I have the model where it is convenient to represent one of the variables as a matrix. This variable, however, is obtained as a solution of ODEs (among other variables). I'm using Sundials to solve ODEs and `Sundials.cvode` requires the ODE RHS function to take a vector. So, it seems logical to pack the variables into a vector to pass to `cvode` and unpack them for more convenient use in my code.
For example, consider `x = fill(1.0, 10)` and the first 6 entries are actually a matrix of size 3x2, other 4: other variables. So, I can do `s = reshape(x[1:6], (3,2))`. However, this creates a copy, which I would want to avoid. And I couldn't find a way to do the view-reshaping by applying `view()` function or doing `SubArray` directly. For now I settle on to using indices of the form `(i-1)*M + j +1` to retrieve `s[i,j] = x[(i-1)*M + j +1]`. But, (1) julia's 1-based arrays make it awkward to use this notation and (2) matrix (not element-wise) operations are not available.
