On 9/07/2020 11:05 pm, karu.pruun wrote:
I do not know what causes the difference but one of the likely issues
is that the Linux libraries have been built using optimizations that
DragonFly is missing. I do not mean optimizations as in compiler flags
(although these count as well), I mean different code paths. The
challenge is to identify which part in the whole stack is responsible
for the optimization; and then find the relevant locations in source
code; typically you are looking for #ifdef blocks in the source and
also build part of the software.
It would be very desirable to fix issues like these. Pandas and numpy
are both fundamental in the python scientific computing stack.
It has been a long time since I've built numpy or it's predecessors but
back then it's performance could be quite dependent on the way some of
the 3rd party libs (e.g. LINPACK/BLAS) were selected and/or built.
Andy
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