[NEST Users] Re: Weights assignment error with mpirun

Hi Xavier, I think I can reproduce your problem and have an idea what it may cause it. How many MPI processes did you use? Best, Hans Ekkehard -- Prof. Dr. Hans Ekkehard Plesser Department of Data Science Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser@nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser From: Xavier Otazu &lt;xotazu(a)cvc.uab.cat&gt; Date: Wednesday, 7 February 2024 at 15:41 To: users(a)nest-simulator.org &lt;users(a)nest-simulator.org&gt; Subject: [NEST Users] Weights assignment error with mpirun [Some people who received this message don't often get email from xotazu(a)cvc.uab.cat. Learn why this is important at https://aka.ms/LearnAboutSenderIdentification ] Hi! I am trying to implement weight normalization (as you show in your documentation). It works well (see below code) when executed "normally" (or when using" mpirun -np 1"), but it hangs (it just do not respond) when executed using mpirun. It hangs when I try to execute nest.Simulate() after weigth assignment. If I remove the "conn.weight = w_nparray" instruction in the following code, it works without hang. I use NEST 3.6 and python3, compiled with python, mpi, sionlib and music. Thanks a lot in advance! import nest import numpy as np pos = nest.spatial.grid(shape = [30,30] ) input = nest.Create('iaf_psc_alpha', positions=pos) layer_0 = nest.Create('iaf_psc_alpha', positions=pos) layer_1 = nest.Create('iaf_psc_alpha', positions=pos) conn_neur = {'rule':'pairwise_bernoulli', 'use_on_source': True, 'mask': {'grid':{'shape':[9,9]}} } nest.CopyModel('static_synapse', 'syn_1_model') syn_0 = {'synapse_model': 'static_synapse'} syn_1 = {'synapse_model': 'syn_1_model'} nest.Connect(input, layer_0, conn_neur, syn_0) nest.Connect(input, layer_1, conn_neur, syn_0) nest.DumpLayerConnections(input, layer_0, 'static_synapse', 'conn.txt') nest.DumpLayerConnections(input, layer_1, 'syn_1_model', 'conn.txt') nest.Simulate(100) for neuron in layer_0: conn = nest.GetConnections(source=input, target=neuron, synapse_model='static_synapse') w = np.array(conn.weight) if (w.size>1): w_normed = w / sum(abs(w)) # L1-norm w_nparray = 2. * w_normed conn.weight = w_nparray nest.Simulate(100) _______________________________________________ NEST Users mailing list -- users(a)nest-simulator.org To unsubscribe send an email to users-leave(a)nest-simulator.org