The question of whether it is possible to load deep neural network architectures efficiently is examined by considering the class of pyramidal architectures. This class allows only a low interaction of the nodes. Still, the loading problem is found to be NP-complete. This provides evidence that depth alone is a factor accounting for loading hardness.