no longer supported. Your host environment must have CUDA 10.0 or later with NVIDIA drivers >= 410 installed (GPU only). Driverless AI ships with its own CUDA libraries, but the driver must exist in the host environment. Go to https://www.nvidia.com/Download/index.aspx to get the latest NVIDIA Tesla V/P/K series driver.
Upgrade Steps¶
If you have systemd (preferred):
# Stop Driverless AI.
sudo systemctl stop dai
# Make a backup of /opt/h2oai/dai/tmp directory at this time.
# Upgrade Driverless AI.
sudo dpkg -i dai_NEWVERSION.deb
sudo systemctl daemon-reload
sudo systemctl start dai
If you do not have systemd:
# Stop Driverless AI.
sudo pkill -U dai
# The processes should now be stopped. Verify.
sudo ps -u dai
# Make a backup of /opt/h2oai/dai/tmp directory at this time. If you do not, all previous data will be lost.
# Upgrade and restart.
sudo dpkg -i dai_NEWVERSION.deb
sudo -H -u dai /opt/h2oai/dai/run-dai.sh
Uninstalling Driverless AI¶
If you have systemd (preferred):
# Stop Driverless AI.
sudo systemctl stop dai
# The processes should now be stopped. Verify.
sudo ps -u dai
# Uninstall Driverless AI.
sudo dpkg -r dai
# Purge Driverless AI.
sudo dpkg -P dai
If you do not have systemd:
# Stop Driverless AI.
sudo pkill -U dai
# The processes should now be stopped. Verify.
sudo ps -u dai
# Uninstall Driverless AI.
sudo dpkg -r dai
# Purge Driverless AI.
sudo dpkg -P dai
CAUTION! At this point you can optionally completely remove all remaining files, including the database (this cannot be undone):
sudo rm -rf /opt/h2oai/dai
sudo rm -rf /etc/dai
Note: The UID and GID are not removed during the uninstall process. These can be removed with userdel
and usergroup
. However, we DO NOT recommend removing the UID and GID if you plan to re-install Driverless AI. If you remove the UID and GID and then reinstall Driverless AI, the UID and GID will likely be re-assigned to a different (unrelated) user/group in the future; this may cause confusion if there are any remaining files on the filesystem referring to the deleted user or group.
Common Problems¶
Start of Driverless AI fails on the message ``Segmentation fault (core dumped)`` on Ubuntu 18.
This problem is caused by the font NotoColorEmoji.ttf
, which cannot be processed by the Python matplotlib library. A workaround is to disable the font by renaming it. (Do not use fontconfig because it is ignored by matplotlib.) The following will print out the command that should be executed.
sudo find / -name "NotoColorEmoji.ttf" 2>/dev/null | xargs -I{} echo sudo mv {} {}.backup