@inproceedings{b5885bd9dd534d9c82c5b4e1db1f8a03,
title = "On brain-inspired hierarchical network topologies",
abstract = "In this paper our aim is to identify layered hierarchical generic network topologies which could closely mimic brain's connectivity. Recent analyses have compared the brain's connectivity (based both on a cortical-equivalent Rent's rule and on neurological data) with well-known network topologies used in supercomputers and massively parallel computers (using two different interpretations of Rent's rule). These have revealed that all the well-known computer network topologies fall short of being strong contenders for mimicking the brain's connectivity. That is why in this paper we perform a high-level analysis of two-layer hierarchical generic networks. The range of granularities (i.e., number of gates/cores/neurons) as well as the fan-ins and the particular combinations of the two generic networks which would make such a mimicking achievable are identified and discussed.",
keywords = "Brain, Connectivity, Nano-architecture, Network topology, Network-on-chip, Neural networks, Rent's rule",
author = "Valeriu Beiu and Madappuram, {Basheer A.M.} and Kelly, {Peter M.} and McDaid, {Liam J.}",
year = "2009",
language = "English",
isbn = "9789810836948",
series = "2009 9th IEEE Conference on Nanotechnology, IEEE NANO 2009",
pages = "202--205",
booktitle = "2009 9th IEEE Conference on Nanotechnology, IEEE NANO 2009",
note = "2009 9th IEEE Conference on Nanotechnology, IEEE NANO 2009 ; Conference date: 26-07-2009 Through 30-07-2009",
}