def test_launcher():
# configured launch commands for selected launchers
serial = SerialMapper()
print "non-python serial launch:", serial
settings = {'python':'', 'program':"hostname"}
print serial._launcher(settings), "\n"
print "serial python launch:", serial
defaults['program'] = "tools.py"
defaults['progargs'] = "12345"
print serial._launcher(defaults), "\n"
qsub = Torque()
serial.scheduler = qsub
print "scheduled serial launch:", serial
settings = {'program':"tools.py", 'progargs':'12345'}
print serial._launcher(settings), "\n"
mpi = Mpi()
print "non-scheduled parallel launch:", mpi
print mpi._launcher(settings), "\n"
qsub.nodes = '4:ppn=2'
mpi.nodes = mpi.njobs(qsub.nodes)
print "scheduled parallel launch:", mpi, "| Torque"
print qsub._submit(mpi._launcher(settings)), "\n"
mpi.scheduler = qsub
print "scheduled parallel launch:", mpi
print mpi._launcher(settings), "\n"
_mpi = Mpi(scheduler=Torque(nodes='4:ppn=2'))
print "scheduled parallel launch:", _mpi
print _mpi._launcher(settings), "\n"
_mpi = TorqueMpi(nodes='4:ppn=2')
print "scheduled parallel launch:", _mpi
print _mpi._launcher(settings), "\n"
qsub.nodes = 1
serial = SerialMapper()
print "scheduled serial launch:", serial, "| Torque"
print qsub._submit(serial._launcher(settings)), "\n"
def test_launcher():
# configured launch commands for selected launchers
serial = SerialMapper()
print("non-python serial launch:", serial)
settings = {'python': '', 'program': "hostname"}
print(serial._launcher(settings), "\n")
print("serial python launch:", serial)
defaults['program'] = "tools.py"
defaults['progargs'] = "12345"
print(serial._launcher(defaults), "\n")
qsub = Torque()
serial.scheduler = qsub
print("scheduled serial launch:", serial)
settings = {'program': "tools.py", 'progargs': '12345'}
print(serial._launcher(settings), "\n")
mpi = Mpi()
print("non-scheduled parallel launch:", mpi)
print(mpi._launcher(settings), "\n")
qsub.nodes = '4:ppn=2'
mpi.nodes = mpi.njobs(qsub.nodes)
print("scheduled parallel launch:", mpi, "| Torque")
print(qsub._submit(mpi._launcher(settings)), "\n")
mpi.scheduler = qsub
print("scheduled parallel launch:", mpi)
print(mpi._launcher(settings), "\n")
_mpi = Mpi(scheduler=Torque(nodes='4:ppn=2'))
print("scheduled parallel launch:", _mpi)
print(_mpi._launcher(settings), "\n")
_mpi = TorqueMpi(nodes='4:ppn=2')
print("scheduled parallel launch:", _mpi)
print(_mpi._launcher(settings), "\n")
qsub.nodes = 1
serial = SerialMapper()
print("scheduled serial launch:", serial, "| Torque")
print(qsub._submit(serial._launcher(settings)), "\n")
#!/usr/bin/env python
#
# Author: Mike McKerns (mmckerns @caltech and @uqfoundation)
# Copyright (c) 1997-2016 California Institute of Technology.
# Copyright (c) 2016-2018 The Uncertainty Quantification Foundation.
# License: 3-clause BSD. The full license text is available at:
# - https://github.com/uqfoundation/pyina/blob/master/LICENSE
from pyina.launchers import SerialMapper
from pyina.schedulers import Torque
from pyina.mpi import _save, _debug
#_debug(True)
#_save(True)
def host(id):
import socket
return "Rank: %d -- %s" % (id, socket.gethostname())
print("Submit a non-parallel job to torque in the 'productionQ' queue...")
print("Using 5 items over 1 nodes and the default mapping strategy")
torque = Torque(queue='productionQ', timelimit='20:00:00', workdir='.')
pool = SerialMapper(scheduler=torque)
res = pool.map(host, range(5))
print(pool)
print('\n'.join(res))
# end of file
#!/usr/bin/env python
#
# Author: Mike McKerns (mmckerns @caltech and @uqfoundation)
# Copyright (c) 1997-2016 California Institute of Technology.
# License: 3-clause BSD. The full license text is available at:
# - http://trac.mystic.cacr.caltech.edu/project/pathos/browser/pyina/LICENSE
from pyina.launchers import SerialMapper
from pyina.schedulers import Torque
from pyina.mpi import _save, _debug
#_debug(True)
#_save(True)
def host(id):
import socket
return "Rank: %d -- %s" % (id, socket.gethostname())
print "Submit a non-parallel job to torque in the 'productionQ' queue..."
print "Using 5 items over 1 nodes and the default mapping strategy"