On Tue, 2016-08-02 at 14:07, Mauro <mauro...@runbox.com> wrote: > Oh, I see, this is in this issue: > https://github.com/JuliaLang/julia/issues/17751
It's not, after all, sorry! (a bit related though) And another wired thing, this seems to be dependent on using x^3. Running: function test0(N) r = 0.234 s = 0.0 for n = 1:N s += r^3 end s end #test0(BigInt(10)) test0(10) @time test0(1_000_000) @time test0(1_000_000) @time test0(1_000_000) gives: 0.130325 seconds (4.00 M allocations: 61.043 MB, 65.15% gc time) 0.198170 seconds (4.00 M allocations: 61.035 MB, 79.65% gc time) 0.036850 seconds (4.00 M allocations: 61.035 MB, 4.88% gc time) whereas using the 4-th power: s += r^4 gives: 0.001198 seconds (134 allocations: 7.719 KB) 0.001188 seconds (5 allocations: 176 bytes) 0.000886 seconds (5 allocations: 176 bytes) > 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) >>>>> >>>>> >>>>> >>>>> >>>>> >>>>>