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There are places in _buildMatrix where we are recreating variables everytime we call _buildMatrix.
Creating variables is relatively expensive due to the
shape calculating using the op,
getUnit() (although it shouldn't be)
building C strings (for small problems)
I think we are recreating these variables due to our caching issues. It seems that we should be able to
keep the variable object but just explicitly tell it not to cache. For example in diffusionTerm.py we have
It seems like for those situations we should be declaring as self.coeff the first time through but then saying
self.coeff.dontCache() after declaration and then there is no need to delete. If we are running
--cache mode on then we probably want to keep self.coeff anyway and not delete it.
Imported from trac ticket #80, created by wd15 on 07-25-2006 at 16:37, last modified: 07-27-2006 at 11:33
The text was updated successfully, but these errors were encountered:
Ran a number of examples and checked if _getUnaryOp() and _getBinaryOp() are called after the first time step. Seems like the only place it was happening was in DiffusionTerm and FixedValue. These
classes now heep a copy of the variable but call dontCachMe().
There are places in _buildMatrix where we are recreating variables everytime we call _buildMatrix.
Creating variables is relatively expensive due to the
I think we are recreating these variables due to our caching issues. It seems that we should be able to
keep the variable object but just explicitly tell it not to cache. For example in diffusionTerm.py we have
and then later on we say
It seems like for those situations we should be declaring as self.coeff the first time through but then saying
self.coeff.dontCache() after declaration and then there is no need to delete. If we are running
--cache mode on then we probably want to keep self.coeff anyway and not delete it.
Imported from trac ticket #80, created by wd15 on 07-25-2006 at 16:37, last modified: 07-27-2006 at 11:33
The text was updated successfully, but these errors were encountered: