http://julia.readthedocs.org/en/release-0.3/manual/performance-tips/

On Sunday, July 12, 2015 at 8:33:56 PM UTC+2, Evgeni Bezus wrote:
>
> Hi all,
>
> I am a Julia novice and I am considering it as a potential alternative to 
> MATLAB.
> My field is computational nanophotonics and the main numerical technique 
> that I use involves multiple solution of the eigenvalue/eigenvector problem 
> for dense matrices with size of about 1000*1000 (more or less).
> I tried to run the following nearly equivalent code in Julia and in MATLAB:
>
> Julia code:
>
> n = 1000
> M = rand(n, n)
> F = eigfact(M)
> tic()
> for i = 1:10
>     F = eigfact(M)
> end
> toc()
>
>
> MATLAB code:
>
> n = 1000;
> M = rand(n, n);
> [D, V] = eig(M);
> tic;
> for i = 1:10
>     [D, V] = eig(M);
> end
> toc
>
> It turns out that MATLAB's eig() runs nearly 2.3 times faster than eig() 
> or eigfact() in Julia. On the machine available to me right now (relatively 
> old Core i5 laptop) the average time for MATLAB is of about 37 seconds, 
> while the mean Julia time is of about 85 seconds. I use MATLAB R2010b and 
> Julia 0.3.7 (i tried to run the code both in Juno and in a REPL session and 
> obtained nearly identical results).
>
> Is there anything that I'm doing wrong?
>
> Best regards,
> Evgeni
>

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