Question icon
Your Current Search
Choose below to refine your search
Research Topic
Download abstract book

Download the NI2012 abstract book here. The page numbers in the index are clickable for easy browsing.

 

Combining simulator independent network descriptions with run-time interoperability based on PyNN and MUSIC

Filed under:
1.54545454545

Jochen Martin Eppler (Institute of Neuroscience and Medicine (INM-6), Computational and Systems Neuroscience, Research Center Jülich), Mikael Djurfeldt (PDC Center for High Performance Computing, School of Computer Science and Communication, KTH), Eilif Muller (Blue Brain Project, Ecole Polytechnique Fédérale de Lausanne (EPFL)), Markus Diesmann (Institute of Neuroscience and Medicine (INM-6), Computational and Systems Neuroscience, Research Center Jülich), Andrew Davison (Unité de Neurosciences Intégratives et Computationnelles (UNIC), Centre National de la Recherche Scientifique)

The Multi-Simulation Coordinator (MUSIC) is an INCF funded standard and library implementation that allows neuronal simulators or programs for stimulus generation, data analysis, or visualization to exchange data at run-time. To set up such a multi-simulation consisting of several simulators, the user has to specify the different parts of the network model in the native description or scripting languages of the respective simulators, and provide a configuration file that tells MUSIC what data has to be transported between which applications.

This approach works well for connecting multiple already existing models written for different simulators. An example for using this is given in [1]. However, this approach requires the user to be familiar with the configuration languages of all simulators involved in the simulation.

To alleviate this problem, we extended the application programming interface (API) of PyNN [2], to enable the simulator-independent specification of multi-simulator neuronal network models.

In this contribution, we provide a detailed description of necessary changes to the existing software packages (i.e. NEST [3], NEURON [4] and PyNN) and the user experience for our prototype implementation of this API. The API allows the user to set up the network model using all of PyNN's high-level language constructs and abstracts away from the technical aspects of using the simulator's native MUSIC interfaces and setting up the multi-simulation.

Acknowledgments:
Partially supported by the Helmholtz Alliance on Systems Biology, the Next-Generation Supercomputer Project of MEXT, and EU Grant 269921 (BrainScaleS).

References:
[1] Mikael Djurfeldt et al (2010) Run-Time Interoperability between Neuronal Network Simulators based on the MUSIC Framework. Neuroinformatics 8:43–60. doi:10.1007/s12021-010-9064-z
[2] Andrew Davison et al (2008) PyNN: A common interface for neuronal network simulators. Front. Neuroinform. 2:11. doi:10.3389/neuro.11.011.2008
[3] Marc-Oliver Gewaltig and Markus Diesmann (2007) NEST (Neural Simulation Tool), Scholarpedia 2 (4), p. 1430.
[4] Michael Hines, Ted Carnevale (1997) The NEURON simulation environment. Neural Comp. 9: 178–1209.
Preferred presentation format: Poster
Topic: Large scale modeling

Filed under:
Andrew Davison
Andrew Davison says:
May 03, 2012 02:36 PM
Not rating this one as I am a co-author