CUDA Runtime Installation on Minimal Jetson Orin Nano Image

Issue Overview

Users are experiencing difficulties installing the CUDA runtime on a minimal image for the Jetson Orin Nano developer board. The main challenges include:

• Absence of essential tools like sudo and dpkg in the minimal image
• Inability to use standard installation methods (.deb packages or .run files)
• Confusion about the correct CUDA version and installation package for Jetpack 5.1.2
• Limitations in using NVIDIA SDK Manager on non-Ubuntu distributions

The issue impacts users’ ability to set up and utilize CUDA capabilities on their Jetson Orin Nano boards, particularly those using custom minimal images or non-standard development environments.

Possible Causes

1. Minimal Image Limitations: The custom-built minimal image lacks common utilities and package management tools, preventing standard installation methods.

2. Incompatible CUDA Version: Attempting to install CUDA 12.3.2 instead of the recommended 11.4 for Jetpack 5.1.2 may cause compatibility issues.

3. Incorrect Installation Method: Using installation methods designed for full Linux distributions on a minimal image can lead to failures.

4. SDK Manager Compatibility: NVIDIA SDK Manager’s limited compatibility with non-Ubuntu distributions restricts its use on systems like Linux Mint.

5. Insufficient System Resources: The minimal image may lack necessary dependencies or libraries required for CUDA installation.

Troubleshooting Steps, Solutions & Fixes

1. Verify CUDA Version Compatibility:

   • Confirm that CUDA 11.4 is the correct version for Jetpack 5.1.2.
   • Avoid using CUDA 12.3.2 packages, as they may not be compatible with your Jetson Orin Nano setup.

2. Use Appropriate CUDA Package:

   • Download the correct CUDA package for Jetson:

     wget https://repo.download.nvidia.com/jetson/common/pool/main/c/cuda-11-4/cuda-11-4_11.4.19-1_arm64.deb
     

   • This package is specifically designed for Jetson devices and should be compatible with your setup.

3. Add Essential Tools to Minimal Image:

   • Consider modifying your Yocto BSP layer or other custom layers to include essential tools like sudo, dpkg, and other utilities.
   • Add the following packages to your image recipe or local.conf:

     IMAGE_INSTALL_append = " sudo dpkg"
     

4. Manual Package Extraction and Installation:

   • If dpkg is not available, you can try manually extracting the CUDA package contents:

     ar x cuda-11-4_11.4.19-1_arm64.deb
     tar xf data.tar.xz -C /
     

   • This method bypasses the need for dpkg but requires careful management of file permissions and dependencies.

5. Consider Using a Full Image:

   • If possible, switch to a full Jetson image that includes necessary tools and utilities for easier CUDA installation.
   • This approach may be more suitable for development and testing purposes.

6. SDK Manager Alternative:

   • For users on non-Ubuntu distributions, consider setting up an Ubuntu virtual machine or container specifically for running SDK Manager.
   • Use the VM/container to download and prepare CUDA packages, then transfer them to your development system.

7. Verify System Requirements:

   • Ensure your Jetson Orin Nano has sufficient storage space for CUDA installation (at least 5GB free).
   • Check that your board’s firmware and drivers are up-to-date and compatible with CUDA 11.4.

8. Custom Build Script:

   • Develop a custom installation script that handles dependency resolution and file placement without relying on package managers.
   • This script should:
     • Extract the CUDA package
     • Copy files to appropriate locations
     • Set correct permissions
     • Update necessary configuration files

9. Consult NVIDIA Developer Resources:

   • If issues persist, refer to NVIDIA’s official documentation for Jetson devices and CUDA installation.
   • Consider posting on NVIDIA’s developer forums for more specific assistance with your custom setup.

Remember to back up your system before attempting any significant changes or installations. If you’re developing a product, consider the trade-offs between using a minimal image and the ease of development with a full image that includes standard utilities.