> 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/testing-and-verification.md).

# Testing and Verification

After the implementation is complete, make sure the GPU is allocated to the Pod by running the following command.

```bash
kubectl exec -it h100-rdma-test -- /bin/bash
```

Once you are inside the container, check the available GPU with the following command.

```bash
nvidia-smi
```

The output should look like this.

```
Mon Dec 19 10:23:45 2024       
+-----------------------------+----------------------+----------------------+
| NVIDIA-SMI 545.23.08        Driver Version: 545.23.08                    |
+==============================================================================+
| GPU  Name                   Persistence-M | Bus-Id        Disp.A | Volatile |
|                            GPU Memory |
|=============================================================================|
|   0  NVIDIA H100 80GB HBM3  Off  | 00:1E.0     Off |              0 |
| 79993MiB / 81920MiB |
+============================================================================+
```

{% hint style="info" %}
If the output shows an H100 GPU with 80 GB of memory, the GPU allocation is successful.
{% endhint %}