27 Nov
2019
27 Nov
'19
3:04 p.m.
Hi Andrew,
Is it because the network takes a long time to build?Are you working
with very large networks that need to be spread on multiple machines?
I am personally building networks with complex topologies, where
creating the synaptic connections requires a lot of time since I do
random sampling with constraint satisfaction directly in Python.
I also need to compute per-synapse approximations of axonal delays,
dendritic tree attenuations and much more. I do build the network once
and have written some Python code that allow to pickle the necessary
information (e.g. parameters of the neuron models, synaptic weights) to
instantiate faster the network in NEST when I want to perform
simulations. But that is just a custom solution, not general to any
network.
Cordially,Simon
On Tue, 2019-11-26 at 12:39 +0100, alehr wrote:
Dear NEST developer,
I am wondering if my inquiry from November 11th has been looked at.
Thanks,
Andrew Lehr
On Mon, Nov 11, 2019 at 1:52 PM alehr <alehr(a)mun.ca> wrote:
--
___________________________________________________
Simon Brodeur
Étudiant au doctorat
Université de Sherbrooke
Département génie électrique et génie informatique
Laboratoire NECOTIS, C1-3036
Tél. : (819) 821-8000 poste 62187
Courriel: Simon.Brodeur(a)USherbrooke.ca
___________________________________________________
Dear NEST developer,
I would like to initialize a network with neurons and connections
and then run many simulations with it. It would be great if I could
build the network one time and then deepcopy (or something similar)
for each simulation. Is something like this possible?
Thanks,
Andrew Lehr
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