If you can reduce this to a standalone, runnable test case that uses only code from Base, it would be helpful to file an issue.
--Tim On Saturday, January 17, 2015 05:36:36 PM Arch Call wrote: > Give alg=MergeSort a whirl. The doc says this is slower than alg=QuickSort > for numeric arrays, but who knows until you try. > > On Saturday, January 17, 2015 at 4:57:20 PM UTC-5, Petr Krysl wrote: > > Hi guys, > > > > This one has me scratching my head. > > > > Matlab code: > > > > function Out =myunique(A) > > > > sA=sort(A,2); > > [sA,rix] = sortrows(sA);; > > d=sA(1:end-1,:)~=sA(2:end,:); > > ad=[true; any(d,2)]; > > iu =find((ad&[ad(2:end);true])==true); > > Out =A(rix(iu),:); > > > > end > > > > was rewritten in Julia. Since some of the functionality is different (or > > slower) as written, I had to rewrite a bit. The surprise was that even > > after the rewrite the Julia code runs in around 24 seconds whereas the > > Matlab code gets it done in two seconds. As I went poking around to find > > what is slow, I found that 95% of the time were spent in the sort() and > > sortrrows() functions. > > > > Any idea of what could cause this slowness? By the way, @code_warntype > > gives the code a clean bill... So are those two functions somehow slow by > > themselves? > > > > The Julia version of this is posted at > > https://gist.github.com/PetrKryslUCSD/cde67dfa0f1b0a1f98ac > > > > Thanks, > > > > Petr
