Setup OpaqueClosures norecompile mode #745
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The opaque closure version is faster? using OrdinaryDiffEq, BenchmarkTools
function f(du, u, p, t)
du[1] = 0.2u[1]
du[2] = 0.4u[2]
end
u0 = ones(2)
tspan = (0.0, 1.0)
prob = ODEProblem{true,false}(f, u0, tspan, Float64[])
prob2 = ODEProblem(lorenz, [1.0; 0.0; 0.0], (0.0, 1.0), Float64[])
alg1 = Rosenbrock23(autodiff=false)
alg2 = Rosenbrock23(chunk_size=1)
@benchmark sol = $solve($prob, $alg1)
@benchmark sol = $solve($prob2, $alg1)
@benchmark sol = $solve($prob, $alg2)
@benchmark sol = $solve($prob2, $alg2)julia> @benchmark sol = $solve($prob, $alg1)
BenchmarkTools.Trial: 10000 samples with 1 evaluation.
Range (min … max): 17.900 μs … 8.254 ms ┊ GC (min … max): 0.00% … 99.25%
Time (median): 20.100 μs ┊ GC (median): 0.00%
Time (mean ± σ): 23.709 μs ± 132.326 μs ┊ GC (mean ± σ): 9.58% ± 1.72%
▁▁█▃▇▁▂
▁▂▃████████▅▇▄▅▃▄▃▃▃▂▃▂▂▂▂▂▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ ▂
17.9 μs Histogram: frequency by time 33.2 μs <
Memory estimate: 21.72 KiB, allocs estimate: 502.
julia> @benchmark sol = $solve($prob2, $alg1)
BenchmarkTools.Trial: 10000 samples with 1 evaluation.
Range (min … max): 89.400 μs … 7.018 ms ┊ GC (min … max): 0.00% … 98.08%
Time (median): 94.400 μs ┊ GC (median): 0.00%
Time (mean ± σ): 102.397 μs ± 160.294 μs ┊ GC (mean ± σ): 3.78% ± 2.40%
▅██▇▅▅▄▃▂▁▁ ▂
████████████▇▇█▇▆▇▆▆▅▄▆▅▄▅▄▃▆▅▅▄▅▅▅▁▄▄▅▄▄▃▁▁▆▄▄▅▅▄▅▆▆▅▆▅▆▅▁▄▅ █
89.4 μs Histogram: log(frequency) by time 212 μs <
Memory estimate: 49.11 KiB, allocs estimate: 1207.
julia> @benchmark sol = $solve($prob, $alg2)
BenchmarkTools.Trial: 10000 samples with 1 evaluation.
Range (min … max): 13.100 μs … 7.901 ms ┊ GC (min … max): 0.00% … 99.29%
Time (median): 15.600 μs ┊ GC (median): 0.00%
Time (mean ± σ): 19.110 μs ± 131.043 μs ┊ GC (mean ± σ): 11.79% ± 1.72%
▄▂█▂▆▁▃ ▁
▁▂▄▅███████▆█▅▇▄▇▄▅▄▅▃▃▂▃▂▂▂▂▂▂▂▁▂▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ ▂
13.1 μs Histogram: frequency by time 28 μs <
Memory estimate: 24.81 KiB, allocs estimate: 419.
julia> @benchmark sol = $solve($prob2, $alg2)
BenchmarkTools.Trial: 10000 samples with 1 evaluation.
