Event Abstract

NEST 2: a parallel simulator for large neuronal networks

  • 1 RIKEN Brain Science Institute, Japan
  • 2 Honda Research Institute Europe GmbH, Germany
  • 3 Norwegian University of Life Sciences, Norway

NEST is a simulation environment for large heterogeneous networks of point-neuron models or neuron models with a small number of compartments. It supports spike based as well as continuous (e.g. rate, currents) interaction between the nodes of the network.

We present NEST 2 with PyNEST, a Python-based user interface (www.python.org), which makes it easier to learn and use NEST. Together with analysis packages like Scientific Python (www.scipy.org), users can now simulate networks and analyze results in a single interactive Python session. Pre-releases of NEST 2 have already been used with great success and appreciation at European summer schools since 2007.

Other new features of NEST 2 include support for synaptic plasticity, a wide range of model neurons, and parallel simulation on multi-processor (core) computers as well as computer clusters, with excellent scaling properties up to thousands of processors. Users can add new neuron and synapse models, as well as new connection and analysis functions, by writing their own NEST modules in C++.

We will demonstrate the capabilities of NEST 2 and invite visitors to try it interactively. For more information, please see the Scholarpedia article on NEST at http://www.scholarpedia.org/article/NEST.

NEST is released under an open source license for non-commercial use.

Conference: Neuroinformatics 2008, Stockholm, Sweden, 7 Sep - 9 Sep, 2008.

Presentation Type: Oral Presentation

Topic: Live Demonstrations

Citation: Diesmann M, Eppler JM, Gewaltig M, Morrison A and Plesser HE (2008). NEST 2: a parallel simulator for large neuronal networks. Front. Neuroinform. Conference Abstract: Neuroinformatics 2008. doi: 10.3389/conf.neuro.11.2008.01.137

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Received: 28 Jul 2008; Published Online: 28 Jul 2008.

* Correspondence: Markus Diesmann, RIKEN Brain Science Institute, Tokyo, Japan, nemoABS01@frontiersin.org