Another option would be to try the conda-forge rdkit. It doesn't appear to use MKL -- I think the MKL dependency for the rdkit::rdkit package is coming from the defaults::numpy dependency.
some tools for example scipy and pandas are only available as openblas > builds via pypi (pip). I believe the conda-forge recipes for these are also based on openblas. You might try installing rdkit from conda-forge in a fresh environment and see if those numpy / scipy builds work for you. -- Peter On Tue, Nov 12, 2019 at 6:48 AM Greg Landrum <greg.land...@gmail.com> wrote: > > > On Tue, Nov 12, 2019 at 2:00 PM Thomas Strunz <beginn...@hotmail.de> > wrote: > >> >> So for me this is temporary workaround but not really a permanent long >> term solution (and as far as I can tell mostly an issue of conda and >> windows and not rdkit) >> > > Yeah, it's clearly not the idea solution to the problem. And, yes, the > problem is clearly related to conda and windows. It seems that there used > to be a blog post explaining this (linked from this github issue: > https://github.com/ContinuumIO/anaconda-issues/issues/656), but the URL > no longer works and I can't find it. > If the performance difference is that dramatic on AMD CPUs, it may be > worth raising a new issue in the repo above and see if you get any kind of > response. > > -greg > > > > _______________________________________________ > Rdkit-discuss mailing list > Rdkit-discuss@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/rdkit-discuss >
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