Run-time interoperability between neuronal network simulators based on the music framework

Djurfeldt, Mikael ; Hjorth, Johannes ; Eppler, Jochen M. ; Dudani, Niraj ; Helias, Moritz ; Potjans, Tobias C. ; Bhalla, Upinder S. ; Diesmann, Markus ; Kotaleski, Jeanette Hellgren ; Ekeberg, Orjan (2010) Run-time interoperability between neuronal network simulators based on the music framework Neuroinformatics, 8 (1). pp. 43-60. ISSN 1539-2791

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Official URL: http://www.springerlink.com/content/r6j425027lmv12...

Related URL: http://dx.doi.org/10.1007/s12021-010-9064-z

Abstract

MUSIC is a standard API allowing large scale neuron simulators to exchange data within a parallel computer during runtime. A pilot implementation of this API has been released as open source. We provide experiences from the implementation of MUSIC interfaces for two neuronal network simulators of different kinds, NEST and MOOSE. A multi-simulation of a cortico-striatal network model involving both simulators is performed, demonstrating how MUSIC can promote inter-operability between models written for different simulators and how these can be re-used to build a larger model system. Benchmarks show that the MUSIC pilot implementation provides efficient data transfer in a cluster computer with good scaling. We conclude that MUSIC fulfills the design goal that it should be simple to adapt existing simulators to use MUSIC. In addition, since the MUSIC API enforces independence of the applications, the multi-simulation could be built from pluggable component modules without adaptation of the components to each other in terms of simulation time-step or topology of connections between the modules.

Item Type:Article
Source:Copyright of this article belongs to Springer-Verlag.
Keywords:MUSIC; Large-scale Simulation; Computer Simulation; Computational Neuroscience; Neuronal Network Models; Inter-operability; MPI; Parallel Processing
ID Code:4423
Deposited On:18 Oct 2010 14:05
Last Modified:16 May 2011 15:09

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