def get_pool(mpi=False,threads=1):
if mpi: # using MPI
from mpipool import MPIPool
pool = MPIPool()
pool.start()
if not pool.is_master():
sys.exit(0)
elif threads>1: # using multiprocessing
from multiprocessing import Pool
pool = Pool(processes=threads)
else:
raise RuntimeError,"Wrong arguments: either mpi=True or threads>1."
return pool
def get_pool(mpi=False, threads=1):
if mpi: # using MPI
from mpipool import MPIPool
pool = MPIPool()
pool.start()
if not pool.is_master():
sys.exit(0)
elif threads > 1: # using multiprocessing
from multiprocessing import Pool
pool = Pool(processes=threads)
else:
raise RuntimeError, "Wrong arguments: either mpi=True or threads>1."
return pool
def get_pool(mpi=False, threads=1):
"""
Create a thread pool for paralleling DEM simulations within GrainLearning
:param mpi: bool, default=False
:param threads: int, default=1
"""
if mpi: # using MPI
from mpipool import MPIPool
pool = MPIPool()
pool.start()
if not pool.is_master():
sys.exit(0)
elif threads > 1: # using multiprocessing
from multiprocessing import Pool
pool = Pool(processes=threads, maxtasksperchild=10)
else:
raise RuntimeError("Wrong arguments: either mpi=True or threads>1.")
return pool
