Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers
- Language
-
Englisch
- Identifier
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1169214428
- Contributor
-
Jordan, Jakob
Ippen, Tammo
Helias, Moritz
Kitayama, Itaru
Sato, Mitsuhisa
Igarashi, Jun
Diesmann, Markus
Kunkel, Susanne
- DOI
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10.18154/RWTH-2018-222272
- URN
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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26.01.2023, 1:53 PM CET
Data provider
This object is provided by:
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Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Jordan, Jakob
- Ippen, Tammo
- Helias, Moritz
- Kitayama, Itaru
- Sato, Mitsuhisa
- Igarashi, Jun
- Diesmann, Markus
- Kunkel, Susanne
Other Objects (12)
Corrigendum: Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers
Communication through resonance in spiking neuronal networks
Nonlinear dynamics of interacting spiking neuronal networks
Modeling and simulation of multi-scale spiking neuronal networks
Extremely scalable cloud applications made easy using the Azure service fabric actor model
How adaptation currents change threshold, gain, and variability of neuronal spiking
Efficient Communication in Distributed Simulations of Spiking Neuronal Networks With Gap Junctions
Interpreting the local field potential as a reflection of cooperative neuronal spiking dynamics
Interplay between graph topology and correlations of third order in spiking neuronal networks
Dynamics of competition between subnetworks of spiking neuronal networks in the balanced state
A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations
Texte von Laptop
Corrigendum: Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers
Communication through resonance in spiking neuronal networks
Nonlinear dynamics of interacting spiking neuronal networks
Modeling and simulation of multi-scale spiking neuronal networks
Extremely scalable cloud applications made easy using the Azure service fabric actor model
How adaptation currents change threshold, gain, and variability of neuronal spiking
Efficient Communication in Distributed Simulations of Spiking Neuronal Networks With Gap Junctions
Interpreting the local field potential as a reflection of cooperative neuronal spiking dynamics
Interplay between graph topology and correlations of third order in spiking neuronal networks
Dynamics of competition between subnetworks of spiking neuronal networks in the balanced state
A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations
Texte von Laptop
Corrigendum: Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers
Communication through resonance in spiking neuronal networks
Nonlinear dynamics of interacting spiking neuronal networks
Modeling and simulation of multi-scale spiking neuronal networks
Extremely scalable cloud applications made easy using the Azure service fabric actor model
How adaptation currents change threshold, gain, and variability of neuronal spiking
Efficient Communication in Distributed Simulations of Spiking Neuronal Networks With Gap Junctions
Interpreting the local field potential as a reflection of cooperative neuronal spiking dynamics
Interplay between graph topology and correlations of third order in spiking neuronal networks
Dynamics of competition between subnetworks of spiking neuronal networks in the balanced state
A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations