I think we have the answer there. You are using system BLAS and LAPACK which are likely to be much slower than OpenBLAS which is shipped with julia.
2014/1/18 Andrea Vigliotti <[email protected]> > *What do you get from versioninfo().* > > Julia Version > 0.2.0 > > Commit 05c6461 (2013-11-16 23:48 > UTC) > > Platform > Info: > > System: Linux > (x86_64-linux-gnu) > > WORD_SIZE: > 64 > > BLAS: libblas.so.3 > LAPACK: liblapack.so.3 > LIBM: libopenlibm > > > > On Saturday, 18 January 2014 11:46:29 UTC, Andreas Noack Jensen wrote: > >> What do you get from versioninfo(). >> >> >> 2014/1/18 Andrea Vigliotti <[email protected]> >> >> p.s. >>> >>> I am running: >>> - MATLAB Version: 8.1.0.604 (R2013a) >>> - Julia Version 0.2.0 (2013-11-16 23:48 UTC) >>> >>> on a DELL with Intel Core i7 and Kubuntu 13.10 >>> cheers, >>> >>> andrea >>> >>> On Friday, 17 January 2014 19:21:21 UTC, Andrea Vigliotti wrote: >>> >>>> Hi All, >>>> >>>> I was comparing the performance of Julia and Matlab in solving systems >>>> of linear equations and I got the following >>>> >>>> Matlab: >>>> >> A = randn(1000); A = A+A'+eye(1000); x = randn(1000,1); >>>> >> tic; A\x; toc >>>> Elapsed time is 0.034763 seconds. >>>> >>>> Julia: >>>> julia> A = randn(1000,1000); A = A+A'+eye(1000); x = randn(1000); >>>> >>>> julia> @time A\x; >>>> elapsed time: 0.192572124 seconds (8012424 bytes allocated) >>>> >>>> I was wondering whether there is anything I can do to improve the >>>> performances of Julia in solving this kind of problems? >>>> >>>> many thanks! >>>> andrea >>>> >>> >> >> >> -- >> Med venlig hilsen >> >> Andreas Noack Jensen >> > -- Med venlig hilsen Andreas Noack Jensen
