Linux Docker Images¶
To simplify local installation, Driverless AI is provided as a Docker image for the following system combinations:
Host OS |
Docker Version |
Host Architecture |
Min Mem |
|---|---|---|---|
Ubuntu 16.04 or later |
Docker CE |
x86_64 |
64 GB |
RHEL or CentOS 7.4 or later |
Docker CE |
x86_64 |
64 GB |
NVIDIA DGX Registry |
x86_64 |
Note: CUDA 11.8.0 or later with NVIDIA drivers >= 471.68 is recommended (GPU only). Note that if you are using K80 GPUs, the minimum required NVIDIA driver version is 450.80.02.
For the best performance, including GPU support, use nvidia-docker. For a lower-performance experience without GPUs, use regular docker (with the same docker image).
These 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://h2o.ai/o/try-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.
Note that from version 1.10 DAI docker image runs with internal tini that is equivalent to using --init from docker, if both are enabled in the launch command, tini prints a (harmless) warning message. For GPU users, as GPU needs --pid=host for nvml, which makes tini not use pid=1, so it will show the warning message (still harmless).
We recommend --shm-size=2g --cap-add=SYS_NICE --ulimit nofile=131071:131071 --ulimit nproc=16384:16384 in docker launch command. But if user plans to build image auto model extensively, then --shm-size=4g is recommended for Driverless AI docker command.
Linux Docker Images