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New EB optimization parameter: eb2.num_coarsen_opt (AMReX-Codes#2872)
At the beginning of EB generation, we chop the entire finest domain into boxes and find out the type of the boxes. We then collect the completely covered boxes and cut boxes into two BoxArrays. This process can be costly because of the number of calls to the implicit functions. In this commit, we have introduced a new ParmParse parameter, eb2.num_coarsen_opt with a default value of zero. If for instance it is set to 3, we start the box type categorization at a resolution that is coarsened by a factor of 2^3. For the provisional cut boxes, we refine them by a factor of 2, Then we chop them into small boxes and categorize the new boxes. This process is performed recursively until we are at the original finest resolution. The users should be aware that, if eb2.num_coaren_opt is too big, this could produce in erroneous results because evaluating the implicit function on coarse boxes could miss fine structures in the EB. Thank Robert Marskar for sharing this algorithm.
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