View source for AI:How to measure machine learning model power consumption with STM32Cube.AI generated application

== Add X-CUBE-AI software pack ==

Select X-CUBE-AI software pack Core and System Performance application:
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[[File:CubeAI_SW_Pack.png|center|alt=STM32CubeAI selection|STM32CubeAI selection]]
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Click on X-CUBE-AI software pack:
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[[File:CubeAI_SW_Pack2.png|center|alt=STM32CubeAI software pack|STM32CubeAI software pack]]
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If by default the peripherals parameters are not set for the best performance, the system warns you of this. Select 'yes' to make sure that the maximal frequency is used.
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[[File:CubeAI_SW_BestPerf.png|center|alt=STM32CubeAI best performance|STM32CubeAI best performance]]
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X-CUBE-AI configures default parameters to set the best performance as well as configuring the UART used to report performances.

You can check which UART is used by X-CUBE-AI to communicate with the board. It is the UART connected to the STLink embedded device which is seen from the PC as a Virtual Com Port once connected by USB.
To do so open the Platform Settings panel:
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[[File:CubeAI_UART.png|center|alt=STM32CubeAI platform settings|STM32CubeAI platform settings]]
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For the NUCLEO-L4R5ZI it is the LPUART1.
You can also check the settings used by X-CUBE-AI for the specified UART in the Connectivity panel / Parameter Settings:
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[[File:CubeAI_UART2.png|center|alt=STM32CubeMX UART configuration|STM32CubeMX UART configuration]]
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These settings must be used on PC the hyper terminal to communicate with the board when the system-performance application is running.
   
Identify the GPIOs used by the UART in the GPIO Settings panel: 
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[[File:CubeAI_UART3.png|center|alt=STM32CubeMX UART pins|STM32CubeMX UART pins]]
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For the NUCLEO-L4R5ZI, it is the {{Highlight|PG7}} and {{Highlight|PG8}} (Pin 7 and 8 of bank G).