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.
%0 Journal Article
%1 djurfeldt_run-time_2010
%A Djurfeldt, Mikael
%A Hjorth, Johannes
%A Eppler, Jochen M.
%A Dudani, Niraj
%A Helias, Moritz
%A Potjans, Tobias C.
%A Bhalla, Upinder S.
%A Diesmann, Markus
%A Hellgren Kotaleski, Jeanette
%A Ekeberg, Örjan
%D 2010
%K simulation
%N 1
%P 43--60
%R 10.1007/s12021-010-9064-z
%T Run-Time Interoperability Between Neuronal Network Simulators Based on the MUSIC Framework
%V 8
%X 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.
@article{djurfeldt_run-time_2010,
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.},
added-at = {2014-01-19T13:49:24.000+0100},
author = {Djurfeldt, Mikael and Hjorth, Johannes and Eppler, Jochen M. and Dudani, Niraj and Helias, Moritz and Potjans, Tobias C. and Bhalla, Upinder S. and Diesmann, Markus and Hellgren Kotaleski, Jeanette and Ekeberg, {\"O}rjan},
bdsk-url-1 = {http://dx.doi.org/10.1007/s12021-010-9064-z},
biburl = {https://www.bibsonomy.org/bibtex/24b57b59c25f0a4d763c8b133625264c8/neurokernel},
doi = {10.1007/s12021-010-9064-z},
interhash = {da1ba3afd1bd291f2627666a78cdf21c},
intrahash = {4b57b59c25f0a4d763c8b133625264c8},
issn = {1539-2791},
keywords = {simulation},
month = mar,
note = {{PMID:} 20195795 {PMCID:} 2846392},
number = 1,
pages = {43--60},
timestamp = {2014-01-19T13:49:24.000+0100},
title = {Run-Time Interoperability Between Neuronal Network Simulators Based on the {MUSIC} Framework},
volume = 8,
year = 2010
}