/usr/share/pyshared/ase/parallel.py is in python-ase 3.6.0.2515-1.1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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import time
import atexit
import numpy as np
def paropen(name, mode='r', buffering=0):
"""MPI-safe version of open function.
In read mode, the file is opened on all nodes. In write and
append mode, the file is opened on the master only, and /dev/null
is opened on all other nodes.
"""
if rank > 0 and mode[0] != 'r':
name = '/dev/null'
return open(name, mode, buffering)
def parprint(*args, **kwargs):
"""MPI-safe print - prints only from master.
Tries to adopt python 3 behaviour.
"""
if rank > 0:
return
defaults = {'end': '\n',
'file': sys.stdout }
for key in defaults:
if not key in kwargs:
kwargs[key] = defaults[key]
for arg in args[:-1]:
print >> kwargs['file'], arg,
if len(args):
last = args[-1]
else:
last = ''
if kwargs['end'] == '\n':
print >> kwargs['file'], last
else:
print >> kwargs['file'], last,
class DummyMPI:
rank = 0
size = 1
def sum(self, a):
if isinstance(a, np.ndarray) and a.ndim > 0:
pass
else:
return a
def barrier(self):
pass
def broadcast(self, a, rank):
pass
class MPI4PY:
def __init__(self):
from mpi4py import MPI
self.comm = MPI.COMM_WORLD
self.rank = self.comm.rank
self.size = self.comm.size
def sum(self, a):
return self.comm.allreduce(a)
def barrier(self):
self.comm.barrier()
def broadcast(self, a, rank):
a[:] = self.comm.bcast(a, rank)
# Check for special MPI-enabled Python interpreters:
if '_gpaw' in sys.modules:
# http://wiki.fysik.dtu.dk/gpaw
from gpaw.mpi import world
elif 'asapparallel3' in sys.modules:
# http://wiki.fysik.dtu.dk/Asap
# We cannot import asap3.mpi here, as that creates an import deadlock
#from asap3.mpi import world
import asapparallel3
world = asapparallel3.Communicator()
elif 'Scientific_mpi' in sys.modules:
from Scientific.MPI import world
elif 'mpi4py' in sys.modules:
world = MPI4PY()
else:
# This is a standard Python interpreter:
world = DummyMPI()
rank = world.rank
size = world.size
barrier = world.barrier
def register_parallel_cleanup_function():
"""Call MPI_Abort if python crashes.
This will terminate the processes on the other nodes."""
if size == 1:
return
def cleanup(sys=sys, time=time, world=world):
error = getattr(sys, 'last_type', None)
if error:
sys.stdout.flush()
sys.stderr.write(('ASE CLEANUP (node %d): %s occurred. ' +
'Calling MPI_Abort!\n') % (world.rank, error))
sys.stderr.flush()
# Give other nodes a moment to crash by themselves (perhaps
# producing helpful error messages):
time.sleep(3)
world.abort(42)
atexit.register(cleanup)
def distribute_cpus(parsize_calculator, comm):
"""Distribute cpus to tasks and calculators"""
assert parsize_calculator <= comm.size
assert comm.size % parsize_calculator == 0
tasks_rank = comm.rank // parsize_calculator
r0 = tasks_rank * parsize_calculator
ranks = np.arange(r0, r0 + parsize_calculator)
calc_comm = comm.new_communicator(ranks)
# print 'comm.rank, ranks=', comm.rank, ranks
tasks_comm = np.arange(0, comm.size, parsize_calculator)
return calc_comm, tasks_comm, tasks_rank
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