[Maxima] Maxima Lapack is very slow: 7 seconds versus 0.002 seconds in Julia.
Manuel Pedrinero rossetil
pdx7l1 at yahoo.es
Sat May 5 09:36:54 CDT 2012
Recently Raimond Toy asked about what capabilities are lacking in maxima, numeric computations in linear algebra seems to be very slow
This is an example in gcl using lapack
(%i2) h[i,j]:= 1/(i+j);
(%o2) h := -----
i, j i + j
(%i3) m : genmatrix(h,50,50)$
(%i4) showtime : true;
Evaluation took 0.0000 seconds (0.0000 elapsed)
(%i5) [one,two,three] : dgeev(m)$
Evaluation took 7.3200 seconds (7.4000 elapsed)
In Julia computing eigenvalues of a 50x50 matrix whose entries are random numbers from a normal distribution is about 0.007 seconds.
julia> @time v1,others = eig(randn(50,50));
elapsed time: 0.0070650577545166016 seconds
The same computation takes 0.002 seconds in Julia. (first make some computation
with eig so that it loads the function in memory).
to convert m to Julia format one can use system and sed
replacing "," => "space" "]" by ";" and deleting "["
the final step is to put parenthesis around the numbers (that are separated by space inside rows and ";" separate rows.
@time one,others = eig(m)
Maxima version: 5.24.0
Maxima build date: 9:11 2/29/2012
Host type: x86_64-unknown-linux-gnu
Lisp implementation type: GNU Common Lisp (GCL)
Lisp implementation version: GCL 2.6.7
I know that some efforts like matlisp are trying to improve this situation.
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