Because not so many may have Matlab installed on Linux,
here are my votes:
Matlab: 1.59 sec
Julia: 0.92 sec
julia> versioninfo()
Julia Version 0.3.0-prerelease+2985
Commit 645c696 (2014-05-10 17:14 UTC)
Platform Info:
System: Linux (x86_64-linux-gnu)
CPU: Intel(R) Core(TM) i3-3217U CPU @ 1.80GHz
WORD_SIZE: 64
BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY)
LAPACK: libopenblas
LIBM: libopenlibm
On Sunday, May 18, 2014 8:38:11 PM UTC+2, J Luis wrote:
>
> Funny, in a similar machine (but running Windows) I get the opposite
>
> Matlab 2012a (32 bits)
> >> tic; inv(K); toc
> Elapsed time is 3.837033 seconds.
>
>
> julia> tic(); inv(K); toc()
> elapsed time: 1.157727675 seconds
> 1.157727675
>
> julia> versioninfo()
> Julia Version 0.3.0-prerelease+3081
> Commit eb4bfcc* (2014-05-16 15:12 UTC)
> Platform Info:
> System: Windows (x86_64-w64-mingw32)
> CPU: Intel(R) Core(TM) i7 CPU M 620 @ 2.67GHz
> WORD_SIZE: 64
> BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY)
> LAPACK: libopenblas
> LIBM: libopenlibm
>
> Domingo, 18 de Maio de 2014 19:16:48 UTC+1, Thomas Covert escreveu:
>>
>> I am finding that MATLAB is considerably faster than Julia for simple
>> linear algebra work on my machine (mid-2009 macbook pro). Why might this
>> be? Is this an OpenBLAS vs Intel MKL issue?
>>
>> For example, on my machine, matrix inversion of a random, symmetric
>> matrix is more than twice as fast in MATLAB as it is in Julia:
>>
>> MATLAB code:
>> K = randn(2500,2500);
>> K = K' * K;
>> tic; inv(K); toc
>> Elapsed time is 2.182241 seconds.
>>
>> Julia code:
>> K = convert(Array{Float32},randn(2500,2500));
>> K = K' * K;
>> tic(); inv(K); toc()
>> elapsed time: 6.249259727 seconds
>>
>> I'm running a fairly recent MATLAB release (2014a), and versioninfo() in
>> my Julia install reads:
>> Julia Version 0.3.0-prerelease+2918
>> Commit 104568c* (2014-05-06 22:29 UTC)
>> Platform Info:
>> System: Darwin (x86_64-apple-darwin12.5.0)
>> CPU: Intel(R) Core(TM)2 Duo CPU P8700 @ 2.53GHz
>> WORD_SIZE: 64
>> BLAS: libgfortblas
>> LAPACK: liblapack
>> LIBM: libopenlibm
>>
>> Any advice is much appreciated.
>>
>>
