16 Jan
2020
16 Jan
'20
11:54 a.m.
Hi,
as long as I didn't miss a significant change in the way Poisson
generators are implemented, please be extremely careful with this! Yes,
Charl is correct, in terms of statistics it does not make a difference,
_but_ in terms of performance it makes a big difference due to the way
Poisson generators are implemented. Without going into the details (with
which other are much more familiar anyway), always try to use the least
possible number of Poisson generators (1x1000Hz >> 100x 10Hz)! Otherwise
your simulations might be terribly slow.
Note however, that for spike generators, the above does not apply, as
far as I know.
Best,
Jakob
On 1/16/20 11:43 AM, Charl Linssen wrote:
> Hi,
>
> Perhaps it helps to note that 100 Poisson generators of rate, say, 10 Hz, is
equivalent to one generator with rate 1000 Hz.
>
> Kind regards,
> Charl
>
>
> On Thu, Jan 16, 2020, at 11:13, Jochen Martin Eppler wrote:
>> Hi!
>>
>> There is no way to get 100 spike generators without creating them
>> individually. But as they are pretty efficient with respect to memory
>> and performance, I also don't see a problem with that.
>>
>> Other than that, the description of what you want to achieve is far too
>> vague to give you more detailed advice. Please consider sending a figure
>> of your planned network topology and/or (pseudo) code that shows what
>> you want to do. Also have a look at the example networks for NEST, as
>> those contain a lot of useful design patterns for all kinds of
>> simulation scenarios:
>>
>> https://nest-simulator.readthedocs.io/en/latest/examples/index.html
>>
>> Cheers,
>> Jochen!
>>
>>
>> On 07.01.20 16:46, shanka19(a)purdue.edu wrote:
>>> Hello everyone,
>>>
>>> Happy New Year! I want to create a simple neural network consisting of a
single neuron connected by multiple inputs (spike generators). I am aware that I can
create single spike generators and then connect them but it becomes infeasible as the size
of input grows. Is there a way to create a network of maybe 100 spike generators connected
to a single LIF Neuron without explicitly creating 100 of them? Once the connections are
made is there a way that the network is updated when the weights are updated. I want the
network to get updated as I update the weights. Now, I update the weights and reset the
network to create it again with new weights. Any help would be appreciated. Thanks in
advance!
>>> _______________________________________________
>>> NEST Users mailing list -- users(a)nest-simulator.org
>>> To unsubscribe send an email to users-leave(a)nest-simulator.org
>>>
>>
>> --
>> Dr. Jochen Martin Eppler
>> Phone: +49(2461)61-96653
>> ----------------------------------
>> Simulation Laboratory Neuroscience
>> Jülich Supercomputing Centre
>> Institute for Advanced Simulation
>>
>>
>>
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