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) >>> >>> >>> >>> >>> >>>
