Book Image

The Insider's Guide to Arm Cortex-M Development

By : Zachary Lasiuk, Pareena Verma, Jason Andrews
Book Image

The Insider's Guide to Arm Cortex-M Development

By: Zachary Lasiuk, Pareena Verma, Jason Andrews

Overview of this book

Cortex-M has been around since 2004, so why a new book now? With new microcontrollers based on the Cortex-M55 and Cortex-M85 being introduced this year, Cortex-M continues to expand. New software concepts, such as standardized software reuse, have emerged alongside new topics including security and machine learning. Development methodologies have also significantly advanced, with more embedded development taking place in the cloud and increased levels of automation. Due to these advances, a single engineer can no longer understand an entire project and requires new skills to be successful. This book provides a unique view of how to navigate and apply the latest concepts in microcontroller development. The book is split into two parts. First, you’ll be guided through how to select the ideal set of hardware, software, and tools for your specific project. Next, you’ll explore how to implement essential topics for modern embedded developers. Throughout the book, there are examples for you to learn by working with real Cortex-M devices with all software available on GitHub. You will gain experience with the small Cortex-M0+, the powerful Cortex-M55, and more Cortex-M processors. By the end of this book, you’ll be able to practically apply modern Cortex-M software development concepts.
Table of Contents (15 chapters)
1
Part 1: Get Set Up
5
Part 2: Sharpen Your Skills

Implementing Continuous Integration

IoT and ML have brought about an explosion of intelligent connected devices that bring massive benefits to various sectors such as industrial, healthcare, and many others. However, with interconnectivity and intelligence comes a steep increase in the complexity of the software.

Factors such as security, over-the-air updates, and networking stacks are essential for connectivity. To enable ML, models may need to be refreshed multiple times a week to stay accurate. For rich OSs such as Linux or Windows, many of these complications are resolved at the OS level and abstracted from the application running on it. For embedded devices, this is typically not true, and that complexity is passed on to the software developer to sort out.

This step change in complexity for embedded devices is causing a major disruption to how embedded software is managed throughout its life cycle. A traditional embedded device, such as a washing machine from the 1990s,...