On brain-inspired connectivity and hybrid network topologies

This paper starts from very fresh analyses comparing brainpsilas connectivity with those of well-known network topologies, based on the latest interpretation of Rentpsilas rule. Those analyses have revealed how close the brain comes to the latest Rentpsilas rule averages. On the other hand, all the known network topologies seems to fall short of being strong contenders for mimicking the brain. That is why this paper performs a detailed Rent-based (top-down) connectivity analysis of many two-level hybrid network topologies. This analysis aims to identify those two-level hybrid network topologies which are able to closely mimic brainpsilas connectivity. The ranges of granularity (as given by the total number of gates and the number of processors) where this mimicking is happening are identified. These results should have implications for the design of networks(-on-chip) and for the burgeoning field of multi/many-core processors (in the short to medium term), as well as for investigations on future nano-architectures (in the long run). Complementary results using a bottom-up approach have also been obtained, and will be mentioned.