Cargando…

Supercomputers Ready for Use as Discovery Machines for Neuroscience

NEST is a widely used tool to simulate biological spiking neural networks. Here we explain the improvements, guided by a mathematical model of memory consumption, that enable us to exploit for the first time the computational power of the K supercomputer for neuroscience. Multi-threaded components f...

Descripción completa

Detalles Bibliográficos
Autores principales:	Helias, Moritz, Kunkel, Susanne, Masumoto, Gen, Igarashi, Jun, Eppler, Jochen Martin, Ishii, Shin, Fukai, Tomoki, Morrison, Abigail, Diesmann, Markus
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2012
Materias:	Neuroscience
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3486988/ https://www.ncbi.nlm.nih.gov/pubmed/23129998 http://dx.doi.org/10.3389/fninf.2012.00026

Ejemplares similares

From laptops to supercomputers: a single highly scalable code base for spiking neuronal network simulations
por: Kunkel, Susanne, et al.
Publicado: (2013)

Spiking network simulation code for petascale computers
por: Kunkel, Susanne, et al.
Publicado: (2014)

Fail-safe detection of threshold crossings of linear integrate-and-fire neuron models in time-driven simulations
por: Kunkel, Susanne, et al.
Publicado: (2011)

A General and Efficient Method for Incorporating Precise Spike Times in Globally Time-Driven Simulations
por: Hanuschkin, Alexander, et al.
Publicado: (2010)

Meeting the Memory Challenges of Brain-Scale Network Simulation
por: Kunkel, Susanne, et al.
Publicado: (2012)

Efficient Communication in Distributed Simulations of Spiking Neuronal Networks With Gap Junctions
por: Jordan, Jakob, et al.
Publicado: (2020)

PyNEST: A Convenient Interface to the NEST Simulator
por: Eppler, Jochen Martin, et al.
Publicado: (2009)

A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations
por: Hahne, Jan, et al.
Publicado: (2015)

Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers
por: Jordan, Jakob, et al.
Publicado: (2018)

Corrigendum: Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers
por: Jordan, Jakob, et al.
Publicado: (2018)

Lectures in Supercomputational Neurosciences: Dynamics in Complex Brain Networks
por: Graben, Peter beim, et al.
Publicado: (2008)

Random wiring limits the development of functional structure in large recurrent neuronal networks
por: Kunkel, Susanne, et al.
Publicado: (2010)

Limits to the Development of Feed-Forward Structures in Large Recurrent Neuronal Networks
por: Kunkel, Susanne, et al.
Publicado: (2011)

Run-Time Interoperability Between Neuronal Network Simulators Based on the MUSIC Framework
por: Djurfeldt, Mikael, et al.
Publicado: (2010)

Towards a unified theory of correlations in recurrent neural networks
por: Helias, Moritz, et al.
Publicado: (2011)

Neurons hear their echo
por: Helias, Moritz, et al.
Publicado: (2010)

The transfer function of the LIF model: from white to filtered noise
por: Schuecker, Jannis, et al.
Publicado: (2014)

Recurrence and external sources differentially shape network correlations
por: Helias, Moritz, et al.
Publicado: (2013)

The Correlation Structure of Local Neuronal Networks Intrinsically Results from Recurrent Dynamics
por: Helias, Moritz, et al.
Publicado: (2014)

Functional consequences of non-equilibrium dynamics caused by antisymmetric and symmetric learning rules
por: Grytskyy, Dmytro, et al.
Publicado: (2015)

Identifying Anatomical Origins of Coexisting Oscillations in the Cortical Microcircuit
por: Bos, Hannah, et al.
Publicado: (2016)

A Compositionality Machine Realized by a Hierarchic Architecture of Synfire Chains
por: Schrader, Sven, et al.
Publicado: (2011)

CERN's supercomputer
Publicado: (1988)

Supercomputational science
por: Evans, R, et al.
Publicado: (1990)

Europese supercomputer
Publicado: (1994)

Supercomputing '97
por: Collective
Publicado: (1997)

Supercomputer architecture
por: Schneck, Paul B
Publicado: (1987)

Supercomputers and their use
por: Lazou, Christopher
Publicado: (1986)

Seminar on Supercomputing
por: Kanada, Y, et al.
Publicado: (1988)

Instantaneous Non-Linear Processing by Pulse-Coupled Threshold Units
por: Helias, Moritz, et al.
Publicado: (2010)

Spike-Timing Dependence of Structural Plasticity Explains Cooperative Synapse Formation in the Neocortex
por: Deger, Moritz, et al.
Publicado: (2012)

Equilibrium and Response Properties of the Integrate-and-Fire Neuron in Discrete Time
por: Helias, Moritz, et al.
Publicado: (2010)

Finite Post Synaptic Potentials Cause a Fast Neuronal Response
por: Helias, Moritz, et al.
Publicado: (2011)

Decorrelation of low-frequency neural activity by inhibitory feedback
por: Tetzlaff, Tom, et al.
Publicado: (2010)

Taming the model zoo: a unified view on correlations in recurrent networks
por: Grytskyy, Dmytro, et al.
Publicado: (2012)

A unified view on weakly correlated recurrent networks
por: Grytskyy, Dmytro, et al.
Publicado: (2013)

Decorrelation of Neural-Network Activity by Inhibitory Feedback
por: Tetzlaff, Tom, et al.
Publicado: (2012)

Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and Correlations
por: van Albada, Sacha Jennifer, et al.
Publicado: (2015)

Identifying and exploiting the anatomical origin of population rate oscillations in multi-layered spiking networks
por: Bos, Hannah, et al.
Publicado: (2015)

Limits to the scalability of cortical network models
por: van Albada, Sacha J, et al.
Publicado: (2015)

Cannot write session to /tmp/vufind_sessions/sess_02ufdj8afrfsecfdgifojfqdn0