On Wednesday, March 25, 2015 at 12:34:47 PM UTC-7, Mauro wrote: > > This is a known limitation of Julia. The trouble is that Julia cannot > do its type interference with the passed in function. I don't have time > to search for the relevant issues but you should be able to find them. > Similarly, lambdas also suffer from this. Hopefully this will be > resolved soon! >
Mauro: When you say "Hopefully this will be resolved soon! " does that mean this is an issue with a planned future fix? For those of us used to programming in a very functional style, this limitation leads to less performant code in Julia. > On Wed, 2015-03-25 at 19:41, Phil Tomson <philt...@gmail.com <javascript:>> > wrote: > > Maybe this is just obvious, but it's not making much sense to me. > > > > If I have a reference to a function (pardon if that's not the correct > > Julia-ish terminology - basically just a variable that holds a Function > > type) and call it, it runs much more slowly (persumably because it's > > allocating a lot more memory) than it would if I make the same call with > > > the function directly. > > > > Maybe that's not so clear, so let me show an example using the abs > function: > > > > function test_time() > > sum = 1.0 > > for i in 1:1000000 > > sum += abs(sum) > > end > > sum > > end > > > > Run it a few times with @time: > > > > julia> @time test_time() > > elapsed time: 0.007576883 seconds (96 bytes allocated) > > Inf > > > > julia> @time test_time() > > elapsed time: 0.002058207 seconds (96 bytes allocated) > > Inf > > > > julia> @time test_time() > > elapsed time: 0.005015882 seconds (96 bytes allocated) > > Inf > > > > Now let's try a modified version that takes a Function on the input: > > > > function test_time(func::Function) > > sum = 1.0 > > for i in 1:1000000 > > sum += func(sum) > > end > > sum > > end > > > > So essentially the same function, but this time the function is passed > in. > > Running this version a few times: > > > > julia> @time test_time(abs) > > elapsed time: 0.066612994 seconds (32000080 bytes allocated, 31.05% > > gc time) > > Inf > > > > julia> @time test_time(abs) > > elapsed time: 0.064705561 seconds (32000080 bytes allocated, 31.16% > gc > > time) > > Inf > > > > So roughly 10X slower, probably because of the much larger amount of > memory > > allocated (32000080 bytes vs. 96 bytes) > > > > Why does the second version allocate so much more memory? (I'm running > > Julia 0.3.6 for this testcase) > > > > Phil > >
