I am converting some algorithms from Python/Numpy to Julia and have no idea how to handle that Julia arrays are column major.
I have a matrix on disk (very large > 10GB) and it is stored row major. This is the natural representation in my application. Now I want to solve a linear system of equations and use the Kaczmarz algorithm that operates on matrix rows and therefore should be used with a row major matrix representation (Please no comments on the convergence speed of Kaczmarz algorithm, its extremely fast in my application). I could write the matrix loading and the algorithm keeping the transposition in mind but this does not feel right to me. Another solution seems to be the introduction of a cheap transposition type. But even more general one could make the Julia base array more flexible and allow for arbitrary strides. Has someone run into similar issues?
