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Extremely Scalable Spiking Neuronal Network Simulation Code : From Laptops to Exascale Computers
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Jordan, Jakob (författare)
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Ippen, Tammo (författare)
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Helias, Moritz (författare)
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Kitayama, Itaru (författare)
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Sato, Mitsuhisa (författare)
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Igarashi, Jun (författare)
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- Diesmann, Markus (författare)
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany;Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany;Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany
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- Kunkel, Susanne (författare)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST),Simulation Laboratory Neuroscience – Bernstein Facility for Simulation and Database Technology, Jülich Research Centre, Jülich, Germany
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(creator_code:org_t)
- 2018-02-16
- 2018
- Engelska.
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Ingår i: Frontiers in Neuroinformatics. - : Frontiers Media SA. - 1662-5196. ; 12
- Relaterad länk:
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https://doi.org/10.3...
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https://www.frontier...
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https://urn.kb.se/re...
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https://doi.org/10.3...
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Abstract
Ämnesord
Stäng
- State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Nyckelord
- supercomputer
- large-scale simulation
- parallel computing
- spiking neuronal network
- exascale computing
- computational neuroscience
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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