Oh, I see, this is in this issue: https://github.com/JuliaLang/julia/issues/17751
On Tue, 2016-08-02 at 10:52, Mauro <mauro...@runbox.com> wrote: > Yes, test2 is slower on 0.4 (expected), test1 is slower on 0.5 (weird) > on my Linux (Intel) machine. Christoph is right, in 0.5 these should > preform the same. And certainly, no function should be 1000x slower on > 0.5 than on 0.4. > > A quick search did not turn up a bug report: > https://github.com/JuliaLang/julia/issues?q=is%3Aopen+is%3Aissue+label%3Aregression+label%3Aperformance > Please file one! > > Other weird thing is that (on 0.5) @code_warntype and @code_llvm return > both exactly the same code. However, @code_native is very short for > test2 and long for test1. > > Weirder: if I re-include the file, then both functions run fast and then > the @code_native. Or, running below file, I get equal results: > > function test1(N) > r = 0.234; s = 0.0 > for n = 1:N > s += r^3 + r^5 > end > return s > end > > > function test2(N, f1) > r = 0.234; s = 0.0 > for n = 1:N > s += f1(r) > end > return s > end > > g1(r) = r^3 + r^5 > > > test1(BigInt(10)) # <--- force one compilation for something else than Int > test1(10) # then compilation for Int produces a fast function > test2(10, g1) > @time 1 # warm-up @time itself > > println("Test1: hard-coded functions") > @time test1(1_000_000) > @time test1(1_000_000) > @time test1(1_000_000) > > println("Test2: pass functions") > @time test2(1_000_000, g1) > @time test2(1_000_000, g1) > @time test2(1_000_000, g1) > > So, it seems that the first compilation is messed up but subsequent > compilations are fine. > > On Tue, 2016-08-02 at 07:01, Eric Forgy <eric.fo...@gmail.com> wrote: >> I still don't understand the details of the new functions in v0.5. but I'd >> be inclined to think this test depends on whether you're on v0.4.6 or >> v0.5.0. >> >> On Tuesday, August 2, 2016 at 12:53:27 PM UTC+8, Greg Plowman wrote: >>> >>> I get timing/allocations the other way around. (test1, hard-coded version >>> is fast without allocation) >>> @code_warntype for test2 shows type-instability for s (because return type >>> cannot be inferred for f1) >>> >>> >>> On Tuesday, August 2, 2016 at 2:33:24 PM UTC+10, Christoph Ortner wrote: >>> >>>> Below are two tests, in the first a simple polynomial is "hard-coded", in >>>> the second it is passed as a function. I would expect the two to be >>>> equivalent, but the second case is significantly faster. Can anybody >>>> explain what is going on? @code_warntype doesn't show anything that would >>>> explain it? >>>> >>>> function test1(N) >>>> >>>> r = 0.234; s = 0.0 >>>> for n = 1:N >>>> s += r^3 + r^5 >>>> end >>>> return s >>>> end >>>> >>>> >>>> function test2(N, f1) >>>> r = 0.234; s = 0.0 >>>> for n = 1:N >>>> s += f1(r) >>>> end >>>> return s >>>> end >>>> >>>> >>>> g1(r) = r^3 + r^5 >>>> >>>> >>>> test1(10) >>>> test2(10, g1) >>>> >>>> >>>> println("Test1: hard-coded functions") >>>> @time test1(1_000_000) >>>> @time test1(1_000_000) >>>> @time test1(1_000_000) >>>> >>>> >>>> println("Test2: pass functions") >>>> @time test2(1_000_000, g1) >>>> @time test2(1_000_000, g1) >>>> @time test2(1_000_000, g1) >>>> >>>> >>>> >>>> >>>> # $ julia5 weird_test2.jl >>>> # Test1: hard-coded functions >>>> # 0.086683 seconds (4.00 M allocations: 61.043 MB, 50.75% gc time) >>>> # 0.142487 seconds (4.00 M allocations: 61.035 MB, 76.91% gc time) >>>> # 0.025388 seconds (4.00 M allocations: 61.035 MB, 4.28% gc time) >>>> # Test2: pass functions >>>> # 0.000912 seconds (5 allocations: 176 bytes) >>>> # 0.000860 seconds (5 allocations: 176 bytes) >>>> # 0.000846 seconds (5 allocations: 176 bytes) >>>> >>>> >>>> >>>> >>>> >>>>
