2.4 KiB
Docker
Prequisites
Docker containers share the kernel with the host operating system, therefore the ROCm kernel-mode driver must be installed on the host. Please refer to the Basic Installation Guide for details. The other user-space parts (like the HIP-runtime or math libraries) of the ROCm stack will be loaded from the container image and don't need to be installed to the host.
Accessing GPUs in containers
In order to access GPUs in a container (to run applications using HIP, OpenCL or OpenMP offloading) explicit access to the GPUs must be granted.
The ROCm runtimes make use of multiple device files:
/dev/kfd: the main compute interface shared by all GPUs/dev/dri/renderD<node>: direct rendering interface (DRI) devices for each GPU.<node>is a number for each card in the system starting from 128.
Exposing these devices to a container is done by using the
--device
option, i.e. to allow access to all GPUs expose /dev/kfd and all
/dev/dri/renderD devices:
docker run --device /dev/kfd --device /dev/renderD128 --device /dev/renderD129 ...
More conveniently, instead of listing all devices, the entire /dev/dri folder
can be exposed to the new container:
docker run --device /dev/kfd --device /dev/dri
Note that this gives more access than strictly required, as it also exposes the other device files found in that folder to the container.
Restricting a container to a subset of the GPUs
If a /dev/dri/renderD device is not exposed to a container then it cannot use
the GPU associated with it; this allows to restrict a container to any subset of
devices.
For example to allow the container to access the first and third GPU start it like:
docker run --device /dev/kfd --device /dev/dri/renderD128 --device /dev/dri/renderD130 <image>
Docker images in the ROCm ecosystem
Base images
https://github.com/RadeonOpenCompute/ROCm-docker hosts images useful for users
wishing to build their own containers levaraging ROCm. The built images are
available from Docker Hub. In particular
rocm/rocm-terminal is a small image with the prequisites to build HIP
applications, but does not include any libraries.
Applications
AMD provides pre-built images for various GPU-ready applications through its Infinity Hub at https://www.amd.com/en/technologies/infinity-hub.