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 *
bgka.mod *
CaBK.mod *
ccanl.mod *
Gfluct2.mod *
gskch.mod *
hyperde3.mod *
ichan2.mod *
LcaMig.mod *
nca.mod *
tca.mod *
bg.sh
DG500_M7.hoc *
dgnetactivity.jpg *
dgnettraces.jpg *
init.hoc
initorig.hoc *
modstat *
mosinit_orig.hoc *
out.std
parRI10sp.hoc
RI10sp.hoc
test1.sh *
time *
                            
TITLE hyperde3.mod  
 
COMMENT
Chen K, Aradi I, Thon N, Eghbal-Ahmadi M, Baram TZ, Soltesz I: Persistently
modified
h-channels after complex febrile seizures convert the seizure-induced
enhancement of
inhibition to hyperexcitability. Nature Medicine, 7(3) pp. 331-337, 2001.
(modeling by Ildiko Aradi, iaradi@uci.edu)
distal dendritic Ih channel kinetics for both HT and Control anlimals
ENDCOMMENT
 
UNITS {
        (mA) =(milliamp)
        (mV) =(millivolt)
        (uF) = (microfarad)
	(molar) = (1/liter)
	(nA) = (nanoamp)
	(mM) = (millimolar)
	(um) = (micron)
	FARADAY = 96520 (coul)
	R = 8.3134	(joule/degC)
}
 
? interface 
NEURON { 
SUFFIX hyperde3 
USEION hyf READ ehyf WRITE ihyf VALENCE 1
USEION hys READ ehys WRITE ihys VALENCE 1
USEION hyhtf READ ehyhtf WRITE ihyhtf VALENCE 1
USEION hyhts READ ehyhts WRITE ihyhts VALENCE 1
RANGE  ghyf, ghys, ghyhtf, ghyhts
RANGE ghyfbar, ghysbar, ghyhtfbar, ghyhtsbar
RANGE hyfinf, hysinf, hyftau, hystau
RANGE hyhtfinf, hyhtsinf, hyhtftau, hyhtstau, ihyf, ihys
}
 
INDEPENDENT {t FROM 0 TO 100 WITH 100 (ms)}
 
PARAMETER {
      v (mV) 
      celsius = 6.3 (degC)
      dt (ms) 

	ghyfbar (mho/cm2)
	ghysbar (mho/cm2)
	ehyf (mV)
	ehys (mV)
	ghyhtfbar (mho/cm2)
	ghyhtsbar (mho/cm2)
	ehyhtf (mV)
	ehyhts (mV)
}
 
STATE {
	hyf hys hyhtf hyhts
}
 
ASSIGNED {
         
  
	ghyf (mho/cm2)
 	ghys (mho/cm2)

	ghyhtf (mho/cm2)
	ghyhts (mho/cm2)

  
	ihyf (mA/cm2)
	ihys (mA/cm2)
	ihyhtf (mA/cm2)
	ihyhts (mA/cm2)

	hyfinf hysinf hyhtfinf hyhtsinf
 	hyftau (ms) hystau (ms) hyhtftau (ms) hyhtstau (ms)
	hyfexp hysexp hyhtfexp hyhtsexp     
} 

? currents
BREAKPOINT {

	SOLVE states

	ghyf = ghyfbar * hyf*hyf
	ihyf = ghyf * (v-ehyf)
	ghys = ghysbar * hys*hys
	ihys = ghys * (v-ehys)

	ghyhtf = ghyhtfbar * hyhtf* hyhtf
	ihyhtf = ghyhtf * (v-ehyhtf)
	ghyhts = ghyhtsbar * hyhts* hyhts
	ihyhts = ghyhts * (v-ehyhts)
		
		}
 
UNITSOFF
 
INITIAL {
	trates(v)
	
	hyf = hyfinf
      hys = hysinf
	hyhtf = hyhtfinf
	hyhts = hyhtsinf
	VERBATIM
	return 0;
	ENDVERBATIM
}

? states
PROCEDURE states() {	:Computes state variables m, h, and n 
        trates(v)	:      at the current v and dt.
        
        hyf = hyf + hyfexp*(hyfinf-hyf)
        hys = hys + hysexp*(hysinf-hys)
	  hyhtf = hyhtf + hyhtfexp*(hyhtfinf-hyhtf)
	  hyhts = hyhts + hyhtsexp*(hyhtsinf-hyhts)

        VERBATIM
        return 0;
        ENDVERBATIM
}
 
LOCAL q10

? rates
PROCEDURE rates(v) {  :Computes rate and other constants at current v.
                      :Call once from HOC to initialize inf at resting v.
        LOCAL  alpha, beta, sum
       q10 = 3^((celsius - 6.3)/10)
       
	:"hyf" FAST CONTROL Hype activation system
	hyfinf =  1 / (1 + exp( (v+91)/10 ))
	hyftau = 14.9 + 14.1 / (1+exp(-(v+95.2)/0.5))

	:"hys" SLOW CONTROL Hype activation system
	hysinf =  1 / (1 + exp( (v+91)/10 ))
	hystau = 80 + 172.7 / (1+exp(-(v+59.3)/-0.83))

		:"hyhtf" FAST HT Hypeht activation system
	hyhtfinf =  1 / (1 + exp( (v+87)/10 ))
	hyhtftau = 23.2 + 16.1 / (1+exp(-(v+91.2)/0.83))

		:"hyhts" SLOW HT Hypeht activation system
	hyhtsinf =  1 / (1 + exp( (v+87)/10 ))
	hyhtstau = 227.3 + 170.7*exp(-0.5*((v+80.4)/11)^2)
}
 
PROCEDURE trates(v) {  :Computes rate and other constants at current v.
                      :Call once from HOC to initialize inf at resting v.
	LOCAL tinc
      TABLE hyfinf, hyhtfinf, hyfexp, hyhtfexp, hyftau, hyhtftau, 
		hysinf, hyhtsinf, hysexp, hyhtsexp, hystau, hyhtstau	
	DEPEND dt, celsius FROM -120 TO 100 WITH 220
                           
	rates(v)	: not consistently executed from here if usetable_hh == 1
		: so don't expect the tau values to be tracking along with
		: the inf values in hoc

	       tinc = -dt * q10
        
        hyfexp = 1 - exp(tinc/hyftau)
	  hysexp = 1 - exp(tinc/hystau)
	  hyhtfexp = 1 - exp(tinc/hyhtftau)
	  hyhtsexp = 1 - exp(tinc/hyhtstau)
}
 
FUNCTION vtrap(x,y) {  :Traps for 0 in denominator of rate eqns.
        if (fabs(x/y) < 1e-6) {
                vtrap = y*(1 - x/y/2)
        }else{  
                vtrap = x/(exp(x/y) - 1)
        }
}
 
UNITSON


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