TY  - CONF
AU  - Hahne, Jan
AU  - Helias, Moritz
AU  - Kunkel, Susanne
AU  - Igarashi, Jun
AU  - Kitayama, Itaru
AU  - Wylie, Brian
AU  - Bolten, Matthias
AU  - Frommer, Andreas
AU  - Diesmann, Markus
TI  - Including Gap Junctions into Distributed Neuronal Network Simulations
VL  - 10087
CY  - Cham
PB  - Springer International Publishing
M1  - FZJ-2017-00070
SN  - 978-3-319-50861-0 (print)
T2  - Lecture Notes in Computer Science
SP  - 43 - 57
PY  - 2016
AB  - Contemporary simulation technology for neuronal networks enables the simulation of brain-scale networks using neuron models with a single or a few compartments. However, distributed simulations at full cell density are still lacking the electrical coupling between cells via so called gap junctions. This is due to the absence of efficient algorithms to simulate gap junctions on large parallel computers. The difficulty is that gap junctions require an instantaneous interaction between the coupled neurons, whereas the efficiency of simulation codes for spiking neurons relies on delayed communication. In a recent paper [15] we describe a technology to overcome this obstacle. Here, we give an overview of the challenges to include gap junctions into a distributed simulation scheme for neuronal networks and present an implementation of the new technology available in the NEural Simulation Tool (NEST 2.10.0). Subsequently we introduce the usage of gap junctions in model scripts as well as benchmarks assessing the performance and overhead of the technology on the supercomputers JUQUEEN and K computer.
T2  - International Workshop on Brain-Inspired Computing
CY  - 6 Jul 2015 - 10 Jul 2015, Cetraro (Italy)
Y2  - 6 Jul 2015 - 10 Jul 2015
M2  - Cetraro, Italy
LB  - PUB:(DE-HGF)8 ; PUB:(DE-HGF)7
DO  - DOI:10.1007/978-3-319-50862-7_4
UR  - https://juser.fz-juelich.de/record/825758
ER  -