Dear Petia,

On each MPI rank, GetConnections() will only collect connections for which the post-synaptic neuron is on that MPI rank. You then need to find a way to collect this information across ranks. If you only need that information for offline processing, it might be easiest to write the connection information to file from each rank and then collect across ranks (you probably don't want to store the result from GetConnections(), but rather get the status of the synapses and store that). As a starting point, you could take the

https://nest-simulator.readthedocs.io/en/v3.4/auto_examples/store_restore_network.html

example. There, connections (and neurons) are stored with

   network = {}

    network["n_vp"] = nest.total_num_virtual_procs

    network["e_nrns"] = self.neurons.get(["V_m"], output="pandas")

    network["i_nrns"] = self.neurons.get(["V_m"], output="pandas")

    network["e_syns"] = nest.GetConnections(synapse_model="e_syn").get(

        ("source", "target", "weight"), output="pandas")

    network["i_syns"] = nest.GetConnections(synapse_model="i_syn").get(

        ("source", "target", "weight"), output="pandas")

    with open(dump_filename, "wb") as f:

        pickle.dump(network, f, pickle.HIGHEST_PROTOCOL)

You might not need the data on neurons, and you would have to write one file per MPI rank. Depending on your synapse type, you may want to store more parameters than source, target and weight.

If you need the information at runtime, you could try to use mpi4py to aggregate the connection information across ranks.

Best,

Hans Ekkehard