Building the MetaClockClock78: My Largest Clock Project Yet

From my previous MetaClockClock project, I still had some hardware available. So I decided to build my largest build so far: to clocks with 78 clocks each.

MetaClockClock78
MetaClockClock78
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Tutorial: Creating Self-Contained MCUXpresso SDK Projects

In Tutorial: Getting Started with MCUXpresso SDK – Repositories with VS Code and Tutorial: Getting Started with MCUXpresso SDK – west I showed how to get the MCUXpresso SDK. In this article it is about tweaking and streamlining the project.

The result is a clean, portable and self-contained MCUXpresso SDK project.

VS Code with streamlined NXP MCUXpresso project
VS Code with streamlined NXP MCUXpresso project
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Tutorial: Getting Started with MCUXpresso SDK – Repositories with VS Code

In “Tutorial: Getting Started with MCUXpresso SDK – west“, I demonstrated the ‘west’ tool’s usage. It helps in acquiring an SDK repository. Instead using the command line tool, I can use the NXP VS Code extension to do the same.

NXP VS Code Extension to import a repository
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Tutorial: Getting Started with MCUXpresso SDK – west

In my earlier tutorial I showed how to install the necessary SDK tools. In this article I’m going to install the SDK sources. For this I’m going to use west. This is a command-line ‘meta-repository’ tool.

west update_board
west update_board
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Tutorial: Getting Started with MCUXpresso SDK – Tool Installation

The engineering and development landscape is constantly changing. This includes the embedded tooling and SDKs.

Back in the year 2017 I have used the version 2 (see Tutorial: Using Eclipse with NXP MCUXpresso SDK v2 and Processor Expert). Back then, it was Eclipse with make. Now we are in 2026 and things have changed to VS Code, cmake, ninja, python and west.

VS Code with MCUXpresso Installer
VS Code with MCUXpresso Installer

Luckily, although more and different tools are needed these days, the installation experience has improved significantly. It has shifted from installing multiple different tools to a streamlined installation process.

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Boost Windows 11 Dev Performance with Docker Volumes

I recently upgraded from Win10 to Win11. Windows 10 was not great for building performance compared to Linux. And I feel that with Windows 11 things got worse too.

Dev Container in VS Code uses docker-based environments. This enables me using a full-featured development environment, with isolated dependencies. This is especially very useful for development in the embedded systems space. There I have to use many different SDKs, toolchains and libraries. Using Dev Containers is super easy. But file I/O operations with building etc/is not that great.

The solution is to use a Docker Volume with VS Code and Dev Container:

Build Performance Comparison
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Using CAN FD for Remote Hardware Debugging of Cortex-M Devices

Today’s projects and systems get more and more complex. Many systems include multiple MCUs, connected with a field bus or network, for example CAN. For example there can be up to 70 CAN nodes in modern cars. Such larger and connected systems are a challenge for debugging.

Traditional hardware debugging requires a hardware debug probe, connected with a dedicated SWD/JTAG debug cable to the target device. This needs dedicated pins on the target device plus physical access to the device itself. In many cases, this is not possible in the final product. The hardware debug probes, cables, pins and high speed signals are costly. And worse they can introduce new problems and are prone to interference.

If there is a field bus like CAN connecting all the MCUs, why not use it for hardware debugging? Hardware debugging meaning programming the FLASH memory, halt the MCU, inspect the memory and registers, and step through the code?

Cortex-M Hardware Debugging over CAN

Yes, we can! With the help of a rather unknown hardware feature on ARM Cortex-M devices. We can use the ARM DebugMonitor Interrupt to control and debug the target system. As we would use a JTAG/SWD connection. Instead, we use the CAN bus :-).

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Sharing Standalone NXP SDK Projects in VS Code

The NXP SDK is git based which is great. If I create a project with VS code, it references the SDK cloned locally.

Standard NXP SDK Project in VS Code

A standalone project structure is needed if you want to easily share a project with your team. It’s also necessary for sharing inside a classroom environment. This article shows how to use an NXP SDK project in standalone mode.

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GitLab Automated CI/CD Embedded Multi-Project Building using Docker

In CI/CD for Embedded with VS Code, Docker and GitHub Actions, I used GitHub to build a pipeline. This setup supports continuous integration within a CI/CD environment.

This time, let’s do a similar thing. But instead of GitHub, I use GitLab with VS Code. And I use it for a project where three different MCUs are used: the Raspberry Pi Pico-W, an Espressif ESP32 plus the NXP K22FX512 on the Sumo robot:

Raspberry Pi Pico-W, Espressif ESP32 and Robot with NXP K22FX512
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Low-Power Optimization Techniques for ARM Cortex-M Microcontrollers

Europe is currently facing an ‘Energy Crisis,’ and ‘Sustainability’ is a popular topic among companies. However, embedded engineers go beyond talking—they take action and make tangible changes in the world. With the increasing use of electronic devices, minimizing their energy and power consumption is crucial. Optimizing systems for deep low power or deep low energy is a challenging task. Nonetheless, as I will demonstrate in this article, it is possible to reduce energy consumption by a factor of 100 or more. This article provides a brief overview of the foundational concepts and then applies them step-by-step to an ARM Cortex microcontroller.

Measuring on-board LPC804 with MCU-Link Pro
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