Support for using file transfer mode via coreneuron embedded module #927
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* add new option coreneuron.file_mode = True / False
* if file_mode=True, the model is written to folder
corenrn_data and coreneuron is launched
* with file transfer mode, only spikes will be
available
* bug fix in the test test_spikes.py in MPI mode:
mpi4py needs to be imported before importing neuron
* add test for file_mode both in serial as well as
mpi mode
This reverts commit 3a03fe4.
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This looks good to me except it seems time to go ahead and implement the \todo item in nrnpy_hoc.cpp and have only the single get_nrncore_opt_value with a return type argument.
Perhaps the NEURON Datum union can be used to send back a int, double, or pointer to (copy?) of a c_str. (Or backcast a returned void*?)
@nrnhines : I don't have complete picture about implementation aspects. Could we do this as separate PR? |
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No problem. As soon as the checks are successful, I'll merge. |
| coreneuron.verbose = 0 | ||
| h.stdinit() | ||
| corenrn_all_spike_t = h.Vector() | ||
| corenrn_all_spike_gids = h.Vector() | ||
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| pc.spike_record( -1 if pc.id() == 0 else (pc.id()), |
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By removing this we are no longer testing 2nd case when we iterate over PreSyns and match up vectors.
- apply suggestion from review in #927
* Update test for better code coverage - apply suggestion from review in #927 * fix the test : gid is pc.id()+1 and not pc.id()
corenrn_data and coreneuron is launched
available
mpi4py needs to be imported before importing neuron
mpi mode
I see two benefits with this PR:
we have to write separate shell scripts to run special and
special-core.
just few processes. But then model building part becomes
slow. Based on this PR, we can build model with process
per core and dump to the file. Then on CoreNEURON side
only few ranks can load the data and utilise GPU using
multiple OpenMP threads per rank.
cc: @iomaganaris @alexsavulescu