Run-time interoperability between neuronal network simulators based on the MUSIC framework.
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.
Djurfeldt
Mikael
M
School of Computer Science and Communication, Royal Institute of Technology, Stockholm, Sweden. mikael@djurfeldt.com
Hjorth
Johannes
J
Eppler
Jochen M
JM
Dudani
Niraj
N
Helias
Moritz
M
Potjans
Tobias C
TC
Bhalla
Upinder S
US
Diesmann
Markus
M
Kotaleski
Jeanette Hellgren
JH
Ekeberg
Orjan
O
D000200:Action Potentials; D000818:Animals; D002540:Cerebral Cortex / Q000166:cytology / Q000502:physiology*; D003198:Computer Simulation; D003342:Corpus Striatum / Q000166:cytology; D006801:Humans; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009434:Neural Pathways / Q000502:physiology; D009474:Neurons / Q000502:physiology; D012984:Software; D014584:User-Computer Interface