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imp_bench_core_neuron_main.hoc~
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//{chdir("./hoc/bench")}
{load_file("nrngui.hoc")}
load_file("stdrun.hoc")
CACHE_EFFICIENT=1
if (!name_declared("MODEL")) { MODEL=0 }
if (!name_declared("NSTIM_POS")) { NSTIM_POS=1 }
if (!name_declared("NSTIM_NUM")) { NSTIM_NUM=2 }
if (!name_declared("NCELLS")) { NCELLS=2 }
if (!name_declared("NSYNAPSE")) { NSYNAPSE=2 }
if (!name_declared("SYNAPSE_RANGE")) { SYNAPSE_RANGE=1 }
if (!name_declared("STOPTIME")) { STOPTIME=100 }
if (!name_declared("NETWORK")) { NETWORK=0 }
if (!name_declared("NTHREAD")) { NTHREAD=1 }
if (!name_declared("MULTISPLIT")) { MULTISPLIT=0 }
if (!name_declared("SPIKE_COMPRESS")) { CACHE_EFFICIENT=1 }
if (!name_declared("SPIKE_COMPRESS")) { SPIKE_COMPRESS=1 }
if (!name_declared("SHOW_SPIKE")) { SHOW_SPIKE=1 }
if (!name_declared("DBG_PRINT")) { DBG_PRINT=1 }
printf("STOPTIME=%lf\n",STOPTIME)
print STOPTIME
{load_file("CellTemplate_BN_1056_Parallel3.hoc")}
{load_file("CellSwc2_nrn8.hoc")}
{load_file("CellTemplate_LineCell_091002.hoc")}
objref pc
objref cells, nclist
objref stim, ncstim, ncstimlist, stimlist, synlist
objref tvec, idvec
// core
// make sure NEURON is compiled with Python
// chk 1
// dt=0.025
// if(pc.id == 0){ printf("check1 * NSTEP=%d (STOPTIME=%lf / dt=%lf)\n", STOPTIME/dt, STOPTIME, dt)}
// dt is not defined
// if (!nrnpython("from neuron import coreneuron")) {
// printf("NEURON not compiled with Python support\n")
// return
// }
// access coreneuron module via Python object
//tstop = STOPTIME
// objref cvode
// cvode = new CVode()
// mode = cvode.cache_efficient(1)
objref py_obj
py_obj = new PythonObject()
nrnpython("from neuron import coreneuron")
//nrnpython("from strtobool import strtobool; import os")
//py_obj.coreneuron.enable = True
//nrnpython("from distutils.util import strtobool; import os; coreneuron.gpu=bool(strtobool(os.environ.get('CORENRN_ENABLE_GPU', 'false')))")
//nrnpython("from distutils.util import strtobool; import os; coreneuron.gpu=bool(strtobool(os.environ.get('CORENRN_ENABLE_GPU', 'false')))")
//printf("nrncore_arg: |%s|\n", py_obj.coreneuron.nrncore_arg(STOPTIME))
//printf("core neuron on.\n")
proc mkcells () { local i, n, j, num_cell localobj cell, nc, syn, nil
cells = new List()
tvec = new Vector()
idvec = new Vector()
nclist = new List()
synlist = new List()
num_cell = $1
n = int(num_cell/pc.nhost)
for(i=0; i<n; i+=1){
// cell = new Cell_BN_1056()
cell = new CellSwc("Swc_BN_1056.swc")
// cell = new Cell_Line(0,0,0,3000)
cells.append(cell)
pc.set_gid2node(i + (n * pc.id), pc.id)
nc = cell.makeNetCon(2500, nil, 0, 0, 1.0) //2500->2300
pc.cell(i + (n * pc.id), nc)
nc.delay = 0.1 // 0.6
nc.weight = 0.05
nc.record(tvec, idvec, nc.srcgid)
nclist.append(nc)
syn = cell.makeSyn(300, 1, 5, 0)
synlist.append(syn)
}
pc.barrier()
}
tmp_pre=0
tmp_post=0
proc connectcells(){ local i, target_id, network_type, num_cell, num_synapse, num_comp, synapse_range localobj src, target, syn, nc, cell, rnd, nil
pc.barrier()
num_cell = $1
network_type = $2
num_synapse = $3
synapse_range = $4
num_comp = 3800
rnd = new Random()
rnd.uniform(0, num_cell-1)
if(network_type == 0 || network_type == 1 || network_type==2){
for(i=0; i<num_cell; i=i+1){
if(pc.gid_exists(i)){
for(j=0; j<num_synapse; j=j+1){
cell = pc.gid2obj(i)
