AN 1011: TinyML Applications in Altera FPGAs Using LiteRT for Microcontrollers

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ID 848984
Date 4/07/2025
Public
Document Table of Contents
Document Table of Contents x
1. Overview 2. Preparing LiteRT Inference Model 3. Generating Nios® V Processor System 4. Generating Arm Processor System 5. Programming and Running 6. Appendix 7. Document Revision History for the AN 1011: TinyML Applications in Altera FPGAs Using LiteRT for Microcontrollers
1. Overview x
1.1. Requirements
2. Preparing LiteRT Inference Model x
2.1. Defining the Problem 2.2. Gathering and Preparing Sample Data 2.3. Building TensorFlow Model 2.4. Preparing the LiteRT Model 2.5. Preparing Binaries for C/C++
2.2. Gathering and Preparing Sample Data x
2.2.1. Preparing Dataset 2.2.2. Preprocessing Dataset
2.3. Building TensorFlow Model x
2.3.1. Constructing Model Architecture 2.3.2. Configuring Model 2.3.3. Training Model 2.3.4. Evaluating the Model 2.3.5. Saving and Loading Model
2.4. Preparing the LiteRT Model x
2.4.1. Converting into LiteRT Model 2.4.2. Saving the LiteRT Model 2.4.3. Analyzing the LiteRT Model 2.4.4. Loading a LiteRT Interpreter 2.4.5. Evaluating the LiteRT Model
2.5. Preparing Binaries for C/C++ x
2.5.1. Converting LiteRT to a C Array 2.5.2. Preparing a Header File for LiteRT C Array 2.5.3. Preparing Supporting Header File for LiteRT C Array 2.5.4. Preparing Main Function to Run TinyML 2.5.5. Converting MNIST Sample into C Array
3. Generating Nios® V Processor System x
3.1. Building Hardware Design in Platform Designer 3.2. Building Software Design with Ashling* RiscFree* IDE for Altera® FPGAs
3.2. Building Software Design with Ashling* RiscFree* IDE for Altera® FPGAs x
3.2.1. Creating a Board Support Package 3.2.2. Building LiteRT for Microcontroller Static Library 3.2.3. Creating an Application Project File 3.2.4. Building the LiteRT TinyML Application
4. Generating Arm Processor System x
4.1. GHRD Hardware Design 4.2. Building the Software Design
4.2. Building the Software Design x
4.2.1. Arm-Trusted-Firmware 4.2.2. Building LiteRT for Microcontrollers Static Library 4.2.3. Zephyr OS Environment Setup 4.2.4. Building the LiteRT TinyML Application
4.2.1. Arm-Trusted-Firmware x
4.2.1.1. Booting from QSPI Flash 4.2.1.2. Running through Ashling* RiscFree* IDE for Altera® FPGAs Debugger
5. Programming and Running x
5.1. Nios® V Processor System 5.2. Arm HPS Processor System
5.2. Arm HPS Processor System x
5.2.1. Booting from QSPI 5.2.2. Booting via the Debugger
6. Appendix x
6.1. main.cc for Nios V Processor 6.2. main.cc for Arm HPS Processor
1. Overview
2. Preparing LiteRT Inference Model
3. Generating Nios® V Processor System
4. Generating Arm Processor System
5. Programming and Running
6. Appendix
7. Document Revision History for the AN 1011: TinyML Applications in Altera FPGAs Using LiteRT for Microcontrollers

3.2. Building Software Design with Ashling* RiscFree* IDE for Altera® FPGAs

Note: Ensure you complete the steps in Preparing LiteRT Inference Model before continuing this chapter.
Once the processor system is ready, start building the software design using Ashling* RiscFree* IDE for Altera® FPGAs. Follow these steps:
  1. Create a Board Support Package (BSP) project.
  2. Build LiteRT for Microcontrollers static library.
  3. Create a Nios V application project with Hello World TinyML example source code.
  4. Import both projects into RiscFree IDE’s workspace.
  5. Build the Hello World application.

Altera recommends you create a similar directory tree in your design project to ensure a streamlined build flow. The following software design flow is based on this directory tree.

To create the software project directory tree:
  • In your design project folder, create a folder called software.
  • In the software folder, create two folders called app and bsp.
    Figure 11. Software Project Directory Tree
Table 3.   LiteRT for Microcontrollers Binaries at Prerequisite
Binaries Description
model_data.cc Model params stored within a C array.
model_data.h Header file of model_data.h.
model_settings.h List of classes to decode classification results in main.cc.
main.cc Main LiteRT application to setup LiteRT model, uploading images, classifying images and profiling.
Multiple figure.h Sample of MNIST images stored within a C array.

Section Content
Creating a Board Support Package
Building LiteRT for Microcontroller Static Library
Creating an Application Project File
Building the LiteRT TinyML Application

Level Two Title