Efficient Communication in Distributed Simulations of Spiking Neuronal Networks With Gap Junctions

Frontiers in Neuroinformatics, vol. 14, pp. 12

Abstract

Investigating the dynamics and function of large-scale spiking neuronal networks with realistic numbers of synapses is made possible today by state-of-the-art simulation code that scales to the largest contemporary supercomputers. However, simulations that involve electrical interactions, also called gap junctions, besides chemical synapses scale only poorly due to a communication scheme that collects global data on each compute node. In comparison to chemical synapses, gap junctions are far less abundant. To improve scalability we exploit this sparsity by integrating an existing framework for continuous interactions with a recently proposed directed communication scheme for spikes. Using a reference implementation in the NEST simulator we demonstrate excellent scalability of the integrated framework, accelerating large-scale simulations with gap junctions by more than an order of magnitude. This allows, for the first time, the efficient exploration of the interactions of chemical and electrical coupling in large-scale neuronal networks models with natural synapse density distributed across thousands of compute nodes.

Authors 4

1. Jakob Jordan corresponding

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · University of Bern

   Affiliation as printed

   Department of Physiology, University of Bern, Bern, Switzerland

   Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany

   Institute of Neuroscience and Medicine (INM-6), Jülich Research Centre, Jülich, Germany

   JARA Institute Brain Structure Function Relationship (INM-10), Jülich Research Centre, Jülich, Germany

2. Moritz Helias Aachen Department of Physics Faculty 1

   RWTH Aachen University · Forschungszentrum Jülich · Jülich Aachen Research Alliance

   Affiliation as printed

   Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany

   Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany

   Institute of Neuroscience and Medicine (INM-6), Jülich Research Centre, Jülich, Germany

   JARA Institute Brain Structure Function Relationship (INM-10), Jülich Research Centre, Jülich, Germany

3. Markus Diesmann Aachen Department of Psychiatry, Psychotherapy and Psychosomatics Medical Faculty Department of Physics Faculty 1

   RWTH Aachen University · Forschungszentrum Jülich · Jülich Aachen Research Alliance

   Affiliation as printed

   Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany

   Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany

   Institute for Advanced Simulation (IAS-6), Jülich Research Centre, Jülich, Germany

   Institute of Neuroscience and Medicine (INM-6), Jülich Research Centre, Jülich, Germany

   JARA Institute Brain Structure Function Relationship (INM-10), Jülich Research Centre, Jülich, Germany

4. Susanne Kunkel

   Norwegian University of Life Sciences

   Affiliation as printed

   Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway