On two-layer brain-inspired hierarchical topologies - A rent's rule approach

Valeriu Beiu, Basheer A.M. Madappuram, Peter M. Kelly, Liam J. McDaid

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


This research compares the brain's connectivity (based on different analyses of neurological data) with well-known network topologies (originally used in super-computers) using Rent's rule. The comparison reveals that brain connectivity is in good agreement with Rent's rule. However, the known network topologies fall short of being strong contenders for mimicking brain's connectivity. That is why we perform a detailed Rent-based (top-down) connectivity analysis of generic two-layer hierarchical network topologies. This analysis aims to identify generic two-layer hierarchical network topologies which could closely mimic brain's connectivity. The range of granularities (i.e., number of gates/cores/neurons) where such mimicking is possible are identified and discussed. These results should have implications for the design of future networks-on-chip in general, and for the burgeoning field of multi/many-core processors in particular (in the medium term), as well as for forward-looking investigations on emerging brain-inspired nano-architectures (in the long run).

Original languageEnglish
Title of host publicationTransactions on High-Performance Embedded Architectures and Compilers IV
PublisherSpringer Verlag
Number of pages23
ISBN (Print)9783642245671
Publication statusPublished - 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6760 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


  • Connectivity
  • Rent's rule
  • brain
  • communication
  • nano-architecture
  • network topology
  • network-on-chip
  • neural networks

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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