Hans,

 

> We clearly need to fix the bug. Could you create a minimal reproducer and then create an issue https://github.com/nest/nest-simulator/issues?


Yes I will.

 

> As a work-around for global normalization of weights, you could try to use MPI4Py to compute the sum of the local weights.

 

I should learn MPI4Py. I am not an expert in MPI (although I am fluent with threads programming). In addition I am clueless about what pyNEST functions to use in order to gather all the pre-synaptic connections of a neuron (different to GetConnections() ).



> If your network sizes do not go into the millions, maybe systems with large numbers of threads could help, e.g., JUSUF which has computed notes with 128 cores. You can apply for access through FENIX (https://fenix-ri.eu). The Human Brain Project provides relatively easy-to-apply for resources there.

 

The problem is that my architecture sometimes (many times, in fact) needs more than 128Gb RAM (just the RAM size of the nodes the cluster I am working on). Hence, I need to work with MPI to distribute my architecture through several nodes.


Now I am working with 1 mpi process (hence, just one node) and 32 threads. But it implies to work with "small" architectures.



> You could also issue a feature request issue on NEST for support for global normalization.

 

I will!


Thanks a lot in advance!


Xavier







Best regards,

Hans Ekkehard

 

-- 

 

Prof. Dr. Hans Ekkehard Plesser

Head, 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

Home http://arken.nmbu.no/~plesser

 

 

 

From: Xavier Otazu <xotazu@cvc.uab.cat>
Date: Thursday, 16 March 2023 at 11:57
To: users@nest-simulator.org <users@nest-simulator.org>
Subject: [NEST Users] Re: MPI error when using GetConnections

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Hi Hans!

Commenting out the DumpLayerConnections() lines, it also crashes.

In addition, the problem disappears when I reduce the size of the number of neurons or the connection shape (but it is not practical for me).

Hence, if it is only the normalization of the local MPI process, I understand the only way to normalize the overall sum of weights of a particular neuron is to not using MPI? It is impractical for me because I use big networks (several tenths of thousands).

Cheers,

Xavier
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