Unfortunately, it is not that clear cut. In the thread I linked you can see
some discussion and timings. It is correct that OpenBLAS is faster for
large problems, but it is slower for small problems.
2014-05-22 23:17 GMT+02:00 Thomas Covert :
> By the way, switching to Homebrew and compiling a r
By the way, switching to Homebrew and compiling a recent git pull solved
the problem. Now my matrix inversions occur at MATLAB speeds or faster.
On Monday, May 19, 2014 7:58:06 AM UTC-5, Andreas Noack Jensen wrote:
>
> Thanks. Julia is calling the correct method.
>
> However, I didn't read your
Thanks. Julia is calling the correct method.
However, I didn't read your last email carefully enough. You are pointing
to the problem. The pre-build binary for Mac does not use OpenBLAS but
Apple's Accelerate which apparently is slower. I have filed an issue
https://github.com/JuliaLang/julia/iss
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},C
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
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 libg
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 Co
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 wrote:
> Funny, in a similar machine (but running Windows) I get the opposite
>
> Ma
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 M
