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@INPROCEEDINGS{Kleijnen:906813,
author = {Kleijnen, Robert and Ebrahimzadeh, Pezhman},
title = {{M}odified {C}ommunication {N}etworks for the {S}imulation
of {N}euromorphic {S}ystems},
reportid = {FZJ-2022-01710},
year = {2021},
abstract = {Neuromorphic computing systems have been introduced in the
past few decades as a paradigm shift in computing
architectures, commonly used for biological and artificial
neural network simulations and artificial intelligence
applications. In order to study the long-term dynamics in
neuronal networks (e.g. biological learning), the existing
systems lack in a significant acceleration compared to
biological time for the simulation of large scale networks,
due to the increase of latency and the unfulfilled bandwidth
demands in the communication network architectures. This
work investigates the traffic load distribution and latency
within a communication network, used to simulate an
arbitrary neural network with a fixed size and connectivity
probability. We report a significant decrease in the latency
and bandwidth requirements by modifying the commonly used
square mesh grid with additional short- and/or long-range
connections between nodes.},
month = {Jul},
date = {2021-07-05},
organization = {Networks 2021, Virtual (USA), 5 Jul
2021 - 10 Jul 2021},
subtyp = {After Call},
cin = {ZEA-2},
cid = {I:(DE-Juel1)ZEA-2-20090406},
pnm = {5234 - Emerging NC Architectures (POF4-523) / ACA -
Advanced Computing Architectures (SO-092)},
pid = {G:(DE-HGF)POF4-5234 / G:(DE-HGF)SO-092},
typ = {PUB:(DE-HGF)6},
url = {https://juser.fz-juelich.de/record/906813},
}