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Advanced virtual server with rapid scalability
Access to an all-inclusive stack for AI development, driven by NVIDIA’s powerful technology!
Enhance application capacity and availability.
Backup and restore data instantly, securely and maintain data integrity.
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Secure, unlimited storage to ensures efficiency as well as high and continuous data access demand.
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How to connect Notebook to a new/existing Kernel?
How to connect Notebook to a new/existing Kernel?
Step 1: Open the Kernel Configuration Menu
In the Notebook IDE, open the kernel configuration menu (top right).
| Option | Description | When to Use |
|---|---|---|
| Running Kernels | Connect to an existing active kernel (e.g., Python 3). | Resume work quickly, save resources |
| Start Other Kernels | Launch a new kernel with chosen GPU resources (1x, 2x, 4x, 8x H100). | New experiments or heavy workloads |
| No Kernel | Open the notebook without attaching any compute. | View or edit code without running |
Step 2a: Start a New Kernel
- Under Start Other Kernels, select the GPU type you want.
- Click Confirm and approve the confirmation pop-up.
- Wait about 1–2 minutes for the notebook to be ready.
- Once connected, the new kernel will appear under Running Kernels.
Step 2b: Switch to an Existing Kernel
- Under Running Kernels, select the kernel you want to connect to.
- Wait about 1–2 minutes for the notebook to be ready.
- Once connected, the selected kernel will be shown under Running Kernels.
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