Run-Time Interoperability Between Neuronal Network Simulators Based on the MUSIC Framework

• MUSIC is an API allowing large scale neuron simulators using MPI internally to exchange data during runtime. We provide experiences from the adaptation of two neuronal network simulators of different kinds, NEST and MOOSE, to this API. 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. We conclude that MUSIC fulfills the design goals of being portable and simple to adapt to existing simulators. In addition, since the MUSIC API enforces independence between the applications, the multi-simulationcould 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.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Bioinformatics (hsv//eng)

Keyword

MUSIC

Large-scale simulation

Computer simulation

Computational neuroscience

Neuronal network models

Inter-operability

MPI

Parallel processing

Software engineering

Programvaruteknik

Publication and Content Type

ref (subject category)

art (subject category)