I get a segmentation error when running multiple version of the same simulations (with different parameters) in parallel on a super computer (Beskow; PDC; Royal Institutet of Technology; Stockholm).
I only get the error when I use the tvec argument of the Vector.record() method:
vdest.record(var_reference, tvec)
https://www.neuron.yale.edu/neuron/stat ... tor.record
And I do not get the error if I run the same simulation locally.
Error message:
Am I doing something wrong or is there a known error with this method? Do you have any ideas of what could be going on?special: ../../../../src/nrn-7.4/src/nrniv/../nrncvode/netcvode.cpp:5737: virtual void VecRecordDiscrete::deliver(double, NetCvode*): Assertion `osMath::equal(t_->elem(j), tt, 1e-8)' failed.
_pmiu_daemon(SIGCHLD): [NID 00110] [c0-0c1s11n2] [Mon Nov 12 16:25:05 2018] PE RANK 117 exit signal Aborted
I'm using Neuron+Python v7.4.
The simulation runs if I do not use the tvec argument and instead pick certain time points after the simulation is finished. But it would be nice if I could get this to work since it would save some computing time and memory storage.
Example code
Code: Select all
tvec_local_vm = [600,800] + range(1000, 1100, 10) + [1100, 1120, 1150, 1200, 1300]
tv_local = h.Vector()
tv_local.from_python( tvec_local_vm )
local_vm = {}
for section in stim:
sec = spike_list['name_to_sec'][section]
local_vm[section] = h.Vector()
local_vm[section].record(sec(0.5)._ref_v, tv_local)
# finalize and run
h.finitialize(-70)
while h.t < tstop:
h.fadvance()
Thanks!
Robert