Klipper Estimator does not handle running out of memory well on a RasPi 4 , 4 GB about klipper_estimator

[psiberfunk]

Thanks ! @dalegaard : Slow is relative I guess.. I have 2-3 hour prints estimating in 5 seconds on my RasPi 4 while printing!

[psiberfunk]

I'm not familiar with rust, but my guess here is that one approach that would scale reasonably well would be to analyze a "layer at a time" in-memory in cases of not having enough to take the whole GCODE file all at once, which is, I suspect, the issue from browsing the code briefly. I'm sure there's other ways to chunk it up as well, but I think in most cases a single layer should fit in the memory of most machines you'd want to run this on, even the relatively memory limited smaller Raspis.

[dalegaard]

Estimation mode indeed relies on loading the entire file, so it can't reasonably run on a Pi currently. Post processing mode works fine though, as it runs in constant memory.

I don't really see the use case for estimate on weak machines as it's mainly a tool for optimization. Change something, run estimate, see how time changed, repeat. Since the pi is so slow it'll take a long time for each run, and so isn't particular useful.

For large files on Pi, a simple work around is enabling a swap file.

At some point estimation mode could definitely be improved to aggregate incrementally, the dataset in memory should still be reasonably small.

Best regards,
Lasse

[dalegaard]

I just released a v1.1.0 where estimate now runs in constant space. This should allow it to work on the Raspberry Pi as well, but of course it'll still probably be a bit slow :-)

Best regards,
Lasse