分配多个独占 BI-V150 设备

要分配多个 BI-V150 设备，你只需分配 iluvatar.ai/BI-V150-vgpu ，无需其他字段。

apiVersion: v1
kind: Pod
metadata:
  name: BI-V150-poddemo
spec:
  restartPolicy: Never
  containers:
  - name: BI-V150-poddemo
    image: registry.iluvatar.com.cn:10443/saas/mr-bi150-4.3.0-x86-ubuntu22.04-py3.10-base-base:v1.0
    command:
    - bash
    args:
    - -c
    - |
      set -ex
      echo "export LD_LIBRARY_PATH=/usr/local/corex/lib64:$LD_LIBRARY_PATH">> /root/.bashrc
      cp -f /usr/local/iluvatar/lib64/libcuda.* /usr/local/corex/lib64/
      cp -f /usr/local/iluvatar/lib64/libixml.* /usr/local/corex/lib64/
      source /root/.bashrc
      sleep 360000
    resources:
      requests:
        iluvatar.ai/BI-V150-vgpu: 2
      limits:
        iluvatar.ai/BI-V150-vgpu: 2

备注

当申请独占一张 GPU（iluvatar.ai/<card-type>-vgpu=1）时，需要同时设置 iluvatar.ai/<card-type>.vCore 和 iluvatar.ai/<card-type>.vMem 的值为 GPU 的最大资源数量。iluvatar.ai/<card-type>-vgpu>1 时不再支持 vGPU 功能，可不必填写核心和显存的数值