> For the complete documentation index, see [llms.txt](https://docs.cloudeka.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.cloudeka.ai/reference/how-to-use-gpu-h100-with-rdma-in-kubernetes/implementation.md).

# Implementation

## Step 1: Prepare the YAML manifest

```yaml
apiVersion: v1
kind: Pod
metadata:
  name: h100-rdma-test
  namespace: default
spec:
  runtimeClassName: nvidia
  nodeSelector:
    nvidia.com/gpu.product: NVIDIA-H100-80GB-HBM3
  securityContext:
    runAsNonRoot: true
    runAsUser: 1000
  containers:
    - name: cuda
      image: nvidia/cuda:12.4.1-base-ubuntu22.04
      command: ["sh", "-c", "nvidia-smi && sleep 3600"]
      securityContext:
        allowPrivilegeEscalation: false
        runAsNonRoot: true
        runAsUser: 1000
      resources:
        requests:
          nvidia.com/gpu: 1
          rdma/ib_shared_device: 1
        limits:
          nvidia.com/gpu: 1
          rdma/ib_shared_device: 1
```

## Step 2: Deploy the Pod

Use `kubectl` to apply the manifest with the following command:

```bash
kubectl apply -f h100-rdma-test.yaml
```

You will see the following output:

```bash
pod/h100-rdma-test created
```

## Step 3: Monitor the deployment

Check the Pod status.

```yaml
kubectl get pods
```

The output should look like this.

```bash
NAME               READY   STATUS              RESTARTS   AGE
h100-rdma-test    0/1     ContainerCreating   0          5s
```

{% hint style="info" %}
Wait until the status changes to `Running`. If the status shows `Pending`, there is a scheduling issue.
{% endhint %}

## Step 4: Verify GPU access

After the Pod is running, check the `nvidia-smi` logs with the following command.

```yaml
kubectl logs h100-rdma-test
```

The output should look like this, which confirms that the GPU is detected and mounted in the container.

```bash
Thu Jul  9 12:02:07 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 580.95.05              Driver Version: 580.95.05      CUDA Version: 13.0     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA H100 80GB HBM3          On  |   00000000:66:00.0 Off |                    0 |
| N/A   32C    P0             71W /  700W |       0MiB /  81559MiB |      0%      Default |
|                                         |                        |             Disabled |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+
```