Renting a GPU on SimplePod
Here you can learn how to set up a cloud-based GPU environment. Setting up a cloud GPU with SimplePod is quick and user-friendly. By following these steps, you can efficiently rent a GPU, monitor its performance and manage your billing.
Choose Your GPU Rental Option:
Access the 'Find Instances' Tab
Start by selecting one of the available GPU rental options. SimplePod offers a variety of cloud based GPU solutions to match your project needs.
Pick the Right Template
From the list of global templates, choose the one that fits your current requirements. Your private templates are shown at the top, while all global templates available for GPU rental are listed below.
Configure Your Instance:
Enter Image Details
Type in the image name from the Docker Repository and select the proper image tag. Then click the 'Use and Save to My Template' button. With each GPU rent session, you can set different configurations tailored to your needs.
Launch Your Instance
Click the 'Run' button to create your instance. As your cloud GPU is being set up, you can monitor its progress and see usage details in the 'My Instances' tab.
Monitor and Manage Your Cloud GPU:
Check Server Status
In the 'My Instances' tab, you can view real-time server usage, system information, and current billing status. The top of the interface shows your saved private templates, with global templates listed below.
Manage Billing and Payments
Switch to the 'Billing' tab to review your account balance and available payment methods. Here you can:
- Enable or disable the auto deposit feature
- Add new payment methods
- Review your instance usage and deposit history
This setup makes managing your GPU cloud both simple and efficient.
Launch and Work on Your Project:
Open the Console
Once the installation is complete, you can launch the console to check metrics like disk usage. This is a key part of managing your cloud GPU effectively.
Start Jupyter and Begin Your Project
After confirming everything is set up, launch Jupyter to kick off your new project. When your work is finished, you can delete your instance to optimize costs for future GPU rent needs.