Get Started Guide

The Metro AI Suite Test Module and the Intel® ESDQ CLI tool are installed as part of the Metro AI Suite Device Qualification Tool.

NOTE: The screenshots may show a package version number different from the current release.

Prerequisite

Perform a clean installation of Ubuntu* 24.04.1 LTS or higher on the target system (For Core and Core Ultra platform, Ubuntu 24.04.2 LTS is preferred, for Xeon platform, Ubuntu 24.04.2 LTS Server is preferred).

Download and Install Intel® ESDQ for Metro AI Suite Device Qualification Tool

1. Click SignIn and Select Download to download the Metro AI Suite Device Qualification Tool package.

   

   Figure 1: Signing-In

   

   Figure 2: Configure and Download

2. Click Download. In the next screen, accept the license agreement and copy the Product Key.

   

   Figure 3: Product Key in Download Page

3. Transfer the downloaded package to the target Ubuntu* system and unzip:

   unzip Metro_AI_Suite_Device_Qualification.zip
   

4. Go to the Metro_AI_Suite_Device_Qualification/ directory:

   cd Metro_AI_Suite_Device_Qualification
   

5. Change permission of the executable edgesoftware file:

   chmod 755 edgesoftware
   

6. For Atom and Core platform, if your OS kernel is 6.5.0-35-generic, check if ‘echo $LC_IDENTIFICATION’ does show *UTF-8. If no, then proceed the following steps:

   sudo apt-get install locales -y
   sudo locale-gen en_US.UTF-8
   sudo update-locale LANG=en_US.UTF-8 LC_CTYPE=en_US.UTF-8 LC_IDENTIFICATION=en_US.UTF-8
   sudo reboot
   

7. Install the Metro AI Suite Device Qualification Tool package:

   sudo apt install python3.12-venv
   cd Metro_AI_Suite_Device_Qualification
   python3 -m venv venv
   ./edgesoftware install
   

8. When prompted, enter the Product Key. You can enter the Product Key mentioned in the email from Intel confirming your download (or the Product Key you copied in Step 2).

   Note for People’s Republic of China (PRC) Network:

   • If you are connecting from the PRC network, the following prompt will appear before downloading the modules

     Figure 3: Prompt to Enable PRC Network

   • Type No to use the default settings, or yes to enter the local mirror URL for pip and apt package managers.

   • Similar prompt will appear during bmra base installation:

     Figure 4: Prompt to Enable PRC Network Mirror

   • Type Yes, to avoid download failure in the PRC network, some follow up prompts will appear.

   • Type No to use the default GitHub mirror and Docker hub mirror.

     If you want to enable RDM and XPU Manager under PRC network, you need to type Yes to enter an available Docker hub mirror

     Figure 5: Prompt to Access Proxy Server for Installation on PRC Network

   • Then you can choose whether to install XPU Manager, if you type yes, please make sure you have replaced the default Docker hub mirror in previous step:

     Figure 6: Prompt to Enable XPU Manager on PRC Network

   • The following prompt will appear, type yes to use default Github mirror:

     Figure 7: Prompt to change GitHub mirror on PRC Network

9. For Atom and Core platform, it will prompt to reboot the system if your kernel is not 6.5.0.35-generic. After rebooting the system, go to step 6 again to check $LC_IDENTIFICATION. Then install again with command ./edgesoftware install

10. When prompted to reboot the machine, press Enter. Ensure to save your work before rebooting.

    

    Figure 10: Prompt to Reboot

11. After rebooting, resume the installation:

    cd Metro_AI_Suite_Device_Qualification
    ./edgesoftware install
    

12. After the ESDQ is installed, you will be prompted for the password. Enter the password to proceed.

    

    Figure 11: Prompt for Password

13. When the installation is complete, you will see the message “Installation of package complete” and the installation status for each module.

    Figure 12: EEF Lincense Agreement

    

    Figure 13: Installation Complete Message

14. Reboot the system:

    sudo reboot
    

Next Step

Refer to Run Application Section on how to run ESDQ.

Known Issues

[QIR-340]:on Intel® Xeon® + Intel® Arc™ A770 platform, OpenVINO™ performance is low compared with AIBOX4.0 OV performance on 12th generation processors + Intel® Arc™ A770 platform.

Troubleshooting

1. As the system is being automatically updated in the background, you may encounter the following errors:

   

   Figure 13: Example Error

   

   Figure 14: Example Error

   To resolve this issue, reboot and manually update the system. Then, rerun the installation:

   sudo reboot
   sudo apt update
   ./edgesoftware install
   

2. If the network quality is poor, you may encounter the following error:

   Figure 15: Example Error

   To resolve this issue, you can configure to run sudo without entering a password before installing:

   sudo visudo
   

Navigate to “# User privilege specification” section and add the following line to grant the current user sudo privileges without requiring a password: bash     USER ALL=(ALL) NOPASSWD: ALL     Please replace USER with your actual username. After adding the line, save and exit, then reinstall the package.

3. If you are facing “output” folder write permission issue, please give required access permission and rerun the test. Deleting will also help to recover the problem, but please note the previous results cant be recovered.

4. If ESDQ package installation failed, please reinstall it

   Figure 16: ESDQ Package Failure

5. OpenVino Test Suite Failed to Run AI models download might be failed during installation time due to NW glitches or slowness. Please try download them manually by following the steps,

   1. Ensure the ai_models_fetching docker image is available. If not, build the container using below command,

      ./modules/DQT_Test_Module/src/openvino_benchmark/ai_model_fetching/build_container.sh
      

   2. Run the script to download the models manually,

      ./modules/DQT_Test_Module/src/openvino_benchmark/ai_model_fetching/get_ai_models.sh
      

   3. Ensure the models are dowloaded successfully,

      ls -l ~/share/models/public
      

   

   Figure 17: AI Models

   4. Now rerun the Openvino Test Cases, sample below

      esdq --verbose module run metro-device-qualification --arg "-r OVRunner -d GPU.0 -t 180"
      

6. Frequency Runner Test Suite failed when running full suite where the system has iGPU & dGPU, Run the Frequency Runner Test individually for iGPU & dGPU separately,

   esdq --verbose module run metro-device-qualification --arg "-r FreqRunner -d GPU.0 -t 1"
   esdq --verbose module run metro-device-qualification --arg "-r FreqRunner -d GPU.1 -t 1"
   

If you’re unable to resolve your issues, contact the Support Forum

Release Notes

Current Version: 1.5.1

New in This Release

• Integrated Edge Device Enablement Framework (EEF) Base Platform BKC.

• Openvino-2025.0.0 integrated.

• Following Models removed from OpenVino Benchmark Runner yolo-v3-tiny-tf yolo-v4-tf yolo-v3-tf yolo-v4-tiny-tf yolo-v5n yolo-v5m yolo-v8n

• Bug Fixes