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The NEST Dry-Run Mo...
The NEST Dry-Run Mode : Efficient Dynamic Analysis of Neuronal Network Simulation Code
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- Kunkel, Susanne (författare)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST),Simulation Laboratory Neuroscience, Bernstein Facility for Simulation and Database Technology, Institute for Advanced Simulation, Jülich Aachen Research Alliance, Forschungszentrum Jülich, Jülich, Germany.
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- Schenck, Wolfram (författare)
- Simulation Laboratory Neuroscience, Bernstein Facility for Simulation and Database Technology, Institute for Advanced Simulation, Jülich Aachen Research Alliance, Forschungszentrum Jülich, Jülich, Germany; Faculty of Engineering and Mathematics, Bielefeld University of Applied Sciences, Bielefeld, Germany.
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(creator_code:org_t)
- 2017-06-28
- 2017
- Engelska.
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Ingår i: Frontiers in Neuroinformatics. - : Frontiers Media SA. - 1662-5196. ; 11
- 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
- NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Nyckelord
- profiling
- performance analysis
- memory footprint
- high-performance computing
- supercomputer
- large-scale simulation
- spiking neuronal networks
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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