Example: 01_using_cython

Note

You can launch an interactive, editable version of this example without installing any local files using the Binder service (although note that at some times this may be slow or fail to open):

Parallel processes using Cython

This example use multiprocessing to run several simulations in parallel. The code is using the default runtime mode (and Cython compilation, if possible).

The numb_proc variable set the number of processes. run_sim is just a toy example that creates a single neuron and connects a StateMonitor to record the voltage.

For more details see the github issue 1154:

Note that Python’s multiprocessing module cannot deal with user-defined functions (including TimedArray) and other complex code structures. If you run into PicklingError or AttributeError exceptions, you might have to use the pathos (https://pypi.org/project/pathos) package instead, which can handle more complex code structures.

import os
import multiprocessing

from brian2 import *


def run_sim(tau):
    pid = os.getpid()
    print(f'RUNNING {pid}')
    G = NeuronGroup(1, 'dv/dt = -v/tau : 1', method='exact')
    G.v = 1
    mon = StateMonitor(G, 'v', record=0)
    run(100*ms)
    print(f'FINISHED {pid}')
    return mon.t/ms, mon.v[0]


if __name__ == "__main__":
    num_proc = 4

    tau_values = np.arange(10)*ms + 5*ms
    with multiprocessing.Pool(num_proc) as p:
        results = p.map(run_sim, tau_values)

    for tau_value, (t, v) in zip(tau_values, results):
        plt.plot(t, v, label=str(tau_value))
    plt.legend()
    plt.show()