.. _Installing Driverless AI:

Installing  and Upgrading Driverless AI
=======================================

For the best (and intended-as-designed) experience, install Driverless AI on modern data center hardware with GPUs and CUDA support. Use Pascal or Volta GPUs with maximum GPU memory for best results. (Note that the older K80 and M60 GPUs available in EC2 are supported and very convenient, but not as fast.) 

Driverless AI supports local, LDAP, and PAM authentication. Authentication can be configured by setting environment variables or via a config.toml file. Refer to the :ref:`setting_environment_variables` section for more information.

Driverless AI also supports HDFS, S3, Google Cloud Storage, Google Big Query, KDB, Minio, and Snowflake access. Support for these data sources can be configured by setting environment variables for the data connectors or via a config.toml file. Refer to the :ref:`Data Connectors` section for more information.

**Sizing Requirements for Native Installs**

Driverless AI requires a minimum of 5 GB of system memory in order to start experiments and a minimum of 5 GB of disk space in order to run a small experiment. Note that these limits can changed in the config.toml file. We recommend that you have lots of system CPU memory (64 GB or more) and 1 TB of free disk space available. 

**Sizing Requirements for Docker Installs**

For Docker installs, we recommend 1 TB of free disk space. Driverless AI uses approximately 38 GB. In addition, the unpacking/temp files require space on the same Linux mount **/var** during installation. Once DAI runs, the mounts from the Docker container can point to other file system mount points.

**GPU Sizing Requirements**

If you are running Driverless AI with GPUs, be sure that your GPU has compute capacity >=3.5 and at least 4GB of RAM. If these requirements are not met, then Driverless AI will switch to CPU-only mode.

**Note about nvidia-docker 1.0**

If you have nvidia-docker 1.0 installed, you need to remove it and all existing GPU containers. Refer to https://github.com/NVIDIA/nvidia-docker/blob/master/README.md for more information.

**Virtual Memory Settings in Linux**

If you are running Driverless AI on a Linux machine, we recommend setting the overcommit memory to 0.  The setting can be changed by the following command:

::

   sudo echo 0 > /proc/sys/vm/overcommit_memory 

This is the default value and it indicates that the Linux kernel is free to overcommit memory.  If this value is set to 2, then the Linux kernel will not overcommit memory.  In this case, the memory requirements of Driverless AI may surpass the memory allocation limit which would prevent the experiment from completing. 

.. toctree::
   :maxdepth: 2
   :caption: Available Installation Platforms

   install/linux-docker-images
   install/linux-rpm
   install/linux-deb
   install/linux-tarsh
   install/linux-in-the-cloud
   install/mac-osx
   install/windows
   install/ibm-power