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@INPROCEEDINGS{Pronold:864815,
author = {Pronold, Jari and Kunkel, Susanne},
title = {{M}eeting the performance challenges of spiking network
simulations on general purpose computers},
reportid = {FZJ-2019-04471},
year = {2019},
abstract = {Today’s extremely scalable simulation technology for
spiking neuronal networks enables the representation of
models of more than a billion of neurons and their
connections using the entire K computer. However, the
runtimes of the largest possible simulations carried out so
far were too long to allow for observations of the network
dynamics over long periods of time, and also small to
medium-scale simulations typically run in far more than
real-time. The performance challenges for spiking neuronal
network simulators such as NEST on general purpose computers
arise from the inherent sparse but broad connectivity
between neurons and from the unpredictable neuronal spiking
activity. In distributed simulations of spiking networks,
this requires frequent communication of spike data, and on
each compute node routing of the incoming spikes to the
local targets. This entails irregular memory access and
hence constitutes a major performance bottleneck, which is a
problem that I will address in my talk. I will present
recent developments in simulation technology that aim at
meeting such performance challenges.},
organization = {RCCS Institutional seminar, RCCS Kobe
(Japan)},
subtyp = {Invited},
cin = {INM-6 / IAS-6 / INM-10},
cid = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828 /
I:(DE-Juel1)INM-10-20170113},
pnm = {574 - Theory, modelling and simulation (POF3-574) /
Advanced Computing Architectures $(aca_20190115)$ /
Brain-Scale Simulations $(jinb33_20121101)$ / PhD no Grant -
Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405)},
pid = {G:(DE-HGF)POF3-574 / $G:(DE-Juel1)aca_20190115$ /
$G:(DE-Juel1)jinb33_20121101$ /
G:(DE-Juel1)PHD-NO-GRANT-20170405},
typ = {PUB:(DE-HGF)31},
url = {https://juser.fz-juelich.de/record/864815},
}