In addition our lu calculates a partially pivoted lu and returns the L and
U matrices and the vector of permutations. To get something comparable in
MATLAB you'll have to write
[L,,U,p] = lu(A,'vector')
On my old Mac where Julia is compiled with OpenBLAS the timings are
MATLAB:
>> tic();for i = 1:10
[L,U,p] = qr(A, 'vector');
end;toc()/10
ans =
3.4801
Julia:
julia> tic(); for i = 1:10
qr(A);
end;toc()/10
elapsed time: 14.758491472 seconds
1.4758491472
Med venlig hilsen
Andreas Noack
2014-09-18 15:33 GMT-04:00 Jason Riedy <ja...@lovesgoodfood.com>:
> And Elliot Saba writes:
> > The first thing you should do is run your code once to warm up the
> > JIT, and then run it again to measure the actual run time, rather
> > than compile time + run time.
>
> To be fair, he seems to be timing MATLAB in the same way, so he's
> comparing systems appropriately at that level.
>
> It's just the tuned BLAS+LAPACK & fftw v. the default ones. This
> is one reason why MATLAB bundles so much. (Another reason being
> the differences in numerical results causing support calls. Took
> a long time before MATLAB gave in to per-platform-tuned libraries.)
>
>
