Parallel network simulations with NEURON (Migliore et al 2006)

 Download zip file   Auto-launch 
Help downloading and running models
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];
/
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
                            
9
1
50	31118	98.6900	0.4899
2
125	31118	39.1900	0.4208
125	33960	79.5400	0.5719
3
250	31118	19.5500	0.4801
250	33960	40.0300	0.4832
250	69529	85.2400	0.7779
3
500	31118	9.7900	0.5051
500	33960	19.6100	0.4718
500	69529	42.4900	0.7584
4
1000	31118	5.5600	0.9549
1000	33960	9.8800	0.6240
1000	69529	21.3600	0.8882
1000	294974	62.4000	2.5212
4
2000	31118	4.0300	1.6343
2000	33960	5.6200	0.9636
2000	69529	11.2500	1.2898
2000	294974	33.6100	3.2577
1
5000	31118	4.88	3.8354
4
4000	33960	4.0900	1.6713
4000	69529	7.1500	2.1151
4000	294974	19.6200	4.8258
4000	844175	63.7900	11.4256
4
8000	33960	4.65	3.3915
8000	69529	6.4700	3.8500
8000	294974	15.7400	8.2277
8000	844175	46.1300	18.7788

Fitting results for exchangeTime = a + b*nspike
#cpu  a   b
50
125
250  0.20  8.1e-6
500  0.20  8.3e-6
1000 0.38  7.3e-6
2000 0.67  8.7e-6
4000 1.27  1.2e-5
8000 2.62  1.9e-5

Loading data, please wait...