In the real world Monte-Carlo-Modell, the model is growing. Still relatively simple, but a full recalc takes about 1.5 seconds. This seems not very long, but when you want to do 10’000 recalcs, it starts to matter.
The model was much faster, before I added some strange formulas, joining data from different matrices. I’m sure there will be more efficient ways to do this. But before starting to optimise, it would be good to know where exactly time is spent in the recalculation of the model. In most programming language, there is a way to find out where the calculation spends its time.
My question: is there any technique to profile the model, e.g. to find out where my model spends time to recalculate?
I found some 4 year old discussions on that maybe “eclipses” cost time, as well as summary items. Is there any progress on this, e.g. is there a list of “expensive” techniques / errors. E.g. use multiple selects in the same formula with nested “and” clauses (as discussed in this post), so I would be interested to know if this might be an expensive technique.
I have discovered the Eclipse impacts performance. How much I’m not sure. I have had larger models and Eclipse seemed to impact them significantly. Generally I always clean up my eclipse so it is hard telling how much they impact my performance now. As stated for a clean model clean up Eclipse.