k8s调用GPU

冷不防 2024-04-18 10:55 68阅读 0赞

##### 创建可调用GPU的pod #####

apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: gpu-master
      namespace: gpu
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: gpu-master
      template:
        metadata:
          labels:
            app: gpu-master
        spec:
          hostname: gpu-master
          containers:
          - name: gpu-master
            image: 192.168.168.10:5000/library/pytorch-gpu:v3
            env:
            - name: NVIDIA_DRIVER_CAPABILITIES
              value: compute,utility
            - name: NVIDIA_VISIBLE_DEVICES
              value: all
            securityContext:
              privileged: true
              runAsUser: 0
            resources:
               limits:
                 nvidia.com/gpu: "1"
               requests:
                 nvidia.com/gpu: "1"
            volumeMounts:
            - name: code-host-path
              mountPath: /persistent
          volumes:
          - name: code-host-path
            hostPath:
               path: /root/gpu/gpucode

##### 创建可调用GPU的job #####

apiVersion: batch/v1
    kind: Job
    metadata:
      labels:
        app-name: gpu-job
        job-name: gpu-job
      name: gpu-job
      namespace: gpu
    spec:
      backoffLimit: 6
      parallelism: 1
      template:
        metadata:
          labels:
            app-name: gpu-job
            job-name: gpu-job
          name: gpu-job
        spec:
          containers:
          - command:
            - /bin/bash
            - -c
            - '/usr/local/anaconda2/envs/edu_pytorch/bin/python3.6 /persistent/test.py '
            image: 192.168.168.10:5000/library/pytorch-gpu:v3
            env:
            - name: NVIDIA_DRIVER_CAPABILITIES
              value: compute,utility
            - name: NVIDIA_VISIBLE_DEVICES
              value: all
            imagePullPolicy: IfNotPresent
            name: gpu-job
            resources:
              limits:
                nvidia.com/gpu: "1"
              requests:
                nvidia.com/gpu: "1"
            securityContext:
              privileged: true
              procMount: Default
            volumeMounts:
            - name: code-host-path
              mountPath: /persistent
          dnsPolicy: ClusterFirst
          hostname: gpu-job
          restartPolicy: OnFailure
          schedulerName: default-scheduler
          securityContext: {}
          volumes:
          - name: code-host-path
            hostPath:
               path: /root/gpu/gpucode