recent attempt



Actually, a factor of 2 or even 3 is not so bad, considering the
convenience of not having to import, export data files in other formats.

Of course there will always be some program which handles a particular
routine better than others.

I, too, want to thank you for porting lapack.  Whatever the speed, it
will be a real plus to have it available.

-sen


On Wed, 3 Jan 2007, Raymond Toy wrote:

>>>>>> "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
>

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