Humm, It's useful but I guess that the problem is something in loop while...
Em quarta-feira, 26 de novembro de 2014 15h05min03s UTC-2, Stefan Karpinski escreveu: > > I'm not sure if this is the problem, but changing the type of a variable > in a function body causes problems for type inference. For that reason, the > first two lines of this code may cause performance issue if you call this > with b and c as matrices. A more Julian idiom for this is to do something > like this: > > function simplex(A::Matrix, b::Vector, c::Vector) > (m,n) = size(A); > ... > end > simplex(A::Matrix, b::Matrix, c::Matrix) = simplex(A, vec(b), vec(c)) > > > This also avoids copying the data of b and c needlessly. > > On Wednesday, November 26, 2014, Emerson Vitor Castelani < > [email protected] <javascript:>> wrote: > >> Have you considered the example scsd8.mat? >> >> Em quarta-feira, 26 de novembro de 2014 14h39min14s UTC-2, Pileas >> escreveu: >>> >>> Result with tic() toc() at the very beginning and at the very end: >>> >>> elapsed time: 0.025719973 seconds >>> >>> >>> Τη Τετάρτη, 26 Νοεμβρίου 2014 11:06:26 π.μ. UTC-5, ο χρήστης Emerson >>> Vitor Castelani έγραψε: >>>> >>>> Well, I am tried to implement a simple version of simplex in Julia and >>>> I have had some troubles. In Julia, my algorithm spends about 30 sec and >>>> in >>>> matlab/octave 3 sec for the same problem. So, I saw some tips in order to >>>> get a better performance but the best that I got in Julia was 17-20 sec. >>>> The codes are in attachment. I am new in Julia and the algorithms are >>>> little roughly implemented but they are very similar. >>>> >>>> Thanks >>>> >>>> >>>>
