Parallel network simulations with NEURON (Migliore et al 2006)

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The NEURON simulation environment has been extended to support parallel network simulations. The performance of three published network models with very different spike patterns exhibits superlinear speedup on Beowulf clusters.
1 . Migliore M, Cannia C, Lytton WW, Markram H, Hines ML (2006) Parallel network simulations with NEURON. J Comput Neurosci 21:119-29 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Gap Junctions:
Simulation Environment: NEURON;
Model Concept(s): Methods;
Implementer(s): Hines, Michael [Michael.Hines at];
// NetGUI default section. Artificial cells, if any, are located here.
  create acell_home_
  access acell_home_

//Network cell templates
//Artificial cells
//   IF_IntervalFire

// modified from NetGUI hoc output to add the random interval

begintemplate IF_IntervalFire
public pp, connect2target, x, y, z, position, is_art, r, hseed, ranstart
external acell_home_
objref pp, r
proc init() {
  hseed = $1
  acell_home_ pp = new IntervalFire(.5)
  r = new Random()
func ranstart() {
  return r.MCellRan4(hseed)
func is_art() { return 1 }
proc connect2target() { $o2 = new NetCon(pp, $o1) }
proc position(){x=$1  y=$2  z=$3}
endtemplate IF_IntervalFire

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