Range (min … max): 48.000 μs … 5.135 ms ┊ GC (min … max): 0.00% … 98.20%
Time (median): 50.800 μs ┊ GC (median): 0.00%
Time (mean ± σ): 58.643 μs ± 143.606 μs ┊ GC (mean ± σ): 7.26% ± 2.95%
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▇██▄▃▃▃▃▃▃▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▂▂▁▂▂▁▂▂▂▁▁▁▁▁▂▂▁▁▁▁▂▂ ▂
48 μs Histogram: frequency by time 131 μs <
Memory estimate: 66.72 KiB, allocs estimate: 651. |
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The MWE is "working": using OrdinaryDiffEq
function f(du, u, p, t)
du[1] = 0.2u[1]
du[2] = 0.4u[2]
end
u0 = ones(2)
tspan = (0.0, 1.0)
prob = ODEProblem{true,false}(f, u0, tspan, Float64[])
function lorenz(du, u, p, t)
du[1] = 10.0(u[2] - u[1])
du[2] = u[1] * (28.0 - u[3]) - u[2]
du[3] = u[1] * u[2] - (8 / 3) * u[3]
end
lorenzprob = ODEProblem{true,false}(lorenz, [1.0; 0.0; 0.0], (0.0, 1.0), Float64[])
typeof(prob) === typeof(lorenzprob) # true
@time sol = solve(prob, Rosenbrock23(autodiff=false))
@time sol = solve(prob, Rosenbrock23(chunk_size=1))but the precompilation doesn't remove compilation time: 1.391319 seconds (5.64 M allocations: 309.916 MiB, 4.14% gc time, 99.88% compilation time)
1.240713 seconds (3.85 M allocations: 216.374 MiB, 3.14% gc time, 99.98% compilation time) |
using OrdinaryDiffEq
function f(du, u, p, t)
du[1] = 0.2u[1]
du[2] = 0.4u[2]
end
u0 = ones(2)
tspan = (0.0, 1.0)
prob = ODEProblem{true,false}(f, u0, tspan, Float64[])
function lorenz(du, u, p, t)
du[1] = 10.0(u[2] - u[1])
du[2] = u[1] * (28.0 - u[3]) - u[2]
du[3] = u[1] * u[2] - (8 / 3) * u[3]
end
lorenzprob = ODEProblem{true,false}(lorenz, [1.0; 0.0; 0.0], (0.0, 1.0), Float64[])
typeof(prob) === typeof(lorenzprob) # true
using Profile
@profile sol = solve(prob, Rosenbrock23(autodiff=false))
@profile sol = solve(prob, Rosenbrock23(chunk_size=1)) |
using OrdinaryDiffEq, SnoopCompile
function f(du, u, p, t)
du[1] = 0.2u[1]
du[2] = 0.4u[2]
end
u0 = ones(2)
tspan = (0.0, 1.0)
prob = ODEProblem{true,false}(f, u0, tspan, Float64[])
function lorenz(du, u, p, t)
du[1] = 10.0(u[2] - u[1])
du[2] = u[1] * (28.0 - u[3]) - u[2]
du[3] = u[1] * u[2] - (8 / 3) * u[3]
end
lorenzprob = ODEProblem{true,false}(lorenz, [1.0; 0.0; 0.0], (0.0, 1.0), Float64[])
typeof(prob) === typeof(lorenzprob) # true
alg = Rosenbrock23(chunk_size=1)
@snoopi_deep sol = solve(prob, alg)
InferenceTimingNode: 0.923631/1.610302 on Core.Compiler.Timings.ROOT() with 36 direct children |
Needs: - SciML/SciMLBase.jl#143 - SciML/OrdinaryDiffEq.jl#1627 ```julia using OrdinaryDiffEq function f(du, u, p, t) du[1] = 0.2u[1] du[2] = 0.4u[2] end u0 = ones(2) tspan = (0.0, 1.0) prob = ODEProblem{true,false}(f, u0, tspan, Float64[]) function lorenz(du, u, p, t) du[1] = 10.0(u[2] - u[1]) du[2] = u[1] * (28.0 - u[3]) - u[2] du[3] = u[1] * u[2] - (8 / 3) * u[3] end lorenzprob = ODEProblem{true,false}(lorenz, [1.0; 0.0; 0.0], (0.0, 1.0), Float64[]) typeof(prob) === typeof(lorenzprob) # true @time sol = solve(prob, Rosenbrock23(autodiff=false)) @time sol = solve(prob, Rosenbrock23(chunk_size=1)) ``` ``` 2.763588 seconds (10.32 M allocations: 648.718 MiB, 4.92% gc time, 99.89% compilation time) 10.577789 seconds (45.44 M allocations: 2.760 GiB, 4.87% gc time, 99.97% compilation time) ``` While the types of `prob` are exactly the same, there is still a significant amount of compile time, even with that exact same time being called in `using` at OrdinaryDiffEq. Maybe this needs to be run on master?
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Does not play nicely with SnoopPrecompile [ Info: Precompiling OrdinaryDiffEq [1dea7af3-3e70-54e6-95c3-0bf5283fa5ed]
fatal: error thrown and no exception handler available.
ErrorException("unimplemented: serialization of MethodInstances for OpaqueClosure")
ijl_error at /cygdrive/c/buildbot/worker/package_win64/build/src\rtutils.c:41
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:852
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:649 [inlined]
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:665
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:649 [inlined]
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:824
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:649 [inlined]
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:820
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:649 [inlined]
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:872
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:649 [inlined]
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:704
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:649 [inlined]
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:893
jl_serialize_value_ at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:1073 [inlined]
serialize_htable_keys at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:1075 [inlined]
ijl_save_incremental at /cygdrive/c/buildbot/worker/package_win64/build/src\dump.c:2686
jl_write_compiler_output at /cygdrive/c/buildbot/worker/package_win64/build/src\precompile.c:65
ijl_atexit_hook at /cygdrive/c/buildbot/worker/package_win64/build/src\init.c:207
jl_repl_entrypoint at /cygdrive/c/buildbot/worker/package_win64/build/src\jlapi.c:712
mainCRTStartup at /cygdrive/c/buildbot/worker/package_win64/build/cli\loader_exe.c:59
BaseThreadInitThunk at C:\WINDOWS\System32\KERNEL32.DLL (unknown line)
RtlUserThreadStart at C:\WINDOWS\SYSTEM32\ntdll.dll (unknown line)
ERROR: Failed to precompile OrdinaryDiffEq [1dea7af3-3e70-54e6-95c3-0bf5283fa5ed] to C:\Users\accou\.julia\compiled\v1.8\OrdinaryDiffEq\jl_B4DB.tmp.
