Parallel network simulations with NEURON (Migliore et al 2006)

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Accession:64229
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.
Reference:
1 . Migliore M, Cannia C, Lytton WW, Markram H, Hines ML (2006) Parallel Network Simulations with NEURON. J Comp Neurosci 21:110-119 [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): Methods;
Implementer(s): Hines, Michael [Michael.Hines at Yale.edu];
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netmod
parscalebush
AMPA.mod *
arhRT03.mod *
cadecay.mod
cadRT03.mod
cah.mod
calRT03.mod
catRT03.mod *
GABAa.mod *
GABAb.mod *
intf.mod
k2RT03.mod *
kahpRT03.mod
kaRT03.mod *
kca.mod *
kcRT03.mod
kdr.mod
kdrp.mod
kdrRT03.mod *
kmRT03.mod *
misc.mod
myfit.mod
na.mod
nafRT03.mod *
nap.mod
napRT03.mod *
NMDA.mod *
nstim.mod
stats.mod
vecst.mod
batch.hoc
bg
bg_cvode.inc
boltz_cvode.inc
geneval_cvode.inc
geom.hoc
init.hoc
netcon.inc
network.hoc
nqsnet.hoc
nspike.dat
params.hoc
parnetwork.hoc
parnqsnet.hoc
perfrun.hoc
prebatch_.hoc
run.hoc
spkplt.hoc *
x_vs_nspike.hoc
                            
// $Id: network.hoc,v 1.2 2006/02/08 11:59:39 hines Exp $

//* network parameters
scale=1
{fpnum = scale*100 idfp=0}
{tpnum = scale*300 idtp=idfp+fpnum}
{b5num = scale*100 idb5=idtp+tpnum}
{stimnum=1  idstim=idb5+b5num}
allcells = fpnum+tpnum+b5num+stimnum
{numc[FP]=fpnum numc[TP]=tpnum numc[B5]=b5num numc[SM]=stimnum}
{ix[FP]=idfp ix[TP]=idtp ix[B5]=idb5 ix[SM]=idstim}
objref cells,cell,fp[fpnum],tp[tpnum],bas5[b5num],nstim,ce,c[CTYPi]
func fpid () { return idfp+$1 }
func tpid () { return idtp+$1 }
func b5id () { return idb5+$1 }
func smid () { return idstim+$1 }
func ctype () { // get cell type from gid
  if ($1>=idfp && $1<idtp) return FP
  if ($1>=idtp && $1<idb5) return TP
  if ($1>=idb5 && $1<idstim) return B5
  if ($1>=idstim && $1<allcells) return SM
  printf("ctype INTERR\n") return -1
}
obfunc cobj () { // get the cell form the gid
  if ($1>=idfp && $1<idtp) return fp[$1-idfp]
  if ($1>=idtp && $1<idb5) return tp[$1-idtp]
  if ($1>=idb5 && $1<idstim) return bas5[$1-idb5]
  if ($1>=idstim && $1<allcells) return nstim // only 1
  printf("cell INTERR\n") return nil
}

//* connectivity values
for ii=0,CTYPi-1 for jj=0,CTYPi-1 for kk=0,STYPi-1 pmat[ii][jj][kk]=0.
pmat[FP][FP][EX] = 0.1
pmat[FP][TP][EX] = 0.1
pmat[TP][FP][EX] = 0.1
pmat[TP][TP][EX] = 0.1
pmat[FP][B5][AM] = 0.1
pmat[TP][B5][AM] = 0.1
pmat[B5][FP][GA] = 0.12
pmat[B5][FP][GB] = 0.03
pmat[B5][TP][GA] = 0.15
pmat[B5][TP][GB] = 0.03
pmat[SM][FP][E2] = 0.8
pmat[SM][TP][E2] = 0.8
pmat[SM][B5][E2] = 0.7

wmat[FP][FP][AM] = 0.002/scale
wmat[FP][FP][NM] = 0.001/scale
wmat[FP][TP][AM] = 0.002/scale
wmat[FP][TP][NM] = 0.0005/scale
wmat[FP][B5][AM] = 0.001/scale
wmat[TP][FP][AM] = 0.002/scale
wmat[TP][FP][NM] = 0.001/scale
wmat[TP][TP][AM] = 0.001/scale
wmat[TP][TP][NM] = 0.0005/scale
wmat[TP][B5][AM] = 0.001/scale
wmat[B5][FP][GA] = 0.004/scale
wmat[B5][FP][GB] = 0.00015/scale
wmat[B5][TP][GA] = 0.015/scale
wmat[B5][TP][GB] = 0.0004/scale
wmat[SM][FP][E2] = 0.06/scale
wmat[SM][TP][E2] = 0.05/scale
wmat[SM][B5][E2] = 0.02/scale

celln=-1
ce=new List()

//* procedures
obfunc create_cell () { localobj s
  celln+=1
  s=new String()
  sprint(s.s,"ce.append(%s)",$s1)
  execute(s.s)
  return ce.object(ce.count-1)
}

for i = 0, fpnum-1 { // fp[i] = new Pyramidal(i,30)
  sprint(tstr,"new Pyramidal(%d,30)",i)
  fp[i]=create_cell(tstr)
}

for i = 0, tpnum-1 { // tp[i] = new Pyramidal2(i,30)
  sprint(tstr,"new Pyramidal2(%d,30)",i)
  tp[i]=create_cell(tstr)
}

for i = 0, b5num-1 { // bas5[i] = new Basket(i,30) 
  sprint(tstr,"new Basket(%d,30)",i)
  bas5[i]=create_cell(tstr)
}

nstim=create_cell("new SStim()")

proc nc_append () { 
  if (ce.o(PR).fflag) {
    ncl.append(new NetCon(ce.o(PR).pp,ce.o(PO).synlist.o(SID),-10,DEL,WT))
  } else {
    ce.o(PR).soma ncl.append(new NetCon(&v(0.5),ce.o(PO).synlist.o(SID),-10,DEL,WT))
  }
}

// sp=new NQS("data/net05jul29.nqs")
PR=PO=SID=WT=DEL=0
proc connall () {  local x,y,z,ii,sn
  sn=0
  for case(&y,FP,TP,B5) for case(&x,SM,FP,TP,B5) for case(&z,AM,GA,GB,EX,E2) {
    sn+=pmat[x][y][z]*numc[x]*numc[y] } // how many synapses -- del numc[y] for mult CPU
  if (myid == 0) printf("Expect %d synapses\n",round(sn))
  sp[2].pad(1.1*sn) // big enough
  sp[2].clear // resize to 0
  for ii=0,allcells-1 { // outer loop iterates through all postsyn cells
    if (myid == 0) if (ii%100==0) printf("%d ",ii)
    y=ctype(ii)
    for case(&x,SM,FP,TP,B5) for case(&z,AM,GA,GB,EX,E2) {
      if (pmat[x][y][z]!=0) {
        mkpomat(x,y,z,ii) 
        sp[2].grow(sp)
      }
    }
  }
  rdsp(sp[2])
}

proc rdsp () {
  for ii=0,$o1.size(1)-1 {
    PR=$o1.v[0].x[ii] PO=$o1.v[1].x[ii] SID=$o1.v[2].x[ii]
    WT=$o1.v[3].x[ii] DEL=$o1.v[4].x[ii]
    nc_append()
  }
}

connall()

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