000137379 001__ 137379
000137379 005__ 20240313094956.0
000137379 037__ $$aFZJ-2013-03826
000137379 1001_ $$0P:(DE-Juel1)151364$$aKunkel, Susanne$$b0$$eCorresponding author$$ufzj
000137379 1112_ $$a10th Meeting of the German Neuroscience Society$$cGoettingen$$d2013-03-13 - 2013-03-18$$gNWG 2013$$wGermany
000137379 245__ $$aSupercomputers ready for use as discovery machines for neuroscience
000137379 260__ $$c2013
000137379 3367_ $$033$$2EndNote$$aConference Paper
000137379 3367_ $$2BibTeX$$aINPROCEEDINGS
000137379 3367_ $$2DRIVER$$aconferenceObject
000137379 3367_ $$2ORCID$$aCONFERENCE_POSTER
000137379 3367_ $$2DataCite$$aOutput Types/Conference Poster
000137379 3367_ $$0PUB:(DE-HGF)24$$2PUB:(DE-HGF)$$aPoster$$bposter$$mposter$$s1570523314_4405$$xAfter Call
000137379 520__ $$aNEST is a widely used tool to simulate biological spiking neural networks [1]. The simulator is subject tocontinuous development, which is driven by the requirements of the current neuroscientific questions. Atpresent, a major part of the software development focuses on the improvement of the simulator'sfundamental data structures in order to enable brain-scale simulations on supercomputers such as theBlue Gene system in Jülich and the K computer in Kobe. Based on our memory-usage model [2], weredesigned the neuronal and the connection infrastructure of NEST such that networks of 10^8 neuronsand 10^12 synapses can be simulated on the K computer [3]. These improvements reduce the memoryfootprint without compromising on the simulator's general usability and user interface. Here, we describethe recent technological advances which enable NEST to achieve high performance and good scaling ofnetwork setup and simulation on the K computer and on the Blue Gene system. We demonstrate that theusability of these machines for network simulations has become comparable to running simulations on asingle PC.
000137379 536__ $$0G:(DE-HGF)POF2-331$$a331 - Signalling Pathways and Mechanisms in the Nervous System (POF2-331)$$cPOF2-331$$fPOF II$$x0
000137379 536__ $$0G:(DE-HGF)POF2-411$$a411 - Computational Science and Mathematical Methods (POF2-411)$$cPOF2-411$$fPOF II$$x1
000137379 536__ $$0G:(DE-Juel1)jinb33_20121101$$aBrain-Scale Simulations (jinb33_20121101)$$cjinb33_20121101$$fBrain-Scale Simulations$$x2
000137379 536__ $$0G:(DE-Juel1)HGF-SystemsBiology$$aHASB - Helmholtz Alliance on Systems Biology (HGF-SystemsBiology)$$cHGF-SystemsBiology$$fHASB-2008-2012$$x3
000137379 536__ $$0G:(DE-Juel1)BTN-Peta-2008-2012$$aBTN-Peta - The Next-Generation Integrated Simulation of Living Matter (BTN-Peta-2008-2012)$$cBTN-Peta-2008-2012$$fBTN-Peta-2008-2012$$x4
000137379 536__ $$0G:(EU-Grant)269921$$aBRAINSCALES - Brain-inspired multiscale computation in neuromorphic hybrid systems (269921)$$c269921$$fFP7-ICT-2009-6$$x5
000137379 536__ $$0G:(DE-Juel1)HGF-SMHB-2013-2017$$aSMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017)$$cHGF-SMHB-2013-2017$$fSMHB$$x6
000137379 536__ $$0G:(DE-HGF)B1175.01.12$$aW2Morrison - W2/W3 Professorinnen Programm der Helmholtzgemeinschaft (B1175.01.12)$$cB1175.01.12$$x7
000137379 536__ $$0G:(DE-Juel1)Helmholtz-SLNS$$aSLNS - SimLab Neuroscience (Helmholtz-SLNS)$$cHelmholtz-SLNS$$x8
000137379 7001_ $$0P:(DE-Juel1)145897$$aSchmidt, Maximilian$$b1$$ufzj
000137379 7001_ $$0P:(DE-Juel1)142538$$aEppler, Jochen Martin$$b2$$ufzj
000137379 7001_ $$0P:(DE-HGF)0$$aIgarashi, Jun$$b3
000137379 7001_ $$0P:(DE-HGF)0$$aMasumoto, Gen$$b4
000137379 7001_ $$0P:(DE-HGF)0$$aFukai, Tomoki$$b5
000137379 7001_ $$0P:(DE-HGF)0$$aIshii, Shin$$b6
000137379 7001_ $$0P:(DE-HGF)0$$aPlesser, Hans Ekkehard$$b7
000137379 7001_ $$0P:(DE-Juel1)151166$$aMorrison, Abigail$$b8$$ufzj
000137379 7001_ $$0P:(DE-Juel1)144174$$aDiesmann, Markus$$b9$$ufzj
000137379 7001_ $$0P:(DE-Juel1)144806$$aHelias, Moritz$$b10$$ufzj
000137379 909CO $$ooai:juser.fz-juelich.de:137379$$pec_fundedresources$$pVDB$$popenaire
000137379 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)151364$$aForschungszentrum Jülich GmbH$$b0$$kFZJ
000137379 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)145897$$aForschungszentrum Jülich GmbH$$b1$$kFZJ
000137379 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)142538$$aForschungszentrum Jülich GmbH$$b2$$kFZJ
000137379 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)151166$$aForschungszentrum Jülich GmbH$$b8$$kFZJ
000137379 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144174$$aForschungszentrum Jülich GmbH$$b9$$kFZJ
000137379 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144806$$aForschungszentrum Jülich GmbH$$b10$$kFZJ
000137379 9131_ $$0G:(DE-HGF)POF2-331$$1G:(DE-HGF)POF2-330$$2G:(DE-HGF)POF2-300$$3G:(DE-HGF)POF2$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lFunktion und Dysfunktion des Nervensystems$$vSignalling Pathways and Mechanisms in the Nervous System$$x0
000137379 9131_ $$0G:(DE-HGF)POF2-411$$1G:(DE-HGF)POF2-410$$2G:(DE-HGF)POF2-400$$3G:(DE-HGF)POF2$$4G:(DE-HGF)POF$$aDE-HGF$$bSchlüsseltechnologien$$lSupercomputing$$vComputational Science and Mathematical Methods$$x1
000137379 9141_ $$y2013
000137379 920__ $$lyes
000137379 9201_ $$0I:(DE-Juel1)INM-6-20090406$$kINM-6$$lComputational and Systems Neuroscience$$x0
000137379 9201_ $$0I:(DE-Juel1)IAS-6-20130828$$kIAS-6$$lTheoretical Neuroscience$$x1
000137379 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x2
000137379 980__ $$aposter
000137379 980__ $$aVDB
000137379 980__ $$aI:(DE-Juel1)INM-6-20090406
000137379 980__ $$aI:(DE-Juel1)IAS-6-20130828
000137379 980__ $$aI:(DE-Juel1)JSC-20090406
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000137379 981__ $$aI:(DE-Juel1)IAS-6-20130828
000137379 981__ $$aI:(DE-Juel1)IAS-6-20130828
000137379 981__ $$aI:(DE-Juel1)JSC-20090406