def _run_multiprocess_pool(cases,
ncpu=os.cpu_count(),
verbose=logging.INFO,
**kwargs):
"""
Run multiprocessing jobs using Pool.
This function returns all System instances in a list, but requires longer computation time.
Parameters
----------
ncpu : int, optional = os.cpu_cout()
Number of cpu cores to use in parallel
mp_verbose : 10 - 50
Verbosity level during multiprocessing
verbose : 10, 20, 30, 40, 50
Verbosity level outside multiprocessing
"""
pool = Pool(ncpu)
print("Cases are processed in the following order:")
print('\n'.join([f'"{name}"' for name in cases]))
ret = pool.map(
partial(run_case, verbose=verbose, remove_pycapsule=True, **kwargs),
cases)
return ret
def _prepare_mp(self, quick=False):
"""
Code generation with multiprocessing. NOT WORKING NOW.
Warnings
--------
Function is not working. Serialization failed for `conj`.
"""
from andes.shared import Pool
import dill
dill.settings['recurse'] = True
# consistency check for group parameters and variables
self._check_group_common()
def _prep_model(model: Model):
model.prepare(quick=quick)
return model
model_list = list(self.models.values())
# TODO: failed when serializing.
ret = Pool().map(_prep_model, model_list)
for idx, name in enumerate(self.models.keys()):
self.models[name] = ret[idx]
self._store_calls()
self.dill()