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→Introduction
According to [https://community.nxp.com/docs/DOC-343798 NXP documentation], ''eIQ Machine Learning Software is a collection of software and development tools for NXP microprocessors and microcontrollers to do inference of neural network AI models on embedded systems.''
This Technical Note (TN for short) illustrates hot to use [https://www.nxp.com/design/software/development-software/eiq-ml-development-environment:EIQ eIQ ] in combination with Mito8M, DAVE Embedded Systems's latest SoM, which is built upon the [https://www.nxp.com/products/processors-and-microcontrollers/arm-processors/i.mx-applications-processors/i.mx-8-processors/i.mx-8m-family-armcortex-a53-cortex-m4-audio-voice-video:i.MX8M i.MX8M processor by NXP].
==Testbed==
For more information about the kernel and the root file system, please refer to the following section.
==Building NXP eIQ software==
NXP document [https://www.nxp.com/docs/en/nxp/user-guides/UM11226.pdf UM11226] describes illustrates how to build eIQ software support using Yocto Project tools. Even though the official procedure was tested against Ubuntu 16.04, a host running Ubuntu 18.04 was used successfully. By following step by step the official procedure,
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The above table lists the achieved results when the benchmark was run as detailed in [[#Running_the_tests_4|this section]]. In this case, the different when running at different ARM core frequencies is very little.
