How to use GPUs

If you need a GPU, you can request one by adding a resource limit for a number of nvidia.com/gpu, for example 1 (this is constrained by the number of GPUs available, and your quotas).

apiVersion: v1
kind: Pod
metadata:
  name: gpu-test
spec:
  containers:
    - name: cuda-container
      image: nvcr.io/nvidia/cuda:9.0-devel
      resources:
        limits:
          nvidia.com/gpu: 1 # Request 1 NVIDIA GPU

If you are using a Job, put the resource limit in the pod template:

apiVersion: batch/v1
kind: Job
metadata:
  name: gpu-test
spec:
  template:
    spec:
      restartPolicy: Never
      containers:
        - name: cuda-container
          image: nvcr.io/nvidia/cuda:9.0-devel
          resources:
            limits:
              nvidia.com/gpu: 1 # Request 1 NVIDIA GPU

List of available GPUs

• hsrn-ed7a-370j
  • NVIDIA A100 (40GB)
  • NVIDIA A100 (40GB)
• hsrn-edbse-12wvpl
  • NVIDIA Quadro RTX 8000 (48 GB)
• hsrn-ed2a-60fifthave
  • NVIDIA Quadro RTX 8000 (48 GB)
• hsrn-ed2n-rcdc
  • NVIDIA Quadro RTX 8000 (48 GB)
  • NVIDIA Quadro RTX 8000 (48 GB)
• hsrn-ed10d-7e12
  • NVIDIA A100 (80GB)
  • NVIDIA A100 (80GB)
• hsrn-ed2d-wwh
  • NVIDIA A100 (40GB)
  • NVIDIA A100 (40GB)
• hsrn-ed5a-meyer
  • NVIDIA A100 (80GB)
  • NVIDIA A100 (80GB)
• vida-c04-13, vida-c15-24
• vida-c04, vida-c05, vida-c06, vida-c07, vida-c08, vida-c09, vida-c10, vida-c11, vida-c12, vida-c13, vida-c15, vida-c16, vida-c17, vida-c18, vida-c19, vida-c20, vida-c21, vida-c22, vida-c23, vida-c24
  • 4x NVIDIA Tesla P100 (12GB)
• vida-c01, vida-c02, vida-c03, vida-c14, vida-c25
  • 4x NVIDIA Tesla P40 (24GB)