MLPerf Closed/NVIDIA Compilation Issues on Jetson AGX Orin

Issue Overview

Users are experiencing compilation errors when attempting to build the MLPerf-inference closed/NVIDIA on the Jetson AGX Orin. The specific symptoms include multiple error messages related to the dali::kernels::ScatterGatherGPU functions during the build process. The context of the problem arises during the compilation phase after setting up the environment with CUDA 11.4, cuDNN, and TensorRT 8.4.1, while using JetPack R35 (release), REVISION: 1.0. The errors occur consistently when executing the command make clean && make build -j12 in the specified directory, indicating a persistent issue affecting users’ ability to compile and run their applications effectively. The impact of these errors is significant, as they prevent successful compilation of machine learning models, thereby hindering development workflows.

Possible Causes

1. Hardware Incompatibilities or Defects: The issue may stem from compatibility problems between the Jetson AGX Orin and the installed software components, particularly if certain hardware features are not supported by the current JetPack version.

2. Software Bugs or Conflicts: There may be unresolved bugs in the NVIDIA DALI library or other dependencies that lead to function mismatches during compilation.

3. Configuration Errors: Incorrect configuration settings in the build environment or project files could lead to mismatched function signatures expected by the DALI library.

4. Driver Issues: Outdated or incompatible drivers for CUDA or DALI may cause discrepancies in function definitions, resulting in compilation failures.

5. Environmental Factors: Issues such as insufficient memory or CPU resources during compilation could lead to incomplete builds or unexpected errors.

6. User Errors or Misconfigurations: Users may have misconfigured their environment or failed to follow installation instructions correctly, leading to errors during the build process.

Troubleshooting Steps, Solutions & Fixes

1. Verify Environment Setup:

   • Ensure that CUDA 11.4, cuDNN, and TensorRT 8.4.1 are correctly installed.
   • Confirm that JetPack R35 is properly set up on the Jetson AGX Orin.

2. Check DALI Installation:

   • Reinstall DALI using the following command:

     pip3 install --extra-index-url https://developer.download.nvidia.com/compute/redist --upgrade nvidia-dali-cuda110
     

   • Ensure that you are using a compatible version of DALI with your CUDA setup.

3. Review Compilation Commands:

   • Use make clean before building to ensure that no residual files from previous builds are causing issues.
   • Execute the build command with reduced parallel jobs if memory issues are suspected:

     make build -j4
     

4. Investigate Error Messages:

   • Analyze specific error messages related to ScatterGatherGPU functions and check for updates or documentation regarding changes in function signatures.
   • Consider building DALI from source if pre-built binaries do not match expected signatures:

     git clone https://github.com/NVIDIA/DALI.git
     cd DALI
     mkdir build && cd build
     cmake ..
     make -j12
     

5. Consult Documentation and Community Resources:

   • Refer to NVIDIA’s official documentation for MLPerf and Jetson setup guides for any missed steps.
   • Engage with community forums for insights from other users who faced similar issues.

6. Update Drivers and Software:

   • Ensure all drivers related to CUDA and JetPack are up-to-date.
   • Check for any available firmware updates for the Jetson AGX Orin.

7. Test Different Configurations:

   • Attempt building with different combinations of installed libraries or configurations to isolate the issue.
   • If possible, test on a different machine or setup to rule out hardware-specific issues.

8. Best Practices for Future Prevention:

   • Regularly update software components and monitor compatibility notes from NVIDIA.
   • Maintain a clean development environment by using virtual environments for Python dependencies.

9. Recommended Approach:

   • If multiple users report success with a specific configuration or installation method, adopt that as a primary approach for troubleshooting.

By following these steps, users should be able to diagnose and potentially resolve compilation issues related to MLPerf on their Jetson AGX Orin devices effectively.