Modular Supercomputing for Neuroscience

Suarez, Estela; Kunkel, Susanne; Plesser, Hans Ekkehard; Küsters, Anne; Lippert, Thomas

doi:10.1007/978-3-030-82427-3_5

Contribution to a conference proceedings/Contribution to a book

FZJ-2019-06093

Modular Supercomputing for Neuroscience

Suarez, E. (Corresponding author)FZJ* ; Kunkel, S. ; Küsters, A.FZJ* ; Plesser, H. E.FZJ* ; Lippert, T.FZJ*

2021
Springer International Publishing Cham
ISBN: 978-3-030-82426-6 (print), 978-3-030-82427-3 (electronic)

Brain-Inspired Computing / Amunts, Katrin (Editor) [https://orcid.org/0000-0001-5828-0867] ; Cham : Springer International Publishing, 2021, Chapter 5 ; ISSN: 0302-9743=1611-3349 ; ISBN: 978-3-030-82426-6=978-3-030-82427-3 ; doi:10.1007/978-3-030-82427-3
BrainComp 2019 - Workshop on Brain-Inspired Computing, Cetraro, Italy, 15 Jul 2019 - 19 Jul 2019 Cham : Springer International Publishing, Lecture Notes in Computer Science 12339, 63-80 (2021) [10.1007/978-3-030-82427-3_5]

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Please use a persistent id in citations: http://hdl.handle.net/2128/28352 doi:10.1007/978-3-030-82427-3_5

Abstract: The precise simulation of the human brain requires coupling different models in order to cover the different physiological and functional aspects of this extremely complex organ. Each of this brain models is implemented following specific mathematical and programming approaches, potentially leading to diverging computational behaviour and requirements. Such situation is the typical use case that can benefit from the Modular Supercomputing Architecture (MSA), which organizes heterogeneous computing resources at system level. This architecture and its corresponding software environment enable to run each part of an application or a workflow on the best suited hardware.This paper presents the MSA concept covering current hardware and software implementations, and describes how the neuroscientific workflow resulting of coupling the codes NEST and Arbor is being prepared to exploit the MSA.

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Appears in the scientific report 2021

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OpenAccess