Comment by miki123211 5 hours ago
Are there any good resources on how this kind of real-time programming is done?
What goes into ensuring that a program is actually realtime? Are there formal proofs, or just experience and "vibes"? Is realtime coding any different from normal coding? How do modern CPU architectures, which have a lot of non-constant time instructions, branch prediction, potential for cache misses and such play into this?
There's some difference between user space and kernel. I don't have much experience in the kernel, but I feel like it's more about making sure tasks are preemptable.
In user space it's often about complexity and guarantees: for example, you really try not to do mallocs in a real-time thread in user space, because it's a system call that will only return in an unpredictable amount of time. Better to preallocate buffers or use the stack. Same for opening files, or stuff like that -- you want to avoid variable time syscalls and do them at thread / application setup.
Choice of algorithms needs to be such that for whatever n you're working with, that it can be processed inside of one sample generation interal. I'm mostly familiar with audio -- e.g. if you're generating audio at 44100 Hz, you need your algorithms to be able to process chunks in less than 22 microseconds.
I'm not hugely experienced in the field personally, but from what I've seen, actually proving hard real time capabilities is rather involved. If something is safety critical (think break systems, avionic computers, etc.) it likely means you also need some special certification or even formal verification. And (correct me if I'm wrong) I don't think you'll want to use a Linux kernel, even with the preempt rt patches. I'd say specialized rt operating systems, like FreeRTOS or Zephyr, would be more fitting (though I don't have direct experience with them).
As for the hardware, you can't really use a ‘regular’ CPU and expect completely deterministic behavior. The things you mentioned (and for example caching) absolutely impact this. iirc amd/xilinx actually offer a processor that has both regular arm cores, alongside some arm real time cores for these exact reasons.
For things like VxWorks, it's mostly vibes and setting priority between processes. But there are other ways. You can "offline schedule" your tasks, i.e. you run a scheduler at compile time which decides all possible supported orderings and how long slots each task can run.
Then, there's the whole thing of hardware. Do you have one or more cores? If you have more than one core, can they introduce jitter or slowdown to each other accessing memory? And so on and so forth.
> it's mostly vibes and setting priority between processes
I'm laughing so so hard right now. Thanks for, among other things, confirming for me that there isn't some magic tool that I'm missing :). At least I have the benefit of working on softer real-time systems where missing a deadline might result in lower quality data but there's no lives at risk.
Setting and clearing GPIOs on task entry/exit are a nice touch for verification too.
Magic? Well, here's some: predictably fast interrupts, critical sections where you code cannot be preempted, but with a watchdog so if your code hits an infinite loop it's restarted, no unpredictable memory allocation delays, no unexpected page fault delays, things like that.
These are relatively easy to obtain on an MCU, where there's no virtual memory, physical memory is predictable (if slow), interrupt hardware is simple, hardware watchdogs are a norm, an normally there's no need for preemptive multitasking.
But when you try to make it work in a kernel that supports VMM, kernel / userland privilege separation, user sessions separation, process separation, preemptive multitasking, and has to work on hardware with a really complex bus and a complex interrupt controller, — well, here's where magic begins.
http://www.rossbencina.com/code/real-time-audio-programming-...
Audio-centric, but will you give a feel for what's involved.
On all the real time systems I've worked on, it has just been empirical measurements of cpu load for the different task periods and a good enough margin to overruns.
On an ECU I worked on, the cache was turned off to not have cache misses ... no cache no problem. I argued it should be turned on and the "OK cpu load" limit decreased instead. But nope.
I wouldn't say there is any conceptual difference from normal coding, except for that you'd want to be kinda sure algorithms terminate in a reasonable time in a time constrained task. More online algorithms than normally, though.
Most of the strangeness in real time coding is actually about doing control theory stuff is my take. The program often feels like state-machine going in a circle.
> On an ECU I worked on, the cache was turned off to not have cache misses ... no cache no problem. I argued it should be turned on and the "OK cpu load" limit decreased instead. But nope.
Yeah, the tradeoff there is interesting. Sometimes "get it as deterministic as possible" is the right answer, even if it's slower.
> Most of the strangeness in real time coding is actually about doing control theory stuff is my take. The program often feels like state-machine going in a circle.
Lol, with my colleagues/juniors I'll often encourage them to take code that doesn't look like that and figure out if there's a sane way to turn it into "state-machine going in a circle". For problems that fit that mold, being able to say "event X in state Y will have effect Z" is really powerful for being able to reason about the system. Plus, sometimes, you can actually use that state machine to more formally reason about it or even informally just draw out the states, events, and transitions and identify if there's anywhere you might get stuck.
You don't break the electrical equipment/motor/armature/process it's hooked up to.
In rt land, you test in prod and hope for the best.
> What goes into ensuring that a program is actually realtime?
Realtime mostly means predictable runtime for code. As long as its predictable, you can scale the CPU/microcontroller to fit your demands or optimize your code to fit the constraints. It’s about making sure your code can always respond in time to hardware inputs, timers, and other interrupts.
Generally the Linux kernel’s scheduling makes the system very unpredictable. RT linux tries to address that along with several other subsystems. On embedded CPUs this usually means disabling advanced features like cache, branch prediction, and speculative execution (although I don’t remember if RT handles that part since its very vendor specific).