Testing GPU setup
Before you create a CDE Data Service, as a Kubernetes administrator, you must ensure that GPUs are advertised by running the sample POD as below.
$ cat <<EOF | kubectl apply -f - apiVersion: v1 kind: Pod metadata: name: gpu-pod spec: restartPolicy: Never containers: - name: cuda-container image: nvcr.io/nvidia/k8s/cuda-sample:vectoradd-cuda10.2 resources: limits: nvidia.com/gpu: 1 # requesting 1 GPU EOF
If you get an output similar to the following, it means that the GPU resources are ready for scheduling.
// Log Output $ kubectl logs gpu-pod [Vector addition of 50000 elements] Copy input data from the host memory to the CUDA device CUDA kernel launch with 196 blocks of 256 threads Copy output data from the CUDA device to the host memory Test PASSED Done