Jetson Orin Nano Dev Board: NanoDB Not Working

Issue Overview

Users are experiencing issues with the NanoDB application on the Nvidia Jetson Orin Nano 8G development board. The primary symptoms include:

• The web UI for NanoDB opens successfully, but any search attempts result in the application freezing, rendering the system unresponsive (users cannot even move the mouse).
• This issue occurs after following a specific tutorial for setting up NanoDB, which involves loading an existing MS COCO example database.

The problem appears to be related to memory constraints, as indicated by discussions in the forum where users noted that the board was running low on memory during operations. The frequency of this issue is not explicitly stated, but it seems to happen consistently when attempting to perform searches in NanoDB after loading a limited dataset of 68 images from the MS COCO dataset.

Possible Causes

Several potential causes for this issue have been identified:

• Hardware Limitations: The Jetson Orin Nano may not have sufficient memory to handle the operations required by NanoDB, leading to freezing.
• Software Bugs: There could be bugs within NanoDB or its dependencies that cause it to hang when processing requests.
• Configuration Errors: Incorrect settings or parameters when running the container could lead to performance issues.
• Driver Issues: Outdated or incompatible drivers may affect the functionality of GPU operations, especially with PyTorch.
• Environmental Factors: Insufficient power supply or overheating could contribute to system instability.
• User Errors: Misconfigurations during setup or execution of commands could lead to unexpected behavior.

Troubleshooting Steps, Solutions & Fixes

To address the issue with NanoDB on the Jetson Orin Nano, users can follow these troubleshooting steps and potential solutions:

1. Check System Resources:

   • Open a terminal and run:

     tegrastats
     

   • Monitor memory usage and ensure that there is enough available RAM during operation.

2. Disable Desktop GUI:

   • Consider disabling the desktop GUI to free up additional resources. Instructions for this can be found here.

3. Run in a Different Environment:

   • If possible, run the application on an NVME drive with swap memory enabled, as this configuration has been reported to improve performance.

4. Modify Command Parameters:

   • Ensure that the command used to run NanoDB is correctly formatted. For example:

     jetson-containers run $(autotag nanodb)
     python3 -m nanodb --path /data/nanodb/coco/2017 --server --port=7860
     

   • Verify that all paths and parameters are correct.

5. Test with Full Dataset:

   • If feasible, try using a larger dataset to see if performance improves or if issues persist.

6. Update Software and Drivers:

   • Ensure that all software components are up-to-date, including JetPack and any relevant libraries.
   • Check for driver updates that may enhance GPU performance.

7. Check Logs for Errors:

   • Review terminal logs when running NanoDB for any error messages that may indicate what went wrong during execution.

8. Consider Alternative Libraries:

   • If issues continue, explore alternative libraries or frameworks that may offer similar functionality without the same resource constraints.

9. Community Support:

   • Engage with community forums for additional insights or solutions from other users who may have faced similar issues.

10. Documentation Links:

    • Refer to official documentation for further guidance on setup and troubleshooting: Nvidia Developer Forums.

By following these steps, users can systematically diagnose and potentially resolve the issues they are facing with NanoDB on their Jetson Orin Nano development board.