There seem to be some problems with type inference and `im`. If at the
beginning of the function I define
myim = convert(Complex128, im)
and then replace all uses of `im` with `myim`, then everything works as
expected.
Can you file an issue, please?
--Tim
On Friday, January 30, 2015 09:48:26 PM Kirill Ignatiev wrote:
> I have a newbie-type performance question.
>
> In some of my code there is a structure that looks like this:
>
> type FourierPoly
>
> > periods :: Vector{Int}
> > radiuses :: Vector{Float64}
> > phase_offsets :: Vector{Float64}
> >
> > end
>
> and the following two functions that operate on it:
>
> - function polyval(f::FourierPoly, t::Float64)
>
> > 33694968 s = zero(Complex128)
> >
> > 0 @inbounds for k = 1:length(f.periods)
> > 0 s += exp(2.pi*(t + f.phase_offsets[k]) * f.periods[k] * im)
> >
> > * f.radiuses[k]
> >
> > - end
> > 0 return s::Complex128
> > 0 end
> > 0
> > 0 function polyder(f::FourierPoly, t::Float64)
> > 0 s = zero(Complex128)
> >
> > 492303248 @inbounds for k = 1:length(f.periods)
> >
> > 0 θ = 2.pi * f.periods[k]
> >
> > 164100720 s += θ * im * exp((t + f.phase_offsets[k]) * θ * im) *
> > f.radiuses[k]
> >
> > 257652 end
> >
> > 0 return s::Complex128
> > - end
>
> (copied from output of julia run with --track-allocation=user).
>
> What is the difference between these two functions? polyval seems fine, but
> polyder is called at most as often as polyval from the rest of the code,
> yet its memory consumption is at least an order of magnitude higher? Can
> somebody please point out what I'm missing here?
