Hi Mahdi, The iteration numbering is based on max_refinement_levels, so you would need to adjust e.g.
CarpetRegrid2::regrid_every = 512 AHFinderDirect::find_every = 1024 and all the outputting too. The iteration count is based on the finest possible level, not the actual finest level, so, if you go from 12 to 9 max levels, you can divide all these numbers by 8 to make sure your simulation is doing everything at the equivalent intervals! I only know this because I got stuck on something related to this recently and found a short note about it here: https://einsteintoolkit.org/arrangementguide/Carpet/documentation.html (near the end of the page). Rhiannon. ________________________________ From: Users <[email protected]> on behalf of Naseri, Mahdi - (mahdinaseri) <[email protected]> Sent: 25 October 2025 01:00 To: [email protected] <[email protected]> Subject: [Users] Unexpected slowdown when increasing Carpet::max_refinement_levels (no AMR active) External email to Cardiff University - Take care when replying/opening attachments or links. Nid ebost mewnol o Brifysgol Caerdydd yw hwn - Cymerwch ofal wrth ateb/agor atodiadau neu ddolenni. Hello, I’m seeing an unexpected performance drop in Carpet (ET). I ran two simulations with identical parameter files (attached) except for: Carpet::max_refinement_levels = 9 (Run A) Carpet::max_refinement_levels = 12 (Run B) During the period I conducted this experiment, all the refinement levels were inactive except for the base level. Therefore, I expected to see the same performance in both Runs A and B, because the active grid structure is the same. However, I realized that Run B is almost 4 times slower than Run A; a plot of wall-clock time per simulation time for these two simulations is also attached for comparison. Is this behavior known/expected (e.g., due to bookkeeping, allocation, or scheduling costs that scale with the allowed number of levels), or does it suggest a configuration issue on my side? Any pointers on what to check, or how to profile this within Carpet/Cactus, to understand the overhead would be greatly appreciated. Thank you, Mahdi Naseri
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