Stacktrace:
[1] error(s::String)
@ Base .\error.jl:35
[2] compilecache(pkg::Base.PkgId, path::String, internal_stderr::IO, internal_stdout::IO, ignore_loaded_modules::Bool)
@ Base .\loading.jl:1558
[3] compilecache
@ .\loading.jl:1502 [inlined]
[4] _require(pkg::Base.PkgId)
@ Base .\loading.jl:1203
[5] _require_prelocked(uuidkey::Base.PkgId)
@ Base .\loading.jl:1091
[6] macro expansion
@ .\loading.jl:1071 [inlined]
[7] macro expansion
@ .\lock.jl:223 [inlined]
[8] require(into::Module, mod::Symbol)
@ Base .\loading.jl:1035
[9] eval
@ .\boot.jl:368 [inlined]
[10] include_string(mapexpr::typeof(REPL.softscope), mod::Module, code::String, filename::String)
@ Base .\loading.jl:1281
[11] invokelatest(::Any, ::Any, ::Vararg{Any}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ Base .\essentials.jl:729
[12] invokelatest(::Any, ::Any, ::Vararg{Any})
@ Base .\essentials.jl:726
[13] inlineeval(m::Module, code::String, code_line::Int64, code_column::Int64, file::String; softscope::Bool)
@ VSCodeServer c:\Users\accou\.vscode\extensions\julialang.language-julia-1.6.31\scripts\packages\VSCodeServer\src\eval.jl:233
[14] (::VSCodeServer.var"#66#70"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})()
@ VSCodeServer c:\Users\accou\.vscode\extensions\julialang.language-julia-1.6.31\scripts\packages\VSCodeServer\src\eval.jl:157
[15] withpath(f::VSCodeServer.var"#66#70"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams}, path::String)
@ VSCodeServer c:\Users\accou\.vscode\extensions\julialang.language-julia-1.6.31\scripts\packages\VSCodeServer\src\repl.jl:249
[16] (::VSCodeServer.var"#65#69"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})()
@ VSCodeServer c:\Users\accou\.vscode\extensions\julialang.language-julia-1.6.31\scripts\packages\VSCodeServer\src\eval.jl:155
[17] hideprompt(f::VSCodeServer.var"#65#69"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})
@ VSCodeServer c:\Users\accou\.vscode\extensions\julialang.language-julia-1.6.31\scripts\packages\VSCodeServer\src\repl.jl:38
[18] (::VSCodeServer.var"#64#68"{Bool, Bool, Bool, Module, String, Int64, Int64, String, VSCodeServer.ReplRunCodeRequestParams})()
@ VSCodeServer c:\Users\accou\.vscode\extensions\julialang.language-julia-1.6.31\scripts\packages\VSCodeServer\src\eval.jl:126
[19] with_logstate(f::Function, logstate::Any)
@ Base.CoreLogging .\logging.jl:511
[20] with_logger
@ .\logging.jl:623 [inlined]
[21] (::VSCodeServer.var"#63#67"{VSCodeServer.ReplRunCodeRequestParams})()
@ VSCodeServer c:\Users\accou\.vscode\extensions\julialang.language-julia-1.6.31\scripts\packages\VSCodeServer\src\eval.jl:225
[22] #invokelatest#2
@ .\essentials.jl:729 [inlined]
[23] invokelatest(::Any)
@ Base .\essentials.jl:726
[24] macro expansion
@ c:\Users\accou\.vscode\extensions\julialang.language-julia-1.6.31\scripts\packages\VSCodeServer\src\eval.jl:34 [inlined]
[25] (::VSCodeServer.var"#61#62")()
@ VSCodeServer .\task.jl:482 |
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This is a continuation of #736 instead using OpaqueClosures. As such, it also requires:
But now the MWE doesn't run:
The precompilation from SciML/OrdinaryDiffEq.jl#1627 seems to not work with opaque closures. Do they not support precompilation? @Keno