Non-essential code runs during initialization

[ctessum]

Describe the bug 🐞

I'm working on a system that involves reading large amounts of data from files and then interpolating them while the system is being solved. An example is here. The files tend to have a lot of different variables, and depending on the specific context they're being used in, we usually only actually need a small subset of the variables. However, which subset of variables is needed depends on the case.

Here is a simplified version of how it works:

using ModelingToolkit
t = ModelingToolkit.t_nounits
D = ModelingToolkit.D_nounits
using OrdinaryDiffEqTsit5

@variables v1(t)=1
@variables v2(t) [guess=0]

mutable struct Data
    name
    data
    count
end
function update!(d::Data, t)
    @info "updating $(d.name) at t=$t"
    d.data = ones(10000) # Updating the data is expensive.
    d.count += 1 # Count the number of times the data gets updated.
end
function (d::Data)(t)
    update!(d, t)
    rand(d.data)
end
@register_symbolic update!(d::Data)

@parameters (d1::Data)(..) = Data(:data1, [], 0)
@parameters (d2::Data)(..) = Data(:data2, [], 0)

eqs = [
    D(v1) ~ d1(t),
    v2 ~ d2(t), # Some of the data parameters are not actually needed to solve the system.
]

@mtkbuild sys = System(eqs, t)

In the code above, we have two data loaders, which have an update! function which is run whenever the data loaders are asked to return data. One of the data loaders (d1) is needed to solve the system, and the other one (d2) is not needed. In this case we know which one is needed and which one is not, but in the actual case this is derived from we don't necessarily know that.

This is what happens when we solve the system:

prob = ODEProblem(sys, [], (0.0, 1.0))

sol = solve(prob, Tsit5())

# Data 1 gets updated every time the ODE function is called, which is as expected.
sol.ps[d1].count # = 9

# Data 2 appears to be only updated during initialization, but it shouldn't be
# necessary to initialize variables and parameters that are never used afterward.
sol.ps[d2].count # = 3

When we solve the problem, d1 gets evaluated 9 times, one for each evaluation of the ODE function. This is fine.

The issue is that d2 also gets evaluated 3 times, all of which appear to be occurring during initialization. This is not a huge problem in the toy problem shown here, but in the real case there are a lot of d2s and they are all expensive in terms of memory and compute, so those three evaluations cause a lot of headaches.

Since it can be proven that evaluating d2 is not actually necessary to solve the problem, is it possible to get it from three evaluations down to zero?

Output from creating and solving ODEProblem

[ Info: updating data2 at t=0.0
ODEProblem with uType Vector{Float64} and tType Float64. In-place: true
Initialization status: FULLY_DETERMINED
Non-trivial mass matrix: false
timespan: (0.0, 1.0)
u0: 1-element Vector{Float64}:
 1.0

[ Info: updating data2 at t=0.0
[ Info: updating data2 at t=0.0
[ Info: updating data1 at t=0.0
[ Info: updating data1 at t=0.0
[ Info: updating data1 at t=0.01
[ Info: updating data1 at t=0.161
[ Info: updating data1 at t=0.327
[ Info: updating data1 at t=0.9
[ Info: updating data1 at t=0.9800255409045097
[ Info: updating data1 at t=1.0
[ Info: updating data1 at t=1.0
retcode: Success
Interpolation: specialized 4th order "free" interpolation
t: 2-element Vector{Float64}:
 0.0
 1.0
u: 2-element Vector{Vector{Float64}}:
 [1.0]
 [1.9999999999999998]

Environment (please complete the following information):

• Output of using Pkg; Pkg.status()

  [961ee093] ModelingToolkit v10.2.0
  [b1df2697] OrdinaryDiffEqTsit5 v1.1.0

• Output of using Pkg; Pkg.status(; mode = PKGMODE_MANIFEST)

