`plan_rfft` together used with `mul!` and `@view` complains about wrong-strides-output

Specific Domains Signal and Image Processing
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I’m not sure if you are correct. I believe the dims argument for fft, rfft is intended for exactly that case:
rfft performs a length(dims)-dimensional Fourier transform over the dims dimensions of the N-dimensional array.

rfft(A [, dims])


  Multidimensional FFT of a real array A, exploiting the fact that the transform has conjugate symmetry in order to save
  roughly half the computational time and storage costs compared with fft. If A has size (n_1, ..., n_d), the result has
  size (div(n_1,2)+1, ..., n_d).

  The optional dims argument specifies an iterable subset of one or more dimensions of A to transform, similar to fft.
  Instead of (roughly) halving the first dimension of A in the result, the dims[1] dimension is (roughly) halved in the
  same way.