mirror of https://github.com/kubernetes/kops.git
52 lines
1.6 KiB
Markdown
52 lines
1.6 KiB
Markdown
# GPU Support
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## kOps managed device driver
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{{ kops_feature_table(kops_added_default='1.22') }}
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kOps can install nvidia device drivers, plugin, and runtime, as well as configure containerd to make use of the runtime.
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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.
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kOps will add `kops.k8s.io/gpu="1"` as node selector as well as the following taint:
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```yaml
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taints:
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- effect: NoSchedule
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key: nvidia.com/gpu
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```
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The taint will prevent you from accidentially scheduling workloads on GPU Nodes.
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You can enable nvidia by adding the following to your Cluster spec:
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```yaml
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containerd:
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nvidiaGPU:
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enabled: true
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```
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## Creating an instance group with GPU nodeN
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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](https://kops.sigs.k8s.io/getting_started/aws/).
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Once the cluster is running, add an instance group with GPUs:
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```yaml
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apiVersion: kops.k8s.io/v1alpha2
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kind: InstanceGroup
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metadata:
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labels:
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kops.k8s.io/cluster: <cluster name>
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name: gpu-nodes
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spec:
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image: 099720109477/ubuntu/images/hvm-ssd/ubuntu-focal-20.04-amd64-server-20200907
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nodeLabels:
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kops.k8s.io/instancegroup: gpu-nodes
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machineType: g4dn.xlarge
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maxSize: 1
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minSize: 1
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role: Node
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subnets:
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- eu-central-1c
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``` |