Translating network models to parallel hardware in NEURON (Hines and Carnevale 2008)

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Accession:96444
Shows how to move a working network model written in NEURON from a serial processor to a parallel machine in such a way that the final result will produce numerically identical results on either serial or parallel hardware.
Reference:
1 . Hines ML, Carnevale NT (2008) Translating network models to parallel hardware in NEURON. J Neurosci Methods 169:425-55 [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):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Simplified Models; Methods;
Implementer(s): Carnevale, Ted [Ted.Carnevale at Yale.edu]; Hines, Michael [Michael.Hines at Yale.edu];
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HinesCarnevaleJNM2007
random
ring
readme.txt
mosinit.hoc
                            
//moddir random
{load_file("nrngui.hoc")}
proc launch() {
	PWManager[0].hide(1)
	chdir($s1)
	load_file($s2)
}

{
xpanel("Launch")
xlabel("Prints spike train to stdout")
xbutton("Ring (Serial)", "launch(\"ring\", \"ringser.hoc\")")
xbutton("Ring (Parallel)", "launch(\"ring\", \"ringpar.hoc\")")
xbutton("Random (Serial)", "launch(\"random\", \"ran3ser.hoc\")")
xbutton("Random (Parallel)", "launch(\"random\", \"ran3par.hoc\")")
xpanel()
}

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