Milan Script is here: https://gist.github.com/musmo/27436a340b41c01d51d557a655276783
On Sunday, May 8, 2016 at 12:40:44 PM UTC-4, feza wrote: > > Thanks for the tip (initially I just transllated the matlab verbatim) > > Now I have made all the changes. In place operations, and direct function > calls. > Despite these changes. Matlab is 3.6 seconds, new Julia 7.6 seconds > TBH the results of this experiment are frustrating, I was hoping Julia was > going to provide a huge speedup (on the level of c) > > Am I still missing anything in the Julia code that is crucial to speed? > @code_warntype looks ok sans a few red unions which i don't think are in > my control > > > On Sunday, May 8, 2016 at 8:15:25 AM UTC-4, Tim Holy wrote: >> >> One of the really cool features of julia is that functions are allowed to >> have >> more than 0 arguments. It's even considered good style, and I highly >> recommend >> making use of this awesome feature in your code! :-) >> >> In other words: try passing all variables as arguments to the functions. >> Even >> though you're wrapping everything in a function, performance-wise you're >> running up against an inference problem >> (https://github.com/JuliaLang/julia/issues/15276). In terms of coding >> style, >> you're still essentially using global variables. Honestly, these make >> your >> life harder in the end ( >> http://c2.com/cgi/wiki?GlobalVariablesAreBad)---it's >> not a bad thing that julia provides gentle encouragement to avoid using >> them, >> and you're losing out on opportunities by trying to sidestep that >> encouragement. >> >> Best, >> --Tim >> >> On Sunday, May 08, 2016 01:38:41 AM feza wrote: >> > That's no surprise your CPU is better :) >> > >> > Regarding devectorization >> > for l in 1:q >> > for k in 1:nz >> > for j in 1:ny >> > for i in 1:nx >> > u = ux[i,j,k] >> > v = uy[i,j,k] >> > w = uz[i,j,k] >> > >> > cu = c[k,1]*u + c[k,2]*v + c[k,3]*w >> > u2 = u*u + v*v + w*w >> > feq[i,j,k,l] = weights[k]*ρ[i,j,k]*(1 + 3*cu + >> 9/2*(cu*cu) >> > - 3/2*u2) >> > f[i,j,k,l] = f[i,j,k,l]*(1-ω) + ω*feq[i,j,k,l] >> > end >> > end >> > end >> > end >> > >> > Actually makes the code a lot slower.... >> > >> > On Sunday, May 8, 2016 at 4:37:18 AM UTC-4, Patrick Kofod Mogensen >> wrote: >> > > For what it's worth it run in about 3-4 seconds on my computer on >> latest >> > > v0.4. >> > > >> > > CPU : Intel(R) Core(TM) i7-4600U CPU @ 2.10GHz >> > > >> > > On Sunday, May 8, 2016 at 10:33:14 AM UTC+2, Patrick Kofod Mogensen >> wrote: >> > >> As for the v0.5 performance (which is horrible), I think it's the >> boxing >> > >> issue with closure https://github.com/JuliaLang/julia/issues/15276 >> . >> > >> Right? >> > >> >> > >> On Sunday, May 8, 2016 at 10:29:59 AM UTC+2, STAR0SS wrote: >> > >>> You are using a lot of vectorized operations and Julia isn't as >> good as >> > >>> matlab is with those. >> > >>> >> > >>> The usual solution is to devectorized your code and to use loops >> (except >> > >>> for matrix multiplication if you have large matrices). >> >>
