From 6b121d9aeee83e52d8eee077a52a6d2a868e76fa Mon Sep 17 00:00:00 2001 From: Simon Strycek Date: Tue, 7 Oct 2025 12:47:12 +0200 Subject: [PATCH] NXP backend: Add NXP backend tutorial page --- docs/source/backends-nxp.md | 41 ++++++++++++++++++++++++++++++++++--- 1 file changed, 38 insertions(+), 3 deletions(-) diff --git a/docs/source/backends-nxp.md b/docs/source/backends-nxp.md index f02f495f685..4783b4a5bc6 100644 --- a/docs/source/backends-nxp.md +++ b/docs/source/backends-nxp.md @@ -1,5 +1,40 @@ # NXP eIQ Neutron Backend -See -[NXP eIQ Neutron Backend](https://github.com/pytorch/executorch/blob/main/backends/nxp/README.md) -for current status about running ExecuTorch on NXP eIQ Neutron Backend. +This manual page is dedicated to introduction of using the ExecuTorch with NXP eIQ Neutron Backend. +NXP offers accelerated machine learning models inference on edge devices. +To learn more about NXP's machine learning acceleration platform, please refer to [the official NXP website](https://www.nxp.com/applications/technologies/ai-and-machine-learning:MACHINE-LEARNING). + +
+For up-to-date status about running ExecuTorch on Neutron Backend please visit the manual page. +
+ +## Features + +Executorch v1.0 supports running machine learning models on selected NXP chips (for now only i.MXRT700). +Among currently supported machine learning models are: +- Convolution-based neutral networks +- Full support for MobileNetv2 and CifarNet + +## Prerequisites (Hardware and Software) + +In order to succesfully build executorch project and convert models for NXP eIQ Neutron Backend you will need a computer running Windows or Linux. + +If you want to test the runtime, you'll also need: +- Hardware with NXP's [i.MXRT700](https://www.nxp.com/products/i.MX-RT700) chip or a testing board like MIMXRT700-AVK +- [MCUXpresso IDE](https://www.nxp.com/design/design-center/software/development-software/mcuxpresso-software-and-tools-/mcuxpresso-integrated-development-environment-ide:MCUXpresso-IDE) or [MCUXpresso Visual Studio Code extension](https://www.nxp.com/design/design-center/software/development-software/mcuxpresso-software-and-tools-/mcuxpresso-for-visual-studio-code:MCUXPRESSO-VSC) + +## Using NXP backend + +To test converting a neural network model for inference on NXP eIQ Neutron Backend, you can use our example script: + +```shell +# cd to the root of executorch repository +./examples/nxp/aot_neutron_compile.sh [model (cifar10 or mobilenetv2)] +``` + +For a quick overview how to convert a custom PyTorch model, take a look at our [exmple python script](https://github.com/pytorch/executorch/tree/release/1.0/examples/nxp/aot_neutron_compile.py). + +## Runtime Integration + +To learn how to run the converted model on the NXP hardware, use one of our example projects on using executorch runtime from MCUXpresso IDE example projects list. +For more finegrained tutorial, visit [this manual page](https://mcuxpresso.nxp.com/mcuxsdk/latest/html/middleware/eiq/executorch/docs/nxp/topics/example_applications.html).