There have been many prior posts about this topic. Maybe we should add a FAQ page we can direct people to. In the mean time, your best bet is to search (or use FastAnonymous or NumericFuns).
--Tim On Wednesday, March 25, 2015 11:41:10 AM Phil Tomson 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
