tech:linux
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| tech:linux [2026/06/14 23:53] – [Step 4: Manual Driver Override (Optional)] glong | tech:linux [2026/06/15 18:53] (current) – glong | ||
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| Ubunut 24.04 | Ubunut 24.04 | ||
| + | |||
| + | [[: | ||
| ====== Install all drivers needed for using V100 on Ubuntu 24.04 LTS ====== | ====== Install all drivers needed for using V100 on Ubuntu 24.04 LTS ====== | ||
| Line 88: | Line 90: | ||
| ====== GeForce 210 Driver Override Guide ====== | ====== GeForce 210 Driver Override Guide ====== | ||
| - | To configure a Driver Override for your GeForce 210, follow these steps to isolate | + | We cannot fix this the '' |
| - | ===== Step 1: Identify Device IDs ===== | + | |
| - | Use '' | + | |
| - | + | ||
| - | lspci -nn | grep -i " | + | |
| - | Note the hexadecimal IDs (e.g., '' | + | |
| - | + | ||
| - | < | + | |
| - | root@test1: | + | |
| - | 01:00.0 VGA compatible controller [0300]: NVIDIA Corporation GT218 [GeForce 210] [10de:0a65] (rev a2) | + | |
| - | </ | + | |
| - | + | ||
| - | ===== Step 2: Isolate the Card with pci-stub ===== | + | |
| - | Bind the device to '' | + | |
| - | + | ||
| - | * Open your GRUB configuration: | + | |
| - | + | ||
| - | sudo nano / | + | |
| - | * Append '' | + | |
| - | + | ||
| - | GRUB_CMDLINE_LINUX_DEFAULT=" | + | |
| - | * Update GRUB: | + | |
| - | + | ||
| - | < | + | |
| - | root@test1: | + | |
| - | GRUB_CMDLINE_LINUX_DEFAULT=" | + | |
| - | </ | + | |
| - | + | ||
| - | sudo update-grub | + | |
| - | + | ||
| - | ===== Step 3: Ensure nouveau is Loaded ===== | + | |
| - | Ensure | + | |
| - | + | ||
| - | * Remove any '' | + | |
| - | * Add '' | + | |
| - | + | ||
| - | echo “nouveau” | sudo tee -a / | + | |
| - | + | ||
| - | ===== Step 4: Manual Driver Override (Optional) ===== | + | |
| - | If the card does not bind correctly after rebooting, create a manual override script to forcibly unbind any driver and attach '' | + | |
| - | + | ||
| - | < | + | |
| - | # | + | |
| - | ## Unbind from any existing driver | + | |
| - | echo " | + | |
| - | ## Force bind to nouveau | + | |
| - | echo " | + | |
| - | echo " | + | |
| - | </ | + | |
| - | ===== Step 5: Verify Configuration ===== | + | |
| - | Reboot your system and verify the kernel driver in use for each card. | + | |
| - | + | ||
| - | lspci -nnk | grep -A 3 " | + | |
| - | The GeForce 210 should show '' | + | |
| - | ------------------------------ | + | |
| - | Does this DokuWiki format work for your documentation needs, or would you like to add more technical details about the V100 configuration as well? | + | |
| Line 251: | Line 197: | ||
| ===== 2. Install the NVIDIA Container Toolkit ===== | ===== 2. Install the NVIDIA Container Toolkit ===== | ||
| + | https:// | ||
| Add the official package repositories and install the toolkit: | Add the official package repositories and install the toolkit: | ||
| Line 258: | Line 205: | ||
| curl -fsSL https:// | curl -fsSL https:// | ||
| - | curl -s -L https:// | + | curl -fsSL https:// |
| - | sed 's#deb https://# | + | && |
| - | sudo tee / | + | sed 's#deb https://# |
| + | sudo tee / | ||
| + | |||
| + | sudo sed -i -e '/ | ||
| # Update package list and install | # Update package list and install | ||
| sudo apt-get update | sudo apt-get update | ||
| - | sudo apt-get install -y nvidia-container-toolkit | + | |
| + | export NVIDIA_CONTAINER_TOOLKIT_VERSION=1.19.1-1 | ||
| + | | ||
| + | | ||
| + | nvidia-container-toolkit-base=${NVIDIA_CONTAINER_TOOLKIT_VERSION} \ | ||
| + | libnvidia-container-tools=${NVIDIA_CONTAINER_TOOLKIT_VERSION} \ | ||
| + | libnvidia-container1=${NVIDIA_CONTAINER_TOOLKIT_VERSION} | ||
| </ | </ | ||
| Line 284: | Line 241: | ||
| < | < | ||
| - | sudo docker run --rm --gpus all ubuntu nvidia-smi | + | docker run --rm --runtime=nvidia |
| </ | </ | ||
| Line 299: | Line 256: | ||
| If you plan to deploy enterprise-grade AI workloads, you can also authenticate your Docker client to the NVIDIA NGC Container Registry using an API key. This gives you direct access to fine-tuned, GPU-optimized AI models and microservices. | If you plan to deploy enterprise-grade AI workloads, you can also authenticate your Docker client to the NVIDIA NGC Container Registry using an API key. This gives you direct access to fine-tuned, GPU-optimized AI models and microservices. | ||
| + | |||
| + | ====== Installing LM Studio on Ubuntu 24.04 ====== | ||
| + | |||
| + | To install LM Studio on Ubuntu 24.04 LTS, you have two primary options: the **headless lms daemon** (ideal for servers, command-line usage, or API orchestration) or the **AppImage** (for the full graphical interface). | ||
| + | |||
| + | --- | ||
| + | |||
| + | ===== Option 1: Headless Daemon (lms) ===== | ||
| + | If you intend to use LM Studio for backend services, API hosting, or CI/CD, the '' | ||
| + | |||
| + | ==== 1. Install the Daemon ==== | ||
| + | Run the following command in your terminal to download and execute the official installer: | ||
| + | < | ||
| + | curl -fsSL https:// | ||
| + | </ | ||
| + | |||
| + | ==== 2. Usage ==== | ||
| + | Once the installation script completes, you can interact with the service directly using the '' | ||
| + | |||
| + | To start the background service: | ||
| + | < | ||
| + | lms daemon up | ||
| + | </ | ||
| + | |||
| + | **Note:** If you encounter an " | ||
| + | |||
| + | --- | ||
| + | |||
| + | ===== Option 2: Graphical AppImage (Full GUI) ===== | ||
| + | If you require the standard LM Studio desktop interface, you must download the AppImage. Note that Ubuntu 24.04 enforces strict sandboxing rules that require manual adjustment. | ||
| + | |||
| + | ==== 1. Download and Make Executable ==== | ||
| + | Download the latest Linux AppImage from the official LM Studio website, then give it execution permissions: | ||
| + | < | ||
| + | chmod +x LM_Studio-*.AppImage | ||
| + | </ | ||
| + | |||
| + | ==== 2. Extract and Configure Sandbox ==== | ||
| + | The application will likely fail to launch unless you fix the '' | ||
| + | < | ||
| + | # Extract the AppImage | ||
| + | ./ | ||
| + | |||
| + | # Navigate to the extracted folder | ||
| + | cd squashfs-root | ||
| + | |||
| + | # Fix sandbox permissions | ||
| + | sudo chown root:root chrome-sandbox | ||
| + | sudo chmod 4755 chrome-sandbox | ||
| + | </ | ||
| + | |||
| + | ==== 3. Launch the Application ==== | ||
| + | You can now run the application from within the extracted directory: | ||
| + | < | ||
| + | ./lm-studio | ||
| + | </ | ||
| + | |||
| + | If you still encounter sandboxing issues and prefer to bypass it, you can launch with the '' | ||
| + | < | ||
| + | ./lm-studio --no-sandbox | ||
| + | </ | ||
| + | |||
| + | --- | ||
| + | |||
| + | ===== Troubleshooting & Performance ===== | ||
| + | ^ Issue ^ Resolution ^ | ||
| + | | **Missing Dependencies** | Install base libraries: \\ < | ||
| + | | **Hardware Acceleration** | For integrated or discrete GPUs, ensure your drivers (such as '' | ||
tech/linux.1781481222.txt.gz · Last modified: by glong
