MATLAB Examples

Code Verification and Validation with PIL

This example shows you how to use Embedded Coder Support Package for ARM Cortex-M Processors for code verification and validation using PIL.

Contents

Introduction

In this example you will learn how to configure a Simulink model to run Processor-In-the-Loop (PIL) simulations. In a PIL simulation, the generated code runs on a QEMU ARM Cortex-M3 emulator. The results of the PIL simulation are transferred to Simulink to verify the numerical equivalence of the simulation and the code generation results. The PIL verification process is a crucial part of the design cycle to ensure that the behavior of the deployment code matches the design.

This example introduces the Simulink code generation and verification workflow by showing you how to:

  • Configure a Simulink model to run PIL simulations on the ARM Cortex-M3 (QEMU) emulator target

Prerequisites

We recommend completing the Getting Started with Embedded Coder Support Package for ARM Cortex-M Processors example.

Task 1 - Verify the generated code for a subsystem using a PIL block

This example shows how to use a PIL block for subsystem code verification. With this approach:

  • You can verify the code generated for a subsystem
  • You must provide a test harness model to supply a test vector or stimulus inputs
  • You must swap your original subsystem with a generated PIL block; you should be careful to avoid saving your model in this state as you would lose your original subsystem

1. Open the PIL Block model. This model is configured for the ARM Cortex-M3 (QEMU) target. The objective here is to create a PIL block out of the Controller subsystem that you will run on the QEMU ARM Cortex-M3 emulator.

2. Follow the below steps to enable PIL through the configuration parameters window:

Alternatively you can enable PIL from MATLAB command window through the following command set_param('arm_cortex_m_pil_block','CreateSILPILBlock','PIL')

3. Follow the below steps to create a PIL block for the Controller subsystem:

4. Follow the below steps to run the PIL simulation:

5. Once you start the simulation, a QEMU session running the PIL block is launched. You can switch between the original and PIL block subsystems by double clicking on the Manual Switch block. Double click on the Numerical Differences block to see the difference between the simulated Controller subsystem and the PIL block running on the QEMU emulator.

Task 2 - Verify referenced model code using PIL

This example shows how to verify the generated code for a referenced model by running a PIL simulation. With this approach:

  • You can verify code generated for referenced models
  • You must provide a test harness model to provide a test vector or stimulus inputs
  • You can easily switch a Model block between normal and PIL simulation mode

1. Open the Model Block PIL model. This model is configured for the ARM Cortex-M3 (QEMU) target. The model contains two Model blocks that both point to the same referenced model. You will configure one Model block to run in PIL mode while the other one will be set to normal mode.

2. Follow the below steps to configure and run the CounterA Model block in PIL mode:

3. When the model starts running, Scope1 displays the PIL simulation output running on the QEMU emulator while Scope2 shows the normal mode simulation output.

Task 3 - Verify top model code using PIL

This example shows how to verify the generated code for a model by running a PIL simulation. With this approach:

  • You can verify code generated for a top model
  • You must configure the model to load test vectors or stimulus inputs from the MATLAB workspace
  • You can easily switch the entire model between normal and PIL simulation mode

1. Open the Top Model PIL model. This model is configured for the ARM Cortex-M3 (QEMU) target.

2. Follow the below steps to run the top model PIL simulation:

3. When the PIL simulation terminates, a logsOut variable is created in the base workspace. The logsOut data contains PIL simulation results. You can access the logged data for signals count_a and count_b using the following commands:

  • count_a = get(logsOut,'count_a');
  • count_a.Values.Data
  • count_b = get(logsOut,'count_b');
  • count_b.Values.Data

Summary

This example introduced code verification workflow using PIL simulation.