pc.set_gid2node(3.2e5+i*num_synapse+j, pc.id)
if(network_type==2){
nc = cell.makeNetCon((1+i*num_synapse+j)%num_comp, nil, 0, 0, 0.1)
}else{
nc = cell.makeNetCon(-1, nil, 0, 0, 0.1)
}
pc.cell(3.2e5+i*num_synapse+j, nc)
nclist.append(nc)
nc.delay = 0.5 // 0.6
nc.weight = 0.05
tmp_pre=tmp_pre+1
}
}
}
pc.barrier()
for(i=0; i<num_cell; i=i+1){
for(j=0; j<num_synapse; j=j+1){
if(network_type==0){
target_id = (1+i+j*synapse_range)%num_cell
}else if(network_type==1 || network_type==2){
target_id = int(rnd.repick())
}
if(pc.gid_exists(target_id) && i!=target_id){
target = pc.gid2cell(target_id)
if(network_type==2){
syn = target.makeSyn((100+i*num_synapse+j)%num_comp, 1, 5, 0)
}else{
syn = target.makeSyn(-1, 1, 5, 0)
}
nc = pc.gid_connect(32000000+i*num_synapse+j, syn)
nclist.append(nc)
nc.delay = 0.5 // 0.6
nc.weight = 0.05
synlist.append(syn)
tmp_post=tmp_post+1
}
}
}
}else{
printf("ERROR : invalid network type.\n")
quit()
}
}
proc setModel(){
model = $1
if(model==1){
forall { insert pas }
}else if(model==2){
forall { insert hh }
// }else if(model==3){
// forall {insert hh_euler }
// }else if(model==4){
// forall {insert hh_runge }
// }else if(model==5){
// forall {insert hh_impl }
// }else if(model==6){
// forall {insert hh_cnexp }
// }else if(model==7){
// forall {insert hh_runge_notable }
// }else if(model==8){
// forall {insert hh_cnexp_notable }
// }else if(model==9){
// forall {insert hh2CW }
// }else if(model==10){
// forall {insert hh2F }
// }else if(model==11){
// forall {insert hh2CW_many }
}else{
forall { insert hh }
}
}
proc print_stat() {
for i = 0, cells.count-1 {
printf("[proc:%02d] synlist %d\n", pc.id, cells.object(i).synlist.count())
}
}
// $1 : cell id for stimulate
proc mkstim() { local i, num_stim_pos, stim_cell, num_cell, num_stim
num_cell = $1
num_stim_pos = $2
num_stim = $3
ncstimlist = new List()
stimlist = new List()
for(i=0; i<num_stim; i=i+1){
stim_cell = i * (num_cell/(num_stim+1))
if(pc.gid_exists(stim_cell)){
//printf("[makestim:%d] CELL %d\n", pc.id, stim_cell)
stim = new NetStim()
stim.number = 10
stim.start = 0
stim.interval = 50
ncstim = new NetCon(stim, pc.gid2cell(stim_cell).synlist.object(0))
ncstim.delay = 1
ncstim.weight = 0.1
stimlist.append(stim)
ncstimlist.append(ncstim)
}
}
}
proc spikeout() { local i, count, rank localobj fobj, tmpmt
printf("start spikeout\n")
strdef filename
count = 0
fobj = new File()
tmpmt = new Matrix(10,10)
sprint(filename, "./result/spike_%010d.txt", pc.id)
fobj.wopen(filename)
fobj.printf("time [ms]\t cell_id\n")
tmpmt.resize(tvec.size(),2)
tmpmt.setcol(0, tvec)
tmpmt.setcol(1, idvec)
tmpmt.fprint(0, fobj, "\t%g\t")
fobj.close
if(pc.id == 0){ printf("\n\ttime [ms]\t cell_id\n") }
pc.barrier()
for i=0, tvec.size()-1{
printf("SPIKE : \t %f\t %d\n", tvec.x[i], idvec.x[i])
}
}
proc printSpikeStat() { local nsendmax, nsend, nrecv, nrecv_useful
nsendmax = pc.spike_statistics(&nsend, &nrecv, &nrecv_useful)
printf("[%d] nsendmax=%d nsend=%d nrecv=%d nrecv_useful=%d\n", pc.id, nsendmax, nsend,nrecv, nrecv_useful)
}
// start main
{printf("main-STOPTIME=%lf\n",STOPTIME)
/// test coreneuron-2
// access coreneuron module via Python object
//py_obj.coreneuron.enable = 1
objref cvode
cvode = new CVode()
mode = cvode.cache_efficient(1)
// objref py_obj
py_obj = new PythonObject()
//py_obj.coreneuron.enable = 1
//0919 need?
//finitialize?
