Here's what I get:
julia> K = randn(2500,2500);
julia> K = K' * K;
julia> @which inv(lufact(K))
inv{T<:Union(Float64,Complex{Float64},Complex{Float32},Float32),S<:Union(DenseArray{T,2},SubArray{T,2,A<:DenseArray{T,N},I<:(Union(Range{Int64},Int64)...,)})}(A::LU{T<:Union(Float64,Complex{Float64},Complex{Float32},Float32),S<:Union(DenseArray{T,2},SubArray{T,2,A<:DenseArray{T,N},I<:(Union(Range{Int64},Int64)...,)})})
at linalg/lu.jl:145
On Monday, May 19, 2014 3:25:30 AM UTC-5, Andreas Noack Jensen wrote:
>
> In generaI, I don't think most people experience that MKL is faster that
> OpenBLAS. On my MacBook, Julia with OpenBLAS and Matlab performs very
> similar on the symmetric inversion problem.
>
> Some time ago, there used to be a problem with inv falling back on a
> slower method. I should be fixed now, but maybe the difference you see is
> my fault and not OpenBLAS'. What do you see if you type
>
> @which inv(lufact(K))
>
>
> 2014-05-19 1:46 GMT+02:00 Thomas Covert <[email protected] <javascript:>>
> :
>
>> Thanks for sending that along - might go down that route once it's clear
>> that MKL would do the trick and that the fixed costs of building it myself
>> are worth it.
>>
>> Are there other mac users using the pre-built binaries that see these
>> same performance differences? Why do the mac binaries report libgfortblas
>> and liblapack when the windows and Linux binaries report libopenblas?
>>
>>
>> On Sunday, May 18, 2014, Leah Hanson <[email protected] <javascript:>>
>> wrote:
>>
>>> There are instructions in the Julia README and on Intel's website for
>>> running Julia with MKL:
>>>
>>> https://github.com/JuliaLang/julia#intel-math-kernel-libraries
>>>
>>> https://software.intel.com/en-us/articles/julia-with-intel-mkl-for-improved-performance
>>>
>>> -- Leah
>>>
>>>
>>> On Sun, May 18, 2014 at 3:59 PM, Thomas Covert <[email protected]>wrote:
>>>
>>>> Seems like the windows and Mac versions of Julia call different
>>>> blas/lapack routines. Might that be the cause? Is it possible for me to
>>>> ask julia to use a different blas/lapack?
>>>>
>>>>
>>>> On Sunday, May 18, 2014, J Luis <[email protected]> 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.
>>>>>>
>>>>>>
>>>
>
>
> --
> Med venlig hilsen
>
> Andreas Noack Jensen
>
