Often (in the scientific computing communities that I am in) large tensor contractions are done by reshaping tensors into matrices, transposing, and using matrix multiplication. The contraction time can change dramatically based on the order one contracts the tensors and the relative sizes of the tensors. It seems this just uses a large nested for loop - how does this strategy compare to using dedicated matrix multiplication algorithms?