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@INPROCEEDINGS{Schenck:173374,
author = {Schenck, Wolfram and Adinets, Andrey and Zaytsev, Yury and
Pleiter, Dirk and Morrison, Abigail},
title = {{P}erformance {M}odel for {L}arge-{S}cale {N}eural
{S}imulations with {NEST}},
reportid = {FZJ-2014-06784},
year = {2014},
abstract = {NEST is a simulator for large networks of spiking point
neurons for neuroscience research. A typical NEST simulation
consists of two stages: first the network is wired up, and
second the dynamics of the network is simulated. Our work
aims at developing a performance model for the second stage,
the simulation stage, by a semi-empirical approach. We
collected measurements of the runtime performance of NEST
under varying parameter settings on the JUQUEEN
supercomputer at Forschungszentrum Jülich, and subsequently
fitted a theoretical model to this data. This performance
model defines the simulation time as weighted sum of
algorithmic complexities which have been identified in the
NEST source code. After parameter fitting, the coefficient
of determination on the training data is close to 1.0, and
the model can be used to successfully extrapolate NEST
simulation times. Furthermore, recommendations for
algorithmic improvements of the NEST code can be derived
from the modeling results.},
month = {Nov},
date = {2014-11-16},
organization = {Supercomputing 2014, New Orleans
(USA), 16 Nov 2014 - 21 Nov 2014},
subtyp = {After Call},
cin = {JSC / JARA-HPC / IAS-6 / INM-6},
cid = {I:(DE-Juel1)JSC-20090406 / $I:(DE-82)080012_20140620$ /
I:(DE-Juel1)IAS-6-20130828 / I:(DE-Juel1)INM-6-20090406},
pnm = {411 - Computational Science and Mathematical Methods
(POF2-411) / SMHB - Supercomputing and Modelling for the
Human Brain (HGF-SMHB-2013-2017) / W2Morrison - W2/W3
Professorinnen Programm der Helmholtzgemeinschaft
(B1175.01.12) / SLNS - SimLab Neuroscience (Helmholtz-SLNS)},
pid = {G:(DE-HGF)POF2-411 / G:(DE-Juel1)HGF-SMHB-2013-2017 /
G:(DE-HGF)B1175.01.12 / G:(DE-Juel1)Helmholtz-SLNS},
typ = {PUB:(DE-HGF)24},
url = {https://juser.fz-juelich.de/record/173374},
}