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

Summary

This chapter outlined basic principles of performance optimization for Cortex-M systems. We took an example software algorithm, the dot product, and went through several boards and compiler options to explore performance implications. The skills learned in this chapter will help you optimize your Cortex-M system intelligently by altering the main factors influencing performance: processor type, software source code implementation, and compilers and compiler options.

No matter how optimized your system is for performance, there are still other important aspects to consider that ensure you have a quality Cortex-M product. The next chapter provides both an overview and practical guide for using machine learning on edge devices.