>>>>> "sen1" == sen1 <sen1 at math.msu.edu> writes:
sen1> 3. Perhaps the ensuing discussion simply made alternate proposals
sen1> which would not have a degrading effect on the speed of the final
sen1> routines. If so, that is fine.
sen1> If not, then
sen1> I would rather see things done right (even if it takes longer to
sen1> implement).
sen1> Otherwise, I don't see the point for real utility. Serious users
sen1> will simply go to octave, python, matlab, etc. or some other tool
sen1> after possibly doing some testing in maxima.
Even without testing, I am very confident in telling you that you will
be disappointed if you are expecting these LAPACK routines to be as
fast as octave or matlab. You'll be even more disappointed if you're
doing large matrices and octave/matlab are using an optimized ATLAS
library.
In addition, I didn't even compile the code with (speed 3) (safety 0)
so there will some loss in speed anyway because there will be type
checks in many places. And the converted routines aren't using
specialized arrays, so you get hit there as well. I would guess maybe
a factor of 2(?) loss in speed compared to Fortran, and even more if
you're used to ATLAS or some other optimized BLAS package.
If all you want to do is crunch numbers, maxima may not be what you
want.
Ray