Notebook access, GPU status, and update controls in one place
DGX Dashboard is a web application that runs locally on your hardware platform. It provides a graphical interface for system updates, resource monitoring, and an integrated JupyterLab environment. You can open it from the desktop app launcher or reach it remotely through NVIDIA Sync or an SSH tunnel. When you work remotely, the dashboard is the easiest way to apply system package and firmware updates.
You'll access DGX Dashboard on your hardware platform, launch a JupyterLab instance with a pre-configured Python environment, monitor GPU utilization, manage system updates, and run a sample AI workload.
Required:
Optional:
Use the matrix below to confirm your hardware platform, recommended default local settings, and whether multi-node applies.
| Hardware platform | OS | Memory | Recommended default local settings | Multi-node capable hardware |
|---|---|---|---|---|
| DGX Spark | DGX OS (Linux) | 128 GB Unified Memory | DGX Dashboard at http://localhost:11000; JupyterLab via dashboard | — |
Hardware requirements
Software requirements
11000 (local or tunneled)All required assets can be found in the playbook repository.
assets/jupyter-cell.py — Sample Stable Diffusion XL notebook cell for verifying GPU-backed generation in JupyterLab