update gpu section in README

Author: johnstcn

README.md

@@ -93,11 +93,59 @@ When passing through GPUs to the inner container, you may end up using associate
 
 Envbox will detect these mounts and pass them inside the inner container it creates, so that GPU-aware tools run inside the inner container can still utilize these libraries.
 
+Here's an example Docker command to run a GPU-enabled workload in Envbox. Note the following:
+
+1) The NVidia container runtime must be installed on the host (`--runtime=nvidia`).
+2) `CODER_ADD_GPU=true` must be set to enable GPU-specific functionality.
+3) When `CODER_ADD_GPU` is set, it is required to also set `CODER_USR_LIB_DIR` to a location where the relvant host directory has been mounted inside the outer container. In the below example, this is `/usr/lib/x86_64-linux-gnu` on the underlying host. It is mounted into the container under the path `/var/coder/usr/lib`. We then set `CODER_USR_LIB_DIR=/var/coder/usr/lib`. The actual location inside the container is not important **as long as it does not overwrite any pre-existing directories containing system libraries**.
+
+   > Note: this step is required in case user workloads require libraries from the underlying host that are not added in by the container runtime.
+
+```shell
+docker run -it --rm \
+  --runtime=nvidia \
+  --gpus=all \
+  --name=envbox-gpu-test \
+  -v /tmp/envbox/docker:/var/lib/coder/docker \
+  -v /tmp/envbox/containers:/var/lib/coder/containers \
+  -v /tmp/envbox/sysbox:/var/lib/sysbox \
+  -v /tmp/envbox/docker:/var/lib/docker \
+  -v /usr/src:/usr/src:ro \
+  -v /lib/modules:/lib/modules:ro \
+  -v /usr/lib/x86_64-linux-gnu:/var/coder/usr/lib \
+  --privileged \
+  -e CODER_INNER_IMAGE=nvcr.io/nvidia/k8s/cuda-sample:vectoradd-cuda10.2 \
+  -e CODER_INNER_USERNAME=root \
+  -e CODER_ADD_GPU=true \
+  -e CODER_USR_LIB_DIR=/var/coder/usr/lib \
+  envbox:latest /envbox docker
+```
+
+To validate GPU functionality, you can run the following commands:
+
+1) To validate that the container runtime correctly passed the required GPU tools into the outer container, run:
+
+   ```shell
+   docker exec -it envbox-gpu-test nvidia-smi
+   ```
+
+2) To validate the same inside the inner container, run:
+
+   ```shell
+   docker exec -it envbox-gpu-test docker exec -it workspace_cvm nvidia-smi
+   ```
+
+3) To validate that the sample CUDA application inside the container runs correctly:
+
+   ```shell
+   docker exec -it envbox-gpu-test docker exec -it workspace_cvm /tmp/vectorAdd
+   ```
+
 ## Hacking
 
 Here's a simple one-liner to run the `codercom/enterprise-minimal:ubuntu` image in Envbox using Docker:
 
-```
+```shell
 docker run -it --rm \
   -v /tmp/envbox/docker:/var/lib/coder/docker \
   -v /tmp/envbox/containers:/var/lib/coder/containers \