SCF Execution ERROR after hours of camera capture

Issue Overview

Users are experiencing segmentation faults and aborted executions while using the Nvidia Jetson Orin Nano Dev board with Jetpack 5.1.2-b104 during extended periods of camera capture. The setup involves a Leopard Imaging carrier board connected to multiple cameras via DS90UB954 FPD-Link III Deserializer and DS90UB953 Serializer. The issue manifests after approximately 30 minutes to 10 hours of capturing images, leading to crashes in the code that utilizes CUDA for inference.

The backtrace logs indicate that the crashes occur within various libraries, primarily related to memory allocation and mutex locking. The errors suggest potential problems with memory management or thread synchronization, which could severely impact system functionality and user experience.

Possible Causes

• Memory Management Issues: The segmentation faults may be triggered by improper memory allocation or deallocation, leading to memory corruption.

• Thread Synchronization Problems: Errors related to mutex locks indicate potential race conditions or deadlocks in the multithreaded environment.

• Software Bugs or Conflicts: The use of Jetpack 5.1.2-b104 may introduce bugs that have been resolved in later versions.

• Driver Incompatibilities: Mismatched or outdated drivers for the camera hardware may lead to instability during prolonged operations.

• Configuration Errors: Incorrect setup of the camera or software parameters could result in unexpected behavior during execution.

• Environmental Factors: Issues such as overheating or power supply inconsistencies may contribute to system instability.

Troubleshooting Steps, Solutions & Fixes

1. Update Jetpack Version:

   • Move to the latest public release version of Jetpack (e.g., Jetpack 5.1.3) as it contains stability updates.
   • Command to check current version:

     cat /etc/nv_tegra_release
     

2. Firmware Update:

   • Ensure that you are using the correct RCE firmware for your device.
   • Download and replace the camera-rtcpu-t234-rce.img firmware if necessary.
   • Follow the steps outlined in relevant topics for updating firmware without using flash.sh.

3. Monitor Memory Usage:

   • Use tools like htop or top to monitor memory consumption during operation.
   • Look for memory leaks in your application code that might lead to crashes.

4. Debugging Segmentation Faults:

   • Utilize GDB to analyze backtrace logs and identify the source of segmentation faults.
   • Example command:

     gdb <your_application>
     

5. Test with Different Configurations:

   • Isolate the issue by testing with fewer cameras or different camera configurations.
   • Check if reducing the workload prevents crashes.

6. Check for Environmental Factors:

   • Ensure adequate cooling and stable power supply to prevent overheating or power-related issues.

7. Implement Logging:

   • Add logging statements throughout your code to trace execution flow and catch errors before they lead to a crash.

8. Review Mutex Usage:

   • Examine how mutexes are being used in your application; ensure they are correctly locked and unlocked.

9. Community Support and Documentation:

   • Refer to Nvidia’s developer forums and documentation for additional troubleshooting steps and community insights.
   • Post new issues separately if problems persist after upgrading and troubleshooting.

10. Best Practices for Future Prevention:

    • Regularly update software and firmware.
    • Conduct stress tests on your application before deploying it in critical environments.

By following these steps, users can systematically diagnose and potentially resolve the SCF execution errors encountered during extended camera capture sessions on the Nvidia Jetson Orin Nano Dev board.