MAUI ML.Net app running on arm64 Android device

Maxim Sarukhanov 20 Reputation points
2023-08-15T20:07:46.25+00:00

Hello there!

I have managed to create MAUI App, that utilizes ML model trained on my Windows PC. This is simple app, that classifies text into 2 categories, positive or negative. Here are the links for tutorial https://www.youtube.com/watch?v=IwNSeevNrNg and sources of this app https://github.com/alfamizar/Maui.ML.Net.App.
So, I am curious if ML net running .Net 6 utilising or supporting any kind of hardware acceleration? May be it is using GPUs OpenCL acceleration? Sample app is simple and performant and I am curious, if I can scale complecity without performance drops running on Android device in scope of .Net MAUI project?

.NET MAUI
.NET MAUI
A Microsoft open-source framework for building native device applications spanning mobile, tablet, and desktop.
3,597 questions
.NET Machine learning
.NET Machine learning
.NET: Microsoft Technologies based on the .NET software framework.Machine learning: A type of artificial intelligence focused on enabling computers to use observed data to evolve new behaviors that have not been explicitly programmed.
159 questions
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Accepted answer
  1. Yonglun Liu (Shanghai Wicresoft Co,.Ltd.) 44,011 Reputation points Microsoft Vendor
    2023-08-16T05:14:44.33+00:00

    Hello,

    I am curious if ML net running .Net 6 utilising or supporting any kind of hardware acceleration? May be it is using GPUs OpenCL acceleration?

    According to this sample code survey, the reason it can also run efficiently on Android is that this project uses a data prediction model that has already been generated, rather than being trained in the project.

    For hardware acceleration, it is generally used in machine learning during the training of data models.

    In the project you provide, you are actually part of the Using Model phase of the data model. Hardware acceleration is not required at this point.

    You could refer to Code workflow for more details.

    For training data models, it is recommended that you do it on a PC to enable hardware acceleration. The efficiency of using a data model is roughly the same regardless of the platform.

    Best Regards,

    Alec Liu.


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