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Installation guide

0. Prepare GPU Node

This guide assumes that the NVIDIA drivers and nvidia-docker2 have been installed.

Enable the Nvidia runtime as your default runtime on your node. To do this, please edit the docker daemon config file which is usually present at /etc/docker/daemon.json:

{
    "default-runtime": "nvidia",
    "runtimes": {
        "nvidia": {
            "path": "/usr/bin/nvidia-container-runtime",
            "runtimeArgs": []
        }
    }
}

if runtimes is not already present, head to the install page of nvidia-docker

1. Deploy GPU share scheduler extender

cd /etc/kubernetes/
curl -O https://raw.githubusercontent.com/AliyunContainerService/gpushare-scheduler-extender/master/config/scheduler-policy-config.json
cd /tmp/
curl -O https://raw.githubusercontent.com/AliyunContainerService/gpushare-scheduler-extender/master/config/gpushare-schd-extender.yaml
kubectl create -f gpushare-schd-extender.yaml

2. Modify scheduler configuration

The goal is to include /etc/kubernetes/scheduler-policy-config.json into the scheduler configuration. Here is the sample of the modified kube-scheduler.yaml

2.1 Add Policy config file parameter in scheduler arguments

- --policy-config-file=/etc/kubernetes/scheduler-policy-config.json

2.2 Add volume mount into Pod Spec

- mountPath: /etc/kubernetes/scheduler-policy-config.json
  name: scheduler-policy-config
  readOnly: true
- hostPath:
      path: /etc/kubernetes/scheduler-policy-config.json
      type: FileOrCreate
  name: scheduler-policy-config

Notice: If your Kubernetes default scheduler is deployed as static pod, don't edit the yaml file inside /etc/kubernetes/manifest. You need to edit the yaml file outside the /etc/kubernetes/manifest directory. and copy the yaml file you edited to the '/etc/kubernetes/manifest/' directory, and then kubernetes will update the default static pod with the yaml file automatically.

3. Deploy Device Plugin

wget https://raw.githubusercontent.com/AliyunContainerService/gpushare-device-plugin/master/device-plugin-rbac.yaml
kubectl create -f device-plugin-rbac.yaml
wget https://raw.githubusercontent.com/AliyunContainerService/gpushare-device-plugin/master/device-plugin-ds.yaml
kubectl create -f device-plugin-ds.yaml

Notice: please remove default GPU device plugin, for example, if you are using nvidia-device-plugin, you can run kubectl delete ds -n kube-system nvidia-device-plugin-daemonset to delete.

4. Add gpushare node labels to the nodes requiring GPU sharing

You need to add a label "gpushare=true" to all node where you want to install device plugin because the device plugin is deamonset.

kubectl label node <target_node> gpushare=true

For example:

kubectl label no mynode gpushare=true

5. Install Kubectl extension

5.1 Install kubectl 1.12 or above

You can download and install kubectl for linux

curl -LO https://storage.googleapis.com/kubernetes-release/release/v1.12.1/bin/linux/amd64/kubectl
chmod +x ./kubectl
sudo mv ./kubectl /usr/bin/kubectl

5.2 Download and install the kubectl extension

cd /usr/bin/
wget https://github.com/AliyunContainerService/gpushare-device-plugin/releases/download/v0.3.0/kubectl-inspect-gpushare
chmod u+x /usr/bin/kubectl-inspect-gpushare