FAQ#

If you run different pipelines in a short period of time, you may encounter the following error:
Figure 1: Workload constraints error
This is because the maxConcurrentWorkload limitation in AiInference.config file. If the workloads hit the maximum, task will be canceled due to workload constrains. To solve this problem, you can kill the service with the commands below, and re-execute the command.
```
sudo pkill Hce
```

If you encounter the following error during code compilation, it is because mkl is not installed successfully: mkl_error

Figure 2: Build failed due to mkl error

Run ls /opt/intel to check if there is a OneAPI directory in the output. If not, it means that mkl was not installed successfully. You need to reinstall mkl by following the steps below:

curl -k -o GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB -L
sudo -E apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB && sudo rm GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
echo "deb https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/oneAPI.list
sudo -E apt-get update -y
sudo -E apt-get install -y intel-oneapi-mkl-devel lsb-release

If the system time is incorrect, you may encounter the following errors during installation:
Figure 3: System Time Error
You need to set the correct system time, for example:
```
sudo timedatectl set-ntp true
```
Then re-run the above installation command.
```
sudo apt-get remove --purge intel-oneapi-mkl-devel
sudo apt-get autoremove -y
sudo apt-get install -y intel-oneapi-mkl-devel
```
If you encounter the following errors during running on B580 platform:
Figure 4: Device Index Error
It may be because the iGPU is not enabled, only the B580 is enabled.

You can use lspci | grep VGA to view the number of GPU devices on the machine.

The solution is either enable iGPU in BIOS, or change the config of Device=(STRING)GPU.1 to Device=(STRING)GPU in VPLDecoderNode and VPLDecoderNode in pipeline config file, for example: ai_inference/test/configs/kitti/6C1L/localFusionPipeline.json.
If you encounter the following backends mismatch errors during running pipeline:
Figure 5: Backends Mismatch Error
This is because the wrong or non-existent device is selected. We need to select the dGPU+opencl Backend. As shown in the figure, it should be the second device (numbered starting from 0), that is, GPU.2.

The solution is change config Device=(STRING)GPU.4 to Device=(STRING)GPU.2 in LidarSignalProcessingNode in pipeline config file, for example: ai_inference/test/configs/kitti/6C1L/localFusionPipeline.json.

FAQ#

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