下载镜像

docker pull nvidia/k8s-device-plugin:v0.9.0

docker tag nvidia/k8s-device-plugin:v0.9.0 10.0.7.125:8000/library/k8s-device-plugin:v0.9.0

docker push 10.0.7.125:8000/library/k8s-device-plugin:v0.9.0

下载并安装驱动

驱动：https://www.nvidia.cn/Download/index.aspx?lang=cn

CUDA：https://developer.nvidia.com/cuda-toolkit-archive

安装nvidia-docker

apt download libnvidia-container1
 
apt download libnvidia-container-tools
 
apt download nvidia-container-toolkit
 
apt download nvidia-container-runtime
 
apt download nvidia-docker2

修改/etc/docker/daemon.json文件配置如下

sudo vim /etc/docker/daemon.json

{
  ...
  "default-runtime": "nvidia",
  "runtimes": {
    "nvidia": {
      "path": "nvidia-container-runtime",
      "runtimeArgs": []
    }
  }
  ...
}

重启docker

sudo systemctl daemon-reload

sudo systemctl restart docker

部署

# Copyright (c) 2019, NVIDIA CORPORATION.  All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: nvidia-device-plugin-daemonset
spec:
  selector:
    matchLabels:
      name: nvidia-device-plugin-ds
  updateStrategy:
    type: RollingUpdate
  template:
    metadata:
      # This annotation is deprecated. Kept here for backward compatibility
      # See https://kubernetes.io/docs/tasks/administer-cluster/guaranteed-scheduling-critical-addon-pods/
      annotations:
        scheduler.alpha.kubernetes.io/critical-pod: ""
      labels:
        name: nvidia-device-plugin-ds
    spec:
      tolerations:
      # This toleration is deprecated. Kept here for backward compatibility
      # See https://kubernetes.io/docs/tasks/administer-cluster/guaranteed-scheduling-critical-addon-pods/
      - key: CriticalAddonsOnly
        operator: Exists
      - key: nvidia.com/gpu
        operator: Exists
        effect: NoSchedule
      # Mark this pod as a critical add-on; when enabled, the critical add-on
      # scheduler reserves resources for critical add-on pods so that they can
      # be rescheduled after a failure.
      # See https://kubernetes.io/docs/tasks/administer-cluster/guaranteed-scheduling-critical-addon-pods/
      priorityClassName: "system-node-critical"
      containers:
      - image: 10.0.7.125:8000/library/nvidia/k8s-device-plugin:v0.9.0
        name: nvidia-device-plugin-ctr
        args: ["--fail-on-init-error=false"]
        securityContext:
          allowPrivilegeEscalation: false
          capabilities:
            drop: ["ALL"]
        volumeMounts:
          - name: device-plugin
            mountPath: /var/lib/kubelet/device-plugins
      volumes:
        - name: device-plugin
          hostPath:
            path: /var/lib/kubelet/device-plugins

测试

kubectl describe node node1|grep nvidia.com/gpu


#  nvidia.com/gpu:     1
#  nvidia.com/gpu:     1
#  nvidia.com/gpu     0          0

有输出结果有则说明部署成功