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.
The latest release of the NXP LinkServer supports ARM 64bit (Debian) besides Windows, Linux and MacOS. With this, I can now develop on an NXP i.MX board. Plus, this enables an inexpensive way for automated on-target tests and CI/CD.
A few days ago, a reader of my blog sent me a message:
“Hi Erich, I am reading you since a lot of years. I think you are a pillar of my professional career. Thanks for this. Let me ask you now: what do you think about LLM and coding with LLM in embedded? My employer thinks it time to stop to hire people, because in 1/2 years everything will be substituted by AI. I am not on the same page. Are you using LLM for coding? What do you think about it? Thanks in advance.”
TL;DR: LLMs are changing and improving, making good engineering and education even more important. Studies show that AI can be useful, but productivity will not always increase. AI coding means more critical thinking and responsibility, not less. Engineering and education needs to adopt and change. This includes assessments and didactic, back to paper and defending the work. Learning how to learn is getting the critical skill in the age of AI.
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 :-).
I’m shifting more and more of my CI/CD testing infrastructure using the LinkServer runner. One reason is the LinkServer runner can run the test on-target. It can also collect GNO gcov coverage information at the same time. LinkServer is a suite of software tools for launching and managing GDB servers for NXP debug probes.
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.
FreeRTOS has a great performance measurement feature built-in: Performance counters. At each context switch, the RTOS can do a bookkeeping of time spent in tasks. With this, it can estimate the runtime distribution between the tasks. A very useful feature to get a feeling what the tasks are doing.
But I noticed that with recent FreeRTOS versions, VS Code extension have issues showing the correct runtime counter values:
Unknown Runtime Counters in VS Code Extension (mcu-debug.rtos-views)Continue reading →