Docker compose has nice support for GPUs, K8s has moved their cluster-wide GPU scheduler from experimental to stable status. Docker swarm has yet to support the device
option used in docker compose
so the mechanisms for supporting GPUs on swarm are a bit more open-ended.
- NVIDIA container runtime for docker. The runtime is no longer required to run GPU support with the docker cli or compose; however, it appears necessary so that one can set
Default Runtime: nvidia
for swarm mode. - docker compose GPU support
- Good GitHub Gist Reference for an overview on Swarm with GPUs. It is a bit dated, but has good links and conversation.
- Miscellaneous Options for docker configuration. Go down to "Node Generic Resources" for an explanation of how this is intended to support NVIDIA GPUs. The main idea is one has to change the
/etc/docker/daemon.json
file to advertise thenode-generic-resources
(NVIDIA GPUs) on each node. GPUs have to be added by hand the thedaemon.json
file, swarm does not detect and advertise them automatically. - How to create a service with generic resources. This shows how to create stacks/services requesting the generic resources advertised in the
/etc/docker/daemon.json
file. - Quick blog overview confirming these basic approaches.
- Really good overview on Generic Resources in swarm.
See a comprehensive writeup here.
Both solutions need to follow these steps first:
- Install
nvidia-container-runtime
. Follow the steps here. Takes <5 minutes. - Update
/etc/docker/daemon.json
to usenvidia
as the default runtime. Then restart the docker daemon on each nodesudo service docker restart
. Confirm the default runtime isnvidia
withdocker info
.
{
"default-runtime": "nvidia",
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
}
}
}
You're done. When you deploy a service to a node, it will by default see all the GPUs on that node. Generally this means you are deploying global services (one per node) or assigning services to specific nodes so that there aren't accidental collisions between services accessing the same GPU resources.
If you want to expose only certain GPUs to a given service (e.g., multiple services on one node with each having access only to its own GPU(s)) use the NVIDIA_VISIBLE_DEVICES
environment variable for each service. See bigchem/docker/docker-compose.terachem.xstream.yaml for an example of how to do this dynamically so that each services gets access to its own GPU using docker service templates. Because {{.Task.Slot}}
starts counting at 1
, the global
service is also included in the template to make use of GPU 0
.
Advertise NVIDA GPUs using Node Generic Resources. This is the most general purpose approach and will enable services to simply declare the required GPU resources and swarm will schedule them accordingly.
The /etc/docker/daemon.json
file on each node needs to be updated to advertise its GPU resources. You can find the UUID for each GPU by running nvidia-smi -a | grep UUID
. You only need to include GPU
plus the first 8 digits of the UUID, it seems, i.e., GPU-be74calf3
for the UUID. The following needs to be added to the daemon.json
file already declaring nvidia
as the default runtime.
{
"node-generic-resources": [
"NVIDIA-GPU=GPU-be74calf3",
"NVIDIA-GPU=GPU-dl23cdb4"
]
}
Enable GPU resource advertising by uncommenting the swarm-resource = "DOCKER_RESOURCE_GPU"
line (line 2) in /etc/nvidia-container-runtime/config.toml
.
The docker daemon must be restarted after updating these files by running sudo service docker restart
on each node. Services can now request GPUs using the generic-resource flag.
docker service create \
--name cuda \
--generic-resource "NVIDIA-GPU=2" \
--generic-resource "SSD=1" \
nvidia/cuda
The names for node-generic-resources
in /etc/docker/daemon.json
could be anything you want. So if you want to declare NVIDIA-H100
and NVIDIA-4090
you could and then request specific GPU types with --generic-resource "NVIDIA-H100"
.
To request GPU resources in a docker-compose.yaml
file for the stack use the following under the deploy
key.
services:
my-gpu-service:
...
deploy:
resources:
reservations:
generic_resources:
- discrete_resource_spec:
kind: "NVIDIA-GPU"
value: 2
- Add support for devices with "service create". Opened July 2016
- Proposal: Device Support. Opened July 2018
- Add support for devices in swarm. PR opened December 2022. Addresses the two issues above.