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I have written a biological neural network that contains several groups of neurons and synapses in Brainpy. However, during simulation, it seems that the code cannot fully utilize all CPU cores. The code looks like this:
I think updating each neuron group and synapse group in python for-loop is slow, In theory, the neuron and synapse groups can be run in parallel. I have tried modified the update function as this using the Python threading module:
But from the task manager (in Ubuntu 22.04), I find that the process is still running on a single core. Is there a way to run multiple neuron groups in a network in parallel in Brainpy?
Thanks!
The text was updated successfully, but these errors were encountered:
Hi, thank you for the reply. I understand that implementing parallel simulation of one BrainPy model is nontrivial. Could you let me know which function (or module) I should use? I can look into it by myself. Or does it require a major revision of the update() function or simulation process?
Dear @CloudyDory , We are still working on the examples for parallel simulations. Tutorials are on the way. We will release these supports in the next week.
I have written a biological neural network that contains several groups of neurons and synapses in Brainpy. However, during simulation, it seems that the code cannot fully utilize all CPU cores. The code looks like this:
I think updating each neuron group and synapse group in python for-loop is slow, In theory, the neuron and synapse groups can be run in parallel. I have tried modified the
update
function as this using the Pythonthreading
module:or this:
But from the task manager (in Ubuntu 22.04), I find that the process is still running on a single core. Is there a way to run multiple neuron groups in a network in parallel in Brainpy?
Thanks!
The text was updated successfully, but these errors were encountered: