GPU Support ¶
kOps managed device driver ¶
Introduced |
---|
kOps 1.22 |
kOps can install nvidia device drivers, plugin, and runtime, as well as configure containerd to make use of the runtime.
kOps will also install a RuntimeClass nvidia
. As the nvidia runtime is not the default runtime, you will need to add runtimeClassName: nvidia
to any Pod spec you want to use for GPU workloads. The RuntimeClass also configures the appropriate node selectors and tolerations to run on GPU Nodes.
kOps will add kops.k8s.io/gpu="1"
as node selector as well as the following taint:
taints:
- effect: NoSchedule
key: nvidia.com/gpu
The taint will prevent you from accidentially scheduling workloads on GPU Nodes.
You can enable nvidia by adding the following to your Cluster spec:
containerd:
nvidiaGPU:
enabled: true
Creating an instance group with GPU nodeN ¶
Due to the cost of GPU instances you want to minimize the amount of pods running on them. Therefore start by provisioning a regular cluster following the getting started documentation.
Once the cluster is running, add an instance group with GPUs:
apiVersion: kops.k8s.io/v1alpha2
kind: InstanceGroup
metadata:
labels:
kops.k8s.io/cluster: <cluster name>
name: gpu-nodes
spec:
image: 099720109477/ubuntu/images/hvm-ssd/ubuntu-focal-20.04-amd64-server-20200907
nodeLabels:
kops.k8s.io/instancegroup: gpu-nodes
machineType: g4dn.xlarge
maxSize: 1
minSize: 1
role: Node
subnets:
- eu-central-1c
GPUs in OpenStack ¶
OpenStack does not support enabling containerd configuration in cluster level. It needs to be done in instance group:
apiVersion: kops.k8s.io/v1alpha2
kind: InstanceGroup
metadata:
labels:
kops.k8s.io/cluster: <cluster name>
name: gpu-nodes
spec:
image: 099720109477/ubuntu/images/hvm-ssd/ubuntu-focal-20.04-amd64-server-20200907
nodeLabels:
kops.k8s.io/instancegroup: gpu-nodes
machineType: g4dn.xlarge
maxSize: 1
minSize: 1
role: Node
subnets:
- eu-central-1c
containerd:
nvidiaGPU:
enabled: true
Verifying GPUs ¶
- after new GPU nodes are coming up, you should see them in
kubectl get nodes
- nodes should have
kops.k8s.io/gpu
label andnvidia.com/gpu:NoSchedule
taint kube-system
namespace should have nvidia-device-plugin-daemonset pod provisioned to GPU node(s)- if you see
nvidia.com/gpu
in kubectl describe nodeeverything should work.
Capacity:
cpu: 4
ephemeral-storage: 9983232Ki
hugepages-1Gi: 0
hugepages-2Mi: 0
memory: 32796292Ki
nvidia.com/gpu: 1 <- this one
pods: 110