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    onboarding

    • Set Up Local Network Access
    • Open WebUI with Ollama

    data science

    • Single-cell RNA Sequencing
    • Portfolio Optimization
    • CUDA-X Data Science
    • Build Knowledge Graphs with txt2kg
    • Optimized JAX

    tools

    • DGX Dashboard
    • RAG Application in AI Workbench
    • Set up Tailscale on Your Spark
    • VS Code
    • Connect Three DGX Spark in a Ring Topology
    • Connect Multiple DGX Spark through a Switch

    fine tuning

    • FLUX.1 Dreambooth LoRA Fine-tuning
    • LLaMA Factory
    • Fine-tune with NeMo
    • Fine-tune with Pytorch
    • Unsloth on DGX Spark

    use case

    • Run Hermes Agent with a Local LLM
    • cuTile Kernels
    • CLI Coding Agent
    • Run NemoClaw with a Local LLM
    • 🦞 Set Up Example NemoClaw Agents 🦞
    • Live VLM WebUI
    • Install and Use Isaac Sim and Isaac Lab
    • Vibe Coding in VS Code
    • Build and Deploy a Multi-Agent Chatbot
    • Connect Two Sparks
    • NCCL for Multiple Sparks
    • Build a Video Search and Summarization (VSS) Agent
    • Spark & Reachy Photo Booth
    • Secure AI Agents with OpenShell
    • Run OpenClaw with a Local LLM

    inference

    • Generate Images and Videos with ComfyUI
    • Serve LLMs with vLLM
    • Speculative Decoding
    • Run models with llama.cpp on DGX Spark
    • Nemotron Model Family on DGX Spark
    • Serve LLMs with SGLang
    • TRT LLM for Inference
    • Quantize Models to NVFP4 with NVIDIA Model Optimizer
    • Multi-modal Inference
    • NIM on Spark
    • LM Studio on DGX Spark

    VS Code

    5 MIN

    Install and use VS Code locally or remotely

    • DGX
    • Spark
    OverviewOverviewDesktop UseDesktop UseRemote UseRemote UseTroubleshootingTroubleshooting

    Step 1
    Download VS Code ARM64 installer to your DGX Spark

    Go to the VS Code download page and download the appropriate ARM64 .deb package for your system.

    Alternatively, download the installer with this command:

    wget https://code.visualstudio.com/sha/download?build=stable\&os=linux-deb-arm64 -O vscode-arm64.deb
    

    Step 2
    Install VS Code

    Install the downloaded package using the system package manager.

    You can click on the installer file directly or use the command line.

    # Install the downloaded .deb package
    sudo dpkg -i vscode-arm64.deb
    
    # Fix any dependency issues if they occur
    sudo apt-get install -f
    

    Step 3
    Open VS Code

    You can open the app directly from the list of applications or from the command line.

    # Test launch (will open VS Code GUI)
    code &
    

    VS Code should launch and display the welcome screen.

    Step 4
    Configure for Spark development

    Set up VS Code for development on the DGX Spark platform.

    # Launch VS Code if not already running
    code
    
    # Or create a new project directory and open it
    mkdir ~/spark-dev-workspace
    cd ~/spark-dev-workspace
    code .
    

    From within VS Code:

    • Open File > Preferences > Settings
    • Search for "terminal integrated shell" to configure default terminal
    • Install recommended extensions via Extensions tab (left sidebar)

    Step 5
    Validate setup and test functionality

    Test core VS Code functionality to ensure proper operation on ARM64.

    Create a test file:

    # Create test directory and file
    mkdir ~/vscode-test
    cd ~/vscode-test
    echo 'print("Hello from DGX Spark!")' > test.py
    code test.py
    

    Within VS Code:

    • Verify syntax highlighting works
    • Open integrated terminal (Terminal > New Terminal)
    • Run the test script: python3 test.py
    • Test Git integration by running git init and then git status in the terminal

    Step 6
    Uninstalling VS Code

    WARNING

    Removing the hidden folders will remove all user settings and extensions.

    To remove VS Code if needed:

    # Remove VS Code package
    sudo apt-get remove code
    
    # Remove configuration files (optional)
    rm -rf ~/.config/Code
    rm -rf ~/.vscode
    

    Resources

    • VS Code Documentation
    • DGX Spark Documentation
    • DGX Spark Forum
    • DGX Spark User Performance Guide
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