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Finding adequate solver settings is not a trivial task. I.e. given some accuracy, which combination of the number of axial cells, absolute/relative tolerances etc. is optimal s.t. computation time is minimized.
As a (naive) first step, functionality should be added to automatically create regular convergence plots (along given dimensions). However this becomes infeasible if the number of hyper parameters increases (e.g. for DG).
For this purpose, we should add a tool that automates this task. The final workflow could look something like:
Detect all hyper parameters in Process
Generate reference solution as ground truth (or use external one if provided)
Setup (integer) optimization problem
Optimize problem
Visualize results
The text was updated successfully, but these errors were encountered:
Finding adequate solver settings is not a trivial task. I.e. given some accuracy, which combination of the number of axial cells, absolute/relative tolerances etc. is optimal s.t. computation time is minimized.
As a (naive) first step, functionality should be added to automatically create regular convergence plots (along given dimensions). However this becomes infeasible if the number of hyper parameters increases (e.g. for DG).
For this purpose, we should add a tool that automates this task. The final workflow could look something like:
Process
The text was updated successfully, but these errors were encountered: