No method matching on 32 bit machine

[Naikless]

I get the following error when using v0.21.18 on a 32 bit machine.

LoadError: MethodError: no method matching vload_transpose_quote(::Int32, ::Int32, ::Int32, ::Int32, ::Int32, ::Int32, ::Int32, ::Bool, ::Int32, ::Int32, ::UInt64, ::Bool)
  Closest candidates are:
    vload_transpose_quote(::Int32, ::Int32, ::Int32, ::Int32, ::Int32, ::Int32, ::Int32, ::Bool, ::Int32, ::Int32, ::UInt32, ::Bool) at /home/runner/.julia/packages/VectorizationBase/Q2q04/src/vecunroll/memory.jl:204

Running the same code on 64 bit causes no error.

[chriselrod]

Hopefully fixed by 67d5236

[chriselrod]

The tests segfault on x86 Windows.
If that's a problem, feel free to file another issue.
I don't have a Windows machine on which to test and debug.
Tests pass on Linux.

[Naikless]

Unfortunately I still receive the exact same error message with v0.21.19 on both x86 linux and Windows.
I only use github actions to test my package on x86 builds too, this is where this shows up. I don't have any x86 os locally to further test this.

Here are the probably most relevant parts of the stacktrace (still long!), maybe its is just showing in the context where it is called.

Got exception outside of a @test
  LoadError: MethodError: no method matching vload_transpose_quote(::Int32, ::Int32, ::Int32, ::Int32, ::Int32, ::Int32, ::Int32, ::Bool, ::Int32, ::Int32, ::UInt64, ::Bool)
  Closest candidates are:
    vload_transpose_quote(::Int32, ::Int32, ::Int32, ::Int32, ::Int32, ::Int32, ::Int32, ::Bool, ::Int32, ::Int32, ::UInt32, ::Bool) at /home/runner/.julia/packages/VectorizationBase/i9XbD/src/vecunroll/memory.jl:204
  Stacktrace:
    [1] #s33#326
      @ ~/.julia/packages/VectorizationBase/i9XbD/src/vecunroll/memory.jl:413 [inlined]
    [2] var"#s33#326"(A::Any, AU::Any, F::Any, N::Any, AV::Any, W::Any, M::Any, I::Any, T::Any, D::Any, RS::Any, UX::Any, C::Any, ::Any, sptr::Any, u::Any, sm::Any, #unused#::Type, #unused#::Type, #unused#::Any)
      @ VectorizationBase ./none:0
    [3] (::Core.GeneratedFunctionStub)(::Any, ::Vararg{Any, N} where N)
      @ Core ./boot.jl:571
    [4] _vload
      @ ~/.julia/packages/VectorizationBase/i9XbD/src/vecunroll/memory.jl:440 [inlined]
    [5] vload
      @ ~/.julia/packages/VectorizationBase/i9XbD/src/llvm_intrin/memory_addr.jl:681 [inlined]
    [6] macro expansion
      @ ~/.julia/packages/TriangularSolve/90Qqf/src/TriangularSolve.jl:229 [inlined]
    [7] rdiv_solve_W!
      @ ~/.julia/packages/TriangularSolve/90Qqf/src/TriangularSolve.jl:220 [inlined]
    [8] rdiv_U!(spc::LayoutPointers.StridedPointer{Float64, 2, 2, 0, (2, 1), Tuple{Int32, Static.StaticInt{8}}, Tuple{Static.StaticInt{0}, Static.StaticInt{0}}}, spa::LayoutPointers.StridedPointer{Float64, 2, 2, 0, (2, 1), Tuple{Int32, Static.StaticInt{8}}, Tuple{Static.StaticInt{0}, Static.StaticInt{0}}}, spu::LayoutPointers.StridedPointer{Float64, 2, 2, 0, (2, 1), Tuple{Int32, Static.StaticInt{8}}, Tuple{Static.StaticInt{0}, Static.StaticInt{0}}}, M::Int32, N::Int32, #unused#::Static.StaticInt{2}, #unused#::Val{true})
      @ TriangularSolve ~/.julia/packages/TriangularSolve/90Qqf/src/TriangularSolve.jl:515
    [9] div_dispatch!(C::StrideArraysCore.PtrArray{Tuple{Int32, Int32}, (false, true), Float64, 2, 2, 0, (2, 1), Tuple{Int32, Static.StaticInt{8}}, Tuple{Static.StaticInt{1}, Static.StaticInt{1}}}, A::StrideArraysCore.PtrArray{Tuple{Int32, Int32}, (false, true), Float64, 2, 2, 0, (2, 1), Tuple{Int32, Static.StaticInt{8}}, Tuple{Static.StaticInt{1}, Static.StaticInt{1}}}, U::StrideArraysCore.PtrArray{Tuple{Int32, Int32}, (false, true), Float64, 2, 2, 0, (2, 1), Tuple{Int32, Static.StaticInt{8}}, Tuple{Static.StaticInt{1}, Static.StaticInt{1}}}, #unused#::Val{true}, #unused#::Val{true})
      @ TriangularSolve ~/.julia/packages/TriangularSolve/90Qqf/src/TriangularSolve.jl:314
   [10] ldiv! (repeats 2 times)
      @ ~/.julia/packages/TriangularSolve/90Qqf/src/TriangularSolve.jl:343 [inlined]
   [11] reckernel!(A::StrideArraysCore.PtrArray{Tuple{Int32, Int32}, (true, true), Float64, 2, 1, 0, (1, 2), Tuple{Static.StaticInt{8}, Int32}, Tuple{Static.StaticInt{1}, Static.StaticInt{1}}}, pivot::Val{true}, m::Int32, n::Int32, ipiv::StrideArraysCore.PtrArray{Tuple{Int32}, (true,), Int32, 1, 1, 0, (1,), Tuple{Static.StaticInt{4}}, Tuple{Static.StaticInt{1}}}, info::Int32, blocksize::Int32, thread::Bool)
      @ RecursiveFactorization ~/.julia/packages/RecursiveFactorization/7pQ6n/src/lu.jl:165
   [12] reckernel!(A::StrideArraysCore.PtrArray{Tuple{Int32, Int32}, (true, true), Float64, 2, 1, 0, (1, 2), Tuple{Static.StaticInt{8}, Int32}, Tuple{Static.StaticInt{1}, Static.StaticInt{1}}}, pivot::Val{true}, m::Int32, n::Int32, ipiv::StrideArraysCore.PtrArray{Tuple{Int32}, (true,), Int32, 1, 1, 0, (1,), Tuple{Static.StaticInt{4}}, Tuple{Static.StaticInt{1}}}, info::Int32, blocksize::Int32, thread::Bool)
      @ RecursiveFactorization ~/.julia/packages/RecursiveFactorization/7pQ6n/src/lu.jl:159
   [13] recurse!
      @ ~/.julia/packages/RecursiveFactorization/7pQ6n/src/lu.jl:76 [inlined]
   [14] lu!(A::Matrix{Float64}, ipiv::Vector{Int32}, pivot::Val{true}; check::Bool, blocksize::Int32, threshold::Int32)
      @ RecursiveFactorization ~/.julia/packages/RecursiveFactorization/7pQ6n/src/lu.jl:62
   [15] #lu!#2
      @ ~/.julia/packages/RecursiveFactorization/7pQ6n/src/lu.jl:27 [inlined]
   [16] lu! (repeats 2 times)
      @ ~/.julia/packages/RecursiveFactorization/7pQ6n/src/lu.jl:22 [inlined]
   [17] (::DiffEqBase.DefaultLinSolve)(x::Vector{Float64}, A::Matrix{Float64}, b::Vector{Float64}, update_matrix::Bool; reltol::Float64, kwargs::Base.Iterators.Pairs{Symbol, DiffEqBase.ScaleVector{Vector{Float64}}, Tuple{Symbol, Symbol}, NamedTuple{(:Pl, :Pr), Tuple{DiffEqBase.ScaleVector{Vector{Float64}}, DiffEqBase.ScaleVector{Vector{Float64}}}}})
      @ DiffEqBase ~/.julia/packages/DiffEqBase/YIT73/src/linear_nonlinear.jl:112
   [18] perform_step!(integrator::OrdinaryDiffEq.ODEIntegrator{OrdinaryDiffEq.Rosenbrock23{11, false, DiffEqBase.DefaultLinSolve, Val{:forward}}, true, Vector{Float64}, Nothing, Float64, Vector{Any}, Float64, Float64, Float64, Float64, Vector{Vector{Float64}}, SciMLBase.ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Vector{Vector{Vector{Float64}}}, SciMLBase.ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Any}, SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.Rosenbrock23{11, false, DiffEqBase.DefaultLinSolve, Val{:forward}}, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Vector{Vector{Float64}}, Vector{Float64}, Vector{Vector{Vector{Float64}}}, OrdinaryDiffEq.Rosenbrock23Cache{Vector{Float64}, Vector{Float64}, Vector{Float64}, Matrix{Float64}, Matrix{Float64}, OrdinaryDiffEq.Rosenbrock23Tableau{Float64}, SciMLBase.TimeGradientWrapper{SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Vector{Float64}, Vector{Any}}, SciMLBase.UJacobianWrapper{SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Float64, Vector{Any}}, DiffEqBase.DefaultLinSolve, FiniteDiff.JacobianCache{Vector{Float64}, Vector{Float64}, Vector{Float64}, UnitRange{Int32}, Nothing, Val{:forward}(), Float64}, FiniteDiff.GradientCache{Nothing, Vector{Float64}, Vector{Float64}, Float64, Val{:forward}(), Float64, Val{true}()}}}, DiffEqBase.DEStats}, SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, OrdinaryDiffEq.Rosenbrock23Cache{Vector{Float64}, Vector{Float64}, Vector{Float64}, Matrix{Float64}, Matrix{Float64}, OrdinaryDiffEq.Rosenbrock23Tableau{Float64}, SciMLBase.TimeGradientWrapper{SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Vector{Float64}, Vector{Any}}, SciMLBase.UJacobianWrapper{SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Float64, Vector{Any}}, DiffEqBase.DefaultLinSolve, FiniteDiff.JacobianCache{Vector{Float64}, Vector{Float64}, Vector{Float64}, UnitRange{Int32}, Nothing, Val{:forward}(), Float64}, FiniteDiff.GradientCache{Nothing, Vector{Float64}, Vector{Float64}, Float64, Val{:forward}(), Float64, Val{true}()}}, OrdinaryDiffEq.DEOptions{Float64, Float64, Float64, Float64, OrdinaryDiffEq.PIController{Rational{Int32}}, typeof(DiffEqBase.ODE_DEFAULT_NORM), typeof(LinearAlgebra.opnorm), Nothing, DiffEqBase.CallbackSet{Tuple{}, Tuple{DiffEqBase.DiscreteCallback{SDtoolbox.CV.var"#approaches_equilibrium#2"{Float64}, typeof(SciMLBase.terminate!), typeof(DiffEqBase.INITIALIZE_DEFAULT), typeof(DiffEqBase.FINALIZE_DEFAULT)}}}, typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), DataStructures.BinaryHeap{Float64, DataStructures.FasterForward}, DataStructures.BinaryHeap{Float64, DataStructures.FasterForward}, Nothing, Nothing, Int32, Tuple{}, Tuple{}, Tuple{}}, Vector{Float64}, Float64, Nothing, OrdinaryDiffEq.DefaultInit}, cache::OrdinaryDiffEq.Rosenbrock23Cache{Vector{Float64}, Vector{Float64}, Vector{Float64}, Matrix{Float64}, Matrix{Float64}, OrdinaryDiffEq.Rosenbrock23Tableau{Float64}, SciMLBase.TimeGradientWrapper{SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Vector{Float64}, Vector{Any}}, SciMLBase.UJacobianWrapper{SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Float64, Vector{Any}}, DiffEqBase.DefaultLinSolve, FiniteDiff.JacobianCache{Vector{Float64}, Vector{Float64}, Vector{Float64}, UnitRange{Int32}, Nothing, Val{:forward}(), Float64}, FiniteDiff.GradientCache{Nothing, Vector{Float64}, Vector{Float64}, Float64, Val{:forward}(), Float64, Val{true}()}}, repeat_step::Bool)
      @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/t7j8H/src/perform_step/rosenbrock_perform_step.jl:113
   [19] perform_step!
      @ ~/.julia/packages/OrdinaryDiffEq/t7j8H/src/perform_step/rosenbrock_perform_step.jl:95 [inlined]
   [20] solve!(integrator::OrdinaryDiffEq.ODEIntegrator{OrdinaryDiffEq.Rosenbrock23{11, false, DiffEqBase.DefaultLinSolve, Val{:forward}}, true, Vector{Float64}, Nothing, Float64, Vector{Any}, Float64, Float64, Float64, Float64, Vector{Vector{Float64}}, SciMLBase.ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Vector{Vector{Vector{Float64}}}, SciMLBase.ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Any}, SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.Rosenbrock23{11, false, DiffEqBase.DefaultLinSolve, Val{:forward}}, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Vector{Vector{Float64}}, Vector{Float64}, Vector{Vector{Vector{Float64}}}, OrdinaryDiffEq.Rosenbrock23Cache{Vector{Float64}, Vector{Float64}, Vector{Float64}, Matrix{Float64}, Matrix{Float64}, OrdinaryDiffEq.Rosenbrock23Tableau{Float64}, SciMLBase.TimeGradientWrapper{SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Vector{Float64}, Vector{Any}}, SciMLBase.UJacobianWrapper{SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Float64, Vector{Any}}, DiffEqBase.DefaultLinSolve, FiniteDiff.JacobianCache{Vector{Float64}, Vector{Float64}, Vector{Float64}, UnitRange{Int32}, Nothing, Val{:forward}(), Float64}, FiniteDiff.GradientCache{Nothing, Vector{Float64}, Vector{Float64}, Float64, Val{:forward}(), Float64, Val{true}()}}}, DiffEqBase.DEStats}, SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, OrdinaryDiffEq.Rosenbrock23Cache{Vector{Float64}, Vector{Float64}, Vector{Float64}, Matrix{Float64}, Matrix{Float64}, OrdinaryDiffEq.Rosenbrock23Tableau{Float64}, SciMLBase.TimeGradientWrapper{SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Vector{Float64}, Vector{Any}}, SciMLBase.UJacobianWrapper{SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Float64, Vector{Any}}, DiffEqBase.DefaultLinSolve, FiniteDiff.JacobianCache{Vector{Float64}, Vector{Float64}, Vector{Float64}, UnitRange{Int32}, Nothing, Val{:forward}(), Float64}, FiniteDiff.GradientCache{Nothing, Vector{Float64}, Vector{Float64}, Float64, Val{:forward}(), Float64, Val{true}()}}, OrdinaryDiffEq.DEOptions{Float64, Float64, Float64, Float64, OrdinaryDiffEq.PIController{Rational{Int32}}, typeof(DiffEqBase.ODE_DEFAULT_NORM), typeof(LinearAlgebra.opnorm), Nothing, DiffEqBase.CallbackSet{Tuple{}, Tuple{DiffEqBase.DiscreteCallback{SDtoolbox.CV.var"#approaches_equilibrium#2"{Float64}, typeof(SciMLBase.terminate!), typeof(DiffEqBase.INITIALIZE_DEFAULT), typeof(DiffEqBase.FINALIZE_DEFAULT)}}}, typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), DataStructures.BinaryHeap{Float64, DataStructures.FasterForward}, DataStructures.BinaryHeap{Float64, DataStructures.FasterForward}, Nothing, Nothing, Int32, Tuple{}, Tuple{}, Tuple{}}, Vector{Float64}, Float64, Nothing, OrdinaryDiffEq.DefaultInit})
      @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/t7j8H/src/solve.jl:478
   [21] #__solve#493
      @ ~/.julia/packages/OrdinaryDiffEq/t7j8H/src/solve.jl:5 [inlined]
   [22] #solve_call#42
      @ ~/.julia/packages/DiffEqBase/YIT73/src/solve.jl:61 [inlined]
   [23] solve_up(prob::SciMLBase.ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Any}, SciMLBase.ODEFunction{true, typeof(SDtoolbox.CV.cv!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, sensealg::Nothing, u0::Vector{Float64}, p::Vector{Any}, args::OrdinaryDiffEq.Rosenbrock23{0, false, DiffEqBase.DefaultLinSolve, Val{:forward}}; kwargs::Base.Iterators.Pairs{Symbol, Any, NTuple{4, Symbol}, NamedTuple{(:progress, :callback, :abtol, :reltol), Tuple{Bool, DiffEqBase.DiscreteCallback{SDtoolbox.CV.var"#approaches_equilibrium#2"{Float64}, typeof(SciMLBase.terminate!), typeof(DiffEqBase.INITIALIZE_DEFAULT), typeof(DiffEqBase.FINALIZE_DEFAULT)}, Float64, Float64}}})
      @ DiffEqBase ~/.julia/packages/DiffEqBase/YIT73/src/solve.jl:87
   [24] #solve#43
      @ ~/.julia/packages/DiffEqBase/YIT73/src/solve.jl:73 [inlined]

[chriselrod]

Unfortunately I still receive the exact same error message with v0.21.19 on both x86 linux and Windows.
I only use github actions to test my package on x86 builds too, this is where this shows up. I don't have any x86 os locally to further test this.

Please provide a reproducer, or at least a stack trace.
The only information I have to go off of here is that the indicated function received a UInt64 argument when it should have received UInt32.
But received from what caller, where?

[chriselrod]

I don't have any x86 os locally to further test this.

If you have an x64 OS locally, you should be able to just install and run an x86 binary on the x64 system.
https://julialang.org/downloads/

You may additionally have to install 32-bit support libraries if you don't have them.

[Naikless]

Unfortunately I still receive the exact same error message with v0.21.19 on both x86 linux and Windows.
I only use github actions to test my package on x86 builds too, this is where this shows up. I don't have any x86 os locally to further test this.

Please provide a reproducer, or at least a stack trace. The only information I have to go off of here is that the indicated function received a UInt64 argument when it should have received UInt32. But received from what caller, where?

Sorry, for the missing information! I added a stacktrace.
And thanks for the hint regarding 32bit Julia on a 64bit system, I will try this as soon as possible.

[chriselrod]

Thanks for the stacktrace.
Should be fixed by: JuliaSIMD/TriangularSolve.jl@e5d987c

[Naikless]

Haha, yeah, those hard-coded UInt64 just might be the culprit. ;)

Unsurprisingly, this did the trick. Thanks a lot for the quick fix!