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ReinhardKeil authored Jun 21, 2024
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Software algorithms for Digital Signal Processing (DSP) or Machine Learning (ML) frequently require significant CPU resources and need to be optimized for the target hardware. Comparing performance of such "load heavy" algorithms requires that they can be automatically executed with different configurations parameters but using identical input. The timing in AVH FVP models is based on a instruction could, therefore it is not timing accurate. However the results can still be used for performance estimation and A/B comparison of algorithms.

**AVH FVP** simulation models allow users to test their programs at scale with reproducible input patterns and so validate and optimize application performance which allows you to:
**AVH FVP** simulation models allow users to test their programs at scale with reproducible input patterns. This allows you to validate and optimize application performance. Usage examples are:
- Compare speed of different implementations of an algorithm (A/B test).
- Optimize resources (i.e. RTOS memory buffers for stream processing) towards application requirements.

## Continuous Testing {#CI}

Applying continuous integration work flows for embedded applications can be complicated by the specifics of development environments and the need of executing the program on target hardware. So the development teams are often reluctant to spend initial effort setting up the continuous integration (CI) workflow even though the long-term benefits are undisputed as shown on the Figure below
Applying continuous integration work flows for embedded applications can be complicated by the specifics of development environments and the need of executing the program on target hardware. Development teams are often reluctant to spend initial effort setting up the continuous integration (CI) workflow even though the long-term benefits are undisputed as shown on the figure below.

![Comparison of test efforts in CI and no CI workflows](./images/effort_comparison.png)

**Arm Virtual Hardware** simplifies the setup and use of CI workflows in embedded projects.
**AVH FVP** simplifies the setup and use of CI workflows in embedded projects. The integration in tools such as Keil MDK and GitHub Actions simplifies setup of CI workflows.

For unit and integration tests virtual targets offer additional advantages over hardware, including:
- **Speed** - no overhead for flashing the application on physical hardware. This saves time on small and fast unit tests.
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