def enable_threads(self, n_threads, multisplit_on=True):
"""Enable threads in neuron Using the parall Neuron"""
h.load_file('parcom.hoc')
pc =h.ParallelComputeTool()
pc.nthread(n_threads, 1)
if multisplit_on:
pc.multisplit(1)
def multisplit():
h.load_file("parcom.hoc")
parcom = h.ParallelComputeTool()
parcom.multisplit(1)
if settings.rank == 0:
lb = parcom.lb
print ('multisplit rank 0: %d pieces Load imbalance %.1f%%' % (lb.npiece, (lb.thread_cxbal_ -1)*100))
def discover_cores_activate_multisplit(h):
"""
Use case: discover_cores_activate_multisplit(h)
where h is a module; from neuron import h.
"""
# discover no. of cores in 1CPU and activate multisplit to use all cores
cores = multiprocessing.cpu_count()
h.load_file("parcom.hoc")
p = h.ParallelComputeTool()
p.change_nthread(cores, 1)
p.multisplit(1)
def activate_cores():
"""Activates cores
**Arguments:** Nothing is passed.
**Returned values:** Nothing is returned.
"""
cores = multiprocessing.cpu_count()
h.load_file("parcom.hoc")
p = h.ParallelComputeTool()
#p.change_nthread(cores, 1)
#p.multisplit(1)
return "cores are activated" # for hardwareTest.py
from neuron import h, gui
from Cereb_GrC_regular import Grc_regular
import multiprocessing
import numpy as np
import matplotlib.pyplot as plt
cell = Grc_regular(1)
h.nrncontrolmenu()
time_step = h.CVode()
time_step.active(0) #0 fixed step, 1 variable time step
cpu = multiprocessing.cpu_count()
h.load_file("parcom.hoc")
p = h.ParallelComputeTool()
if cpu > 8:
p.change_nthread(8, 1)
print('Maximum 8 threads')
else:
p.change_nthread(cpu, 1)
print('N° of treads', cpu)
p.multisplit(1)
h('load_file("vm.ses")')
stimdata = dict()
stimdata['timeglobal'] = 2500
synapsesdata = dict()
