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I ran the "pyridineDensOverlap" example with the GPU and CPU versions (https://github.com/Probe-Particle/ppafm/tree/main/examples/pyridineDensOverlap). Using the same input files and comparing the results, I noticed differences in the simulated images generated. For most simulations, there is a match; but some appear quite different (e.g., df_024.png or df_029.png). What are these differences due to? I expected much more similar results. Am I missing something? Thank you
The text was updated successfully, but these errors were encountered:
The GPU version is using some faster approximations in various parts of the computation, which means that it's potentially less stable in some respects.
In this case it's a interpolation error that comes from resampling the charge density and Hartree potential to a coarser grid. If you set the grid density higher by putting pixPerAngstrome=14 (the original grid density) in the run_gpu.py script, then the rings should disappear, but this also makes the computation slower and requires significantly more memory.
I actually spotted this one before but forgot about it. We probably should fix this but I'm not sure how, because for example my laptop GPU runs out of memory if I set the grid density to that value.
We agreed that @NikoOinonen will take on the task of adding documentation explaining the areas of applicability of different methods/approximations. After that, the issue can be closed.
I ran the "pyridineDensOverlap" example with the GPU and CPU versions (https://github.com/Probe-Particle/ppafm/tree/main/examples/pyridineDensOverlap). Using the same input files and comparing the results, I noticed differences in the simulated images generated. For most simulations, there is a match; but some appear quite different (e.g., df_024.png or df_029.png). What are these differences due to? I expected much more similar results. Am I missing something? Thank you
The text was updated successfully, but these errors were encountered: