Cell splitting in neural networks extends strong scaling (Hines et al. 2008)

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Accession:97917
Neuron tree topology equations can be split into two subtrees and solved on different processors with no change in accuracy, stability, or computational effort; communication costs involve only sending and receiving two double precision values by each subtree at each time step. Application of the cell splitting method to two published network models exhibits good runtime scaling on twice as many processors as could be effectively used with whole-cell balancing.
Reference:
1 . Hines M, Eichner H, Schuermann F (2008) Neuron splitting in compute-bound parallel network simulations enables runtime scaling with twice as many processors J Comput Neurosci 25(1):203-210 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Generic;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Methods;
Implementer(s): Hines, Michael [Michael.Hines at Yale.edu];
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splitcell
pardentategyrus
readme.html *
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ccanl.mod *
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hyperde3.mod *
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tca.mod *
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init.hoc
initorig.hoc *
modstat *
mosinit_orig.hoc *
out.std
parRI10sp.hoc
RI10sp.hoc
test1.sh *
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TITLE T-calcium channel From Migliore CA3
: T-type calcium channel


UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)

	FARADAY = 96520 (coul)
	R = 8.3134 (joule/degC)
	KTOMV = .0853 (mV/degC)
}

PARAMETER {
	v (mV)
	celsius = 6.3	(degC)
	gcatbar=.003 (mho/cm2)
	cai (mM)
	cao (mM)
}


NEURON {
	SUFFIX cat
	USEION tca READ etca WRITE itca VALENCE 2
	USEION ca READ cai, cao VALENCE 2
        RANGE gcatbar,cai, itca, etca
}

STATE {
	m h 
}

ASSIGNED {
	itca (mA/cm2)
        gcat (mho/cm2)
	etca (mV)
}

INITIAL {
      m = minf(v)
      h = hinf(v)
	VERBATIM
	cai=_ion_cai;
	ENDVERBATIM
}

BREAKPOINT {
	SOLVE states METHOD cnexp
	gcat = gcatbar*m*m*h
	itca = gcat*ghk(v,cai,cao)

}

DERIVATIVE states {	: exact when v held constant
	m' = (minf(v) - m)/m_tau(v)
	h' = (hinf(v) - h)/h_tau(v)
}


FUNCTION ghk(v(mV), ci(mM), co(mM)) (mV) {
        LOCAL nu,f

        f = KTF(celsius)/2
        nu = v/f
        ghk=-f*(1. - (ci/co)*exp(nu))*efun(nu)
}

FUNCTION KTF(celsius (DegC)) (mV) {
        KTF = ((25./293.15)*(celsius + 273.15))
}


FUNCTION efun(z) {
	if (fabs(z) < 1e-4) {
		efun = 1 - z/2
	}else{
		efun = z/(exp(z) - 1)
	}
}

FUNCTION hinf(v(mV)) {
	LOCAL a,b
	TABLE FROM -150 TO 150 WITH 200
	a = 1.e-6*exp(-v/16.26)
	b = 1/(exp((-v+29.79)/10)+1)
	hinf = a/(a+b)
}

FUNCTION minf(v(mV)) {
	LOCAL a,b
	TABLE FROM -150 TO 150 WITH 200
        
	a = 0.2*(-1.0*v+19.26)/(exp((-1.0*v+19.26)/10.0)-1.0)
	b = 0.009*exp(-v/22.03)
	minf = a/(a+b)
}

FUNCTION m_tau(v(mV)) (ms) {
	LOCAL a,b
	TABLE FROM -150 TO 150 WITH 200
	a = 0.2*(-1.0*v+19.26)/(exp((-1.0*v+19.26)/10.0)-1.0)
	b = 0.009*exp(-v/22.03)
	m_tau = 1/(a+b)
}

FUNCTION h_tau(v(mV)) (ms) {
	LOCAL a,b
        TABLE FROM -150 TO 150 WITH 200
	a = 1.e-6*exp(-v/16.26)
	b = 1/(exp((-v+29.79)/10.)+1.)
	h_tau = 1/(a+b)
}

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