000912537 001__ 912537
000912537 005__ 20221216132046.0
000912537 0247_ $$2Handle$$a2128/33146
000912537 037__ $$aFZJ-2022-05710
000912537 041__ $$aEnglish
000912537 1001_ $$0P:(DE-Juel1)161462$$aYegenoglu, Alper$$b0$$eCorresponding author
000912537 1112_ $$aEnd of year colloquium 2022 at JSC$$cJülich$$d2022-12-08 - 2022-12-08$$wGermany
000912537 245__ $$aOptimizing Spiking Neural Networks with L2L on HPC systems$$f2022-12-08 - 
000912537 260__ $$c2022
000912537 3367_ $$033$$2EndNote$$aConference Paper
000912537 3367_ $$2DataCite$$aOther
000912537 3367_ $$2BibTeX$$aINPROCEEDINGS
000912537 3367_ $$2ORCID$$aLECTURE_SPEECH
000912537 3367_ $$0PUB:(DE-HGF)31$$2PUB:(DE-HGF)$$aTalk (non-conference)$$btalk$$mtalk$$s1671182565_8017$$xOther
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000912537 520__ $$aIn my talk I present the optimization of spiking neural networks (SNN) on HPC system using the L2L framework. I explain the problems when training SNNs to learn to solve tasks, then I introduce the concept of learning to learn and the framework L2L which implements the concept. Furthermore, I describe how optimization can be applied with L2L on SNNs and showcase two examples, namely optimizing a spiking reservoir network to classify digits and a swarm with a foraging behaviour.
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000912537 536__ $$0G:(EU-Grant)785907$$aHBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)$$c785907$$fH2020-SGA-FETFLAG-HBP-2017$$x1
000912537 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x2
000912537 536__ $$0G:(DE-Juel1)PHD-NO-GRANT-20170405$$aPhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405)$$cPHD-NO-GRANT-20170405$$x3
000912537 536__ $$0G:(DE-Juel1)HDS-LEE-20190612$$aHDS LEE - Helmholtz School for Data Science in Life, Earth and Energy (HDS LEE) (HDS-LEE-20190612)$$cHDS-LEE-20190612$$x4
000912537 536__ $$0G:(DE-Juel1)CSD-SSD-20190612$$aCSD-SSD - Center for Simulation and Data Science (CSD) - School for Simulation and Data Science (SSD) (CSD-SSD-20190612)$$cCSD-SSD-20190612$$x5
000912537 536__ $$0G:(DE-Juel1)Helmholtz-SLNS$$aSLNS - SimLab Neuroscience (Helmholtz-SLNS)$$cHelmholtz-SLNS$$x6
000912537 536__ $$0G:(EU-Grant)800858$$aICEI - Interactive Computing E-Infrastructure for the Human Brain Project (800858)$$c800858$$fH2020-SGA-INFRA-FETFLAG-HBP$$x7
000912537 8564_ $$uhttps://juser.fz-juelich.de/record/912537/files/yegenoglu_eoyc_2022.pdf$$yOpenAccess
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000912537 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)161462$$aForschungszentrum Jülich$$b0$$kFZJ
000912537 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5111$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
000912537 9141_ $$y2022
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