 [47edcb42] ADTypes v1.14.0
  [1520ce14] AbstractTrees v0.4.5
  [7d9f7c33] Accessors v0.1.42
  [79e6a3ab] Adapt v4.3.0
  [66dad0bd] AliasTables v1.1.3
  [ec485272] ArnoldiMethod v0.4.0
  [4fba245c] ArrayInterface v7.19.0
  [4c555306] ArrayLayouts v1.11.1
⌅ [e2ed5e7c] Bijections v0.1.10
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [8e7c35d0] BlockArrays v1.6.3
  [70df07ce] BracketingNonlinearSolve v1.3.0
  [2a0fbf3d] CPUSummary v0.2.6
  [d360d2e6] ChainRulesCore v1.25.1
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [861a8166] Combinatorics v1.0.3
  [a80b9123] CommonMark v0.9.1
  [38540f10] CommonSolve v0.2.4
  [bbf7d656] CommonSubexpressions v0.3.1
  [f70d9fcc] CommonWorldInvalidations v1.0.0
  [34da2185] Compat v4.16.0
  [b152e2b5] CompositeTypes v0.1.4
  [a33af91c] CompositionsBase v0.1.2
  [2569d6c7] ConcreteStructs v0.2.3
  [187b0558] ConstructionBase v1.5.8
  [adafc99b] CpuId v0.3.1
  [a8cc5b0e] Crayons v4.1.1
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.18.22
  [e2d170a0] DataValueInterfaces v1.0.0
  [2b5f629d] DiffEqBase v6.175.0
  [459566f4] DiffEqCallbacks v4.6.0
  [77a26b50] DiffEqNoiseProcess v5.24.1
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
⌅ [a0c0ee7d] DifferentiationInterface v0.6.54
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  [a4df4552] FastPower v1.1.2
  [1a297f60] FillArrays v1.13.0
  [64ca27bc] FindFirstFunctions v1.4.1
  [6a86dc24] FiniteDiff v2.27.0
  [1fa38f19] Format v1.3.7
⌅ [f6369f11] ForwardDiff v0.10.38
  [069b7b12] FunctionWrappers v1.1.3
  [77dc65aa] FunctionWrappersWrappers v0.1.3
  [d9f16b24] Functors v0.5.2
  [46192b85] GPUArraysCore v0.2.0
  [c27321d9] Glob v1.3.1
  [86223c79] Graphs v1.13.0
  [34004b35] HypergeometricFunctions v0.3.28
  [615f187c] IfElse v0.1.1
  [3263718b] ImplicitDiscreteSolve v0.1.2
  [d25df0c9] Inflate v0.1.5
  [18e54dd8] IntegerMathUtils v0.1.2
  [8197267c] IntervalSets v0.7.11
  [3587e190] InverseFunctions v0.1.17
  [92d709cd] IrrationalConstants v0.2.4
  [82899510] IteratorInterfaceExtensions v1.0.0
  [692b3bcd] JLLWrappers v1.7.0
  [ae98c720] Jieko v0.2.1
  [98e50ef6] JuliaFormatter v2.1.2
⌅ [70703baa] JuliaSyntax v0.4.10
  [ccbc3e58] JumpProcesses v9.16.0
  [ba0b0d4f] Krylov v0.10.1
  [b964fa9f] LaTeXStrings v1.4.0
  [23fbe1c1] Latexify v0.16.8
  [10f19ff3] LayoutPointers v0.1.17
  [5078a376] LazyArrays v2.6.1
  [87fe0de2] LineSearch v0.1.4
  [d3d80556] LineSearches v7.3.0
  [7ed4a6bd] LinearSolve v3.17.0
  [2ab3a3ac] LogExpFunctions v0.3.29
  [d8e11817] MLStyle v0.4.17
  [1914dd2f] MacroTools v0.5.16
  [d125e4d3] ManualMemory v0.1.8
  [bb5d69b7] MaybeInplace v0.1.4
  [e1d29d7a] Missings v1.2.0
  [961ee093] ModelingToolkit v10.2.0
  [2e0e35c7] Moshi v0.3.5
  [46d2c3a1] MuladdMacro v0.2.4
  [102ac46a] MultivariatePolynomials v0.5.9
  [d8a4904e] MutableArithmetics v1.6.4
  [d41bc354] NLSolversBase v7.10.0
  [77ba4419] NaNMath v1.1.3
  [8913a72c] NonlinearSolve v4.9.0
  [be0214bd] NonlinearSolveBase v1.12.0
  [5959db7a] NonlinearSolveFirstOrder v1.5.0
  [9a2c21bd] NonlinearSolveQuasiNewton v1.6.0
  [26075421] NonlinearSolveSpectralMethods v1.2.0
  [6fe1bfb0] OffsetArrays v1.17.0
  [429524aa] Optim v1.12.0
  [bac558e1] OrderedCollections v1.8.1
  [bbf590c4] OrdinaryDiffEqCore v1.26.0
  [b1df2697] OrdinaryDiffEqTsit5 v1.1.0
  [90014a1f] PDMats v0.11.35
  [d96e819e] Parameters v0.12.3
  [e409e4f3] PoissonRandom v0.4.4
  [f517fe37] Polyester v0.7.18
  [1d0040c9] PolyesterWeave v0.2.2
  [85a6dd25] PositiveFactorizations v0.2.4
⌅ [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.4.3
  [08abe8d2] PrettyTables v2.4.0
  [27ebfcd6] Primes v0.5.7
  [43287f4e] PtrArrays v1.3.0
  [1fd47b50] QuadGK v2.11.2
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  [e6cf234a] RandomNumbers v1.6.0
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  [189a3867] Reexport v1.2.2
  [ae029012] Requires v1.3.1
  [ae5879a3] ResettableStacks v1.1.1
  [79098fc4] Rmath v0.8.0
  [7e49a35a] RuntimeGeneratedFunctions v0.5.15
  [9dfe8606] SCCNonlinearSolve v1.2.0
  [94e857df] SIMDTypes v0.1.0
  [0bca4576] SciMLBase v2.99.0
  [19f34311] SciMLJacobianOperators v0.1.6
  [c0aeaf25] SciMLOperators v1.3.1
  [431bcebd] SciMLPublic v1.0.0
  [53ae85a6] SciMLStructures v1.7.0
  [efcf1570] Setfield v1.1.2
  [727e6d20] SimpleNonlinearSolve v2.5.0
  [699a6c99] SimpleTraits v0.9.4
  [ce78b400] SimpleUnPack v1.1.0
  [a2af1166] SortingAlgorithms v1.2.1
  [0a514795] SparseMatrixColorings v0.4.20
  [276daf66] SpecialFunctions v2.5.1
  [aedffcd0] Static v1.2.0
  [0d7ed370] StaticArrayInterface v1.8.0
  [90137ffa] StaticArrays v1.9.13
  [1e83bf80] StaticArraysCore v1.4.3
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.7.1
  [2913bbd2] StatsBase v0.34.5
  [4c63d2b9] StatsFuns v1.5.0
  [7792a7ef] StrideArraysCore v0.5.7
  [892a3eda] StringManipulation v0.4.1
  [2efcf032] SymbolicIndexingInterface v0.3.40
  [19f23fe9] SymbolicLimits v0.2.2
  [d1185830] SymbolicUtils v3.29.0
  [0c5d862f] Symbolics v6.40.0
  [3783bdb8] TableTraits v1.0.1
  [bd369af6] Tables v1.12.1
  [ed4db957] TaskLocalValues v0.1.2
  [8ea1fca8] TermInterface v2.0.0
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  [5c2747f8] URIs v1.5.2
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  [856f044c] MKL_jll v2025.0.1+1
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
  [f50d1b31] Rmath_jll v0.5.1+0
  [1317d2d5] oneTBB_jll v2022.0.0+0
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [ade2ca70] Dates v1.11.0
  [8ba89e20] Distributed v1.11.0
  [f43a241f] Downloads v1.6.0
  [7b1f6079] FileWatching v1.11.0
  [9fa8497b] Future v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [4af54fe1] LazyArtifacts v1.11.0
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.11.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [a63ad114] Mmap v1.11.0
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.11.0
  [de0858da] Printf v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization v1.11.0
  [1a1011a3] SharedArrays v1.11.0
  [6462fe0b] Sockets v1.11.0
  [2f01184e] SparseArrays v1.11.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test v1.11.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
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  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.6+0
  [14a3606d] MozillaCACerts_jll v2023.12.12
  [4536629a] OpenBLAS_jll v0.3.27+1
  [05823500] OpenLibm_jll v0.8.5+0
  [bea87d4a] SuiteSparse_jll v7.7.0+0
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.11.0+0
  [8e850ede] nghttp2_jll v1.59.0+0
  [3f19e933] p7zip_jll v17.4.0+2

• Output of versioninfo()

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: macOS (arm64-apple-darwin24.0.0)
  CPU: 8 × Apple M1
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, apple-m1)
Threads: 4 default, 0 interactive, 2 GC (on 4 virtual cores)
Environment:
  JULIA_EDITOR = code
  JULIA_VSCODE_REPL = 1
  JULIA_NUM_THREADS = 4

[hersle]

It helps if you use use_scc = false:

prob = ODEProblem(sys, [], (0.0, 1.0); use_scc = false)
sol = solve(prob, Tsit5())

[ Info: updating data1 at t=0.0
[ Info: updating data1 at t=0.0
[ Info: updating data1 at t=0.01
[ Info: updating data1 at t=0.161
[ Info: updating data1 at t=0.327
[ Info: updating data1 at t=0.9
[ Info: updating data1 at t=0.9800255409045097
[ Info: updating data1 at t=1.0
[ Info: updating data1 at t=1.0

[hersle]

I don't think ModelingToolkit should make assumptions on the parameters to get rid of the duplicate data1 at t=0.0 and data1 at t=1.0. Instead I would suggest to modify your Data type to something like this:

using ModelingToolkit
t = ModelingToolkit.t_nounits
D = ModelingToolkit.D_nounits
using OrdinaryDiffEqTsit5

@variables v1(t)=1
@variables v2(t) [guess=0]

mutable struct Data
    name
    data
    count
    last_t
end
function update!(d::Data, t)
    if t != d.last_t
        @info "updating $(d.name) at t=$t"
        d.data = ones(10000) # Updating the data is expensive.
        d.count += 1 # Count the number of times the data gets updated.
        d.last_t = t
    end
end
function (d::Data)(t)
    update!(d, t)
    rand(d.data)
end
@register_symbolic update!(d::Data)

@parameters (d1::Data)(..) = Data(:data1, [], 0, NaN)
@parameters (d2::Data)(..) = Data(:data2, [], 0, NaN)

eqs = [
    D(v1) ~ d1(t),
    v2 ~ d2(t), # Some of the data parameters are not actually needed to solve the system.
]
@mtkbuild sys = System(eqs, t)

prob = ODEProblem(sys, [], (0.0, 1.0); use_scc = false)
sol = solve(prob, Tsit5())

[ Info: updating data1 at t=0.0
[ Info: updating data1 at t=0.01
[ Info: updating data1 at t=0.161
[ Info: updating data1 at t=0.327
[ Info: updating data1 at t=0.9
[ Info: updating data1 at t=0.9800255409045097
[ Info: updating data1 at t=1.0

[AayushSabharwal]

#3724 should fix this

[ctessum]

Thanks!