I am puzzled by the performance of Julia, somehow it matters if I fully specialize the function argument. Consider the two functions: @noinline @inbounds function update_gen!(y::AbstractVector{T}, x::AbstractVector{T}) where {T<:Number} y[1] = x[1] return nothing end @noinline @inbounds functio…

[image] NicolasW: Try dropping the interpolation of the in/output and the Float64version becomes significantly faster. Dropping the interpolation means that you are timing dynamic dispatch, which is not typically relevant to performance in real applications.

Performance of value assignment inside functions

General Usage Performance

stevengj July 13, 2022, 1:20pm 4

Dropping the interpolation means that you are timing dynamic dispatch, which is not typically relevant to performance in real applications.

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Performance of value assignment inside functions

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