Skip to content
Closed
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
21 changes: 21 additions & 0 deletions get-started.mdx
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,24 @@ import { PodTooltip, NetworkVolumeTooltip, TemplateTooltip, PyTorchTooltip } fro

Follow this guide to learn how to create an account, deploy your first GPU <PodTooltip />, and use it to execute code remotely.

## Run GPU code with Flash
Copy link
Copy Markdown
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Citation: Mo King requested adding a simple Flash code sample to the top-level docs homepage. Code sample adapted from the Flash overview example.
View source


If you want the fastest path to running GPU code on Runpod, use [Flash](/flash/overview). Flash lets you run Python functions on remote GPUs with a single decorator:

```python
import asyncio
from runpod_flash import Endpoint, GpuType

@Endpoint(name="hello-gpu", gpu=GpuType.NVIDIA_GEFORCE_RTX_4090)
def hello():
import torch
return {"gpu": torch.cuda.get_device_name(0)}

asyncio.run(hello())
```

Install Flash with `pip install runpod-flash`, authenticate with `flash login`, and you're ready to go. See the [Flash quickstart](/flash/quickstart) for complete setup instructions.

## Step 1: Create an account

Start by creating a Runpod account:
Expand Down Expand Up @@ -189,6 +207,9 @@ runpodctl pod delete $RUNPOD_POD_ID
<Card title="Runpod Serverless" href="/serverless/overview" icon="cloud" horizontal>
Start building production-ready applications.
</Card>
<Card title="Flash SDK" href="/flash/overview" icon="bolt" horizontal>
Run GPU functions with Python decorators.
</Card>
</CardGroup>

## Need help?
Expand Down
Loading