Who is this for?

This learning path is for developers who want to learn how to create cross-platform applications with .NET MAUI and leverage performance improvements on Arm64.

What will you learn?

Upon completion of this Learning Path, you will be able to:

  • Create and build a .NET MAUI application
  • Measure code execution performance uplift on Arm64

Prerequisites

Before starting, you will need the following:

  • A Windows on Arm computer such as the Lenovo Thinkpad X13s running Windows 11 or a Windows on Arm virtual machine .
  • Visual Studio 2022 with .NET Multi-platform App UI development and Universal Windows Platform development installed.

Summary

AI-assisted

This summary was drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.

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You’ll create a .NET MAUI project in Visual Studio on Windows on Arm and add a compute workload to measure execution time on Arm64. First, you’ll implement helpers that generate vectors, calculate a*b+c, and time execution. Then, you’ll update the UI with a list view, run the workload, and review its processing results and timings.

Frequently asked questions

AI-assisted

These FAQs were drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.

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I don’t see the .NET MAUI project template in Visual Studio. What should I check?
Verify that the .NET Multi-platform App UI development workload is installed in Visual Studio. If it’s missing, modify your installation to add it.
Where should I add the `PerformanceHelper` and `VectorHelper` classes?
Add both classes to the .NET MAUI project so both are accessible from the application code that triggers the computation and updates the UI.
What does the AdditionOfProduct method compute and with which data types?
It computes a*b+c over pseudo-randomly generated vectors of double-precision values. The operation produces results that are then used for timing and display.
How do I know the performance measurement is working?
Run the app and look for timing and processing results in the list view. If the list updates after triggering the operation, the measurement path is active.
Which build configuration should I use when measuring execution time?
No configuration is explicitly specified. Use the same configuration for all runs so measurements are comparable.
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