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. 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 promted 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 9 or 9.2 - cuDNN >=7.2.1 (Required only if using TensorFlow.) - Driverless AI DEB, available from https://www.h2o.ai/download/. About the Install ~~~~~~~~~~~~~~~~~ .. include:: linux-rpmdeb-about.frag Installing the Driverless AI Linux DEB ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Run the following commands to install the Driverless AI DEB. Replace with your specific version. :: # Optionally install libraries to enable PDF documentation generation. sudo apt-get update sudo apt-get install -y libcairo2 libpango1.0-0 # 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 and 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 NVIDIA persistence Mode ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ If you have NVIDIA GPUs, perform the following two NVIDIA commands to improve performance. For more information: http://docs.nvidia.com/deploy/driver-persistence/index.html. :: sudo nvidia-persistenced --user dai sudo nvidia-smi -pm 1 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.out sudo less /opt/h2oai/dai/log/h2o.out sudo less /opt/h2oai/dai/log/procsy.out sudo less /opt/h2oai/dai/log/vis-server.out 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 ~~~~~~~~~~~~~~~~~~~~~~~ **WARNING**: This is currently alpha software status. Back up your data (especially the Driverless AI tmp directory) before attempting. **WARNING**: Experiments, MLIs, and MOJOs are not automatically upgraded when Driverless AI is upgraded. - Build MLI models before upgrading. - Build MOJO pipelines 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. 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. If you have systemd (preferred): :: # Stop Driverless AI. sudo systemctl stop dai # Back up your /opt/h2oai/dai/tmp directory at this time. If you do not, all previous data will be lost. # 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 # Back up your /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