I have a type-stability question. In my 2D axisymmetric ray tracing code, I define an array of surfaces that has the type Union{Cone, Plane}, like surfaces = Matrix{Union{Cone, Plane}}(undef, 100, 2) All of them should in principle be cones, but due to small errors from a discretization earlier on…

Cone and Plane are abstract types. Only unions of isbits types are fast. If you are using 64 bits floats then you probably want the type to be Union{Cone{Float64},Plane{Float64}}.

Yeah that’s roughly what I’m looking for. Looks like this way of doing things isn’t ideal then. But I’m also recalling discussion about updates to Julia where small Unions now have fairly good performance, whereas before, Unions were a performance-killer. What gives? Or is the 10x slowdown still “d…

Thank you, this helped. The field is not a float, but a subtype of Reflection. What would be the idiomatic way to write this function? Is it using typeof(), as in the following: function foo(refl) T = typeof(refl) surfaces = Matrix{Union{Plane{T}, Cone{T}}}(undef, 200, 2) return surface…

The question is if you need the parameterization on Reflection. You have two reflection types, so you could make an enum with two entries out of those. That would remove the type parameter of Cone and Plane, making the union small and therefore fast.

[image] Ininterrompue: function foo(refl) T = typeof(refl) surfaces = Matrix{Union{Plane{T}, Cone{T}}}(undef, 200, 2) return surfaces end This looks fine and idiomatic to me. Some people might replace the first two lines with function foo(refl::T) where T (or ... where T<:Reflecti…

Array of union causing 10x slowdown

General Usage Performance

jling December 7, 2022, 2:56am 2

maybe Allocation and slow down when # of types involved increase (slower than C++ virtual methods)

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Array of union causing 10x slowdown

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