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dc.contributor.authorKayraklıoğlu, Engin
dc.contributor.authorEl-Ghazawi, Tarek A.
dc.contributor.authorBozkuş, Zeki
dc.date.accessioned2019-06-27T08:02:28Z
dc.date.available2019-06-27T08:02:28Z
dc.date.issued2015
dc.identifier.isbn978-1-5090-0154-5
dc.identifier.urihttps://hdl.handle.net/20.500.12469/627
dc.identifier.urihttps://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.79
dc.description.abstractNEural Simulation Tool(NEST) is a large scale spiking neuronal network simulator of the brain. In this work we present a CUDA(R) implementation of NEST. We were able to gain a speedup of factor 20 for the computational parts of NEST execution using a different data structure than NEST's default. Our partial implementation shows the potential gains and limitations of such possible port. We discuss possible novel approaches to be able to adapt generic spiking neural network simulators such as NEST to run on commodity or high-end GPGPUs.en_US]
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectBrain simulationen_US
dc.subjectCudaen_US
dc.subjectAcceleratorsen_US
dc.titleAccelerating Brain Simulations on Graphical Processing Unitsen_US
dc.typeconferenceObjecten_US
dc.identifier.startpage556en_US
dc.identifier.endpage560
dc.relation.journal2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computingen_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.identifier.wosWOS:000380514500078en_US
dc.identifier.doi10.1109/CIT/IUCC/DASC/PICOM.2015.79en_US
dc.identifier.scopus2-s2.0-84964199590en_US
dc.institutionauthorBozkuş, Zekien_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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