//stdinit()
//nrnpython("from neuron.tests.utils.strtobool import strtobool; import os; coreneuron.gpu=bool(strtobool(os.environ.get('CORENRN_ENABLE_GPU', 'false')))")
nrnpython("from distutils.util import strtobool; import os; coreneuron.gpu=bool(strtobool(os.environ.get('CORENRN_ENABLE_GPU', 'false')))")
nrnpython("coreneuron.gpu=bool(strtobool(os.environ.get('CORENRN_ENABLE_GPU', 'false')))")
printf("nrncore_arg: |%s|\n", py_obj.coreneuron.nrncore_arg(STOPTIME))
printf("core neuron on.\n")
// test end
// if(pc.id == 0){ printf("check2 * NSTEP=%d (STOPTIME=%lf / dt=%lf)\n", STOPTIME/dt, STOPTIME, dt)}
pc = new ParallelContext()
if(NTHREAD != 0){ pc.nthread(NTHREAD) }
if(SPIKE_COMPRESS==1){
if(pc.id ==0){ printf("pc.spike_compress(1, 0)\n") }
pc.spike_compress(1, 0)
}else if(SPIKE_COMPRESS==2){
pc.spike_compress(0, 1, 1)
}
printf("id %d",pc.id)
if(pc.id == 0){
printf("\nCondition : \n")
printf(" * Process=%d, Thread=%d\n", pc.nhost, NTHREAD)
printf(" * NSTEP=%d (STOPTIME=%lf / dt=%lf)\n", STOPTIME/dt, STOPTIME, dt)
printf(" * Model=%s, nCELLS=%d, nSYNAPSE=%d\n", "BN_1056", NCELLS, NSYNAPSE)
printf(" * NSTIM_POS=%d, NSTIM_NUM=%d, SYNAPSE_RANGE=%d\n", NSTIM_POS, NSTIM_NUM, SYNAPSE_RANGE)
printf(" * CacheEfficient=%d, SpikeCompressMode=%d\n\n", CACHE_EFFICIENT, SPIKE_COMPRESS)
printf("[id:0] start modeling\n")
}
start_time = pc.time
mkcells(NCELLS)
printf("mkcell-finished\n")
connectcells(NCELLS, NETWORK, NSYNAPSE, SYNAPSE_RANGE)
printf("connetcel-finished\n")
setModel(MODEL)
printf("setmode-finished\n")
//if(pc.id == 0){ print_stat() }
mkstim(NCELLS, NSTIM_POS, NSTIM_NUM)
// spikerecord()
pc.barrier()
//if(MULTISPLIT==1){ pc.multisplit() }
//if(CACHE_EFFICIENT==1){ pc.cache_efficient(1) }
//if(CACHE_EFFICIENT==1){ pc.multisplit() }
pc.set_maxstep(5)
{load_file("recorder.hoc")}
// setVoltageRecord()
spikerecord()
// tstop = STOPTIME
// stdinit()
// tstop = STOPTIME
if(pc.id == 0){ printf("[id:0] Modeling Finished.\n") }
if(pc.id == 0){ printf("[id:0] Calculation Starts\n") }
pc.barrier()
// print startsw()
modelfin_time = pc.time
start_waittime = pc.wait_time
if(pc.id == 0){startsw()}
if(pc.id == 0){
printf("pre-psolve\n")
printf("check3 * NSTEP=%d (STOPTIME=%lf / dt=%lf)\n", STOPTIME/dt, STOPTIME, dt)}
//0919 need?
//finitialize?
stdinit()
// start sim
pc.psolve(tstop)
if(pc.id == 0){ printf("[id:0] Calculation Finished !!\n") }
pc.barrier()
if(pc.id == 0){startsw()}
stop_time = pc.time
stop_waittime = pc.wait_time()
stop_steptime = pc.step_time()
stop_sendtime = pc.send_time()
// fprintVoltageRecord()
// fprintVoltageVecRecord()
pc.barrier()
if(pc.id ==0){
printf("\nRESULT : \n")
printf(" * SpikeSendMax=%d\n", pc.spike_statistics() )
printf(" * step=%lf sec, wait=%lf sec, send=%f sec\n", stop_steptime, stop_waittime-start_waittime, stop_sendtime)
printf(" * modeling time : %f sec\n", modelfin_time - start_time)
printf(" * core time : %f sec\n", stop_time-modelfin_time)
}
pc.barrier()
printf("[%d] NC = %d, SYN = %d, tmp_pre = %d, tmp_post = %d\n", pc.id, nclist.count(), synlist.count(), tmp_pre, tmp_post)
if(SHOW_SPIKE==1){ spikeout() }
printSpikeStat()
//quit()
//pc.max_histogram()
if(pc.id == 0){printf("finished all check")}
pc.runworker()
pc.done()
}
// change the place
//{chdir("../f_job")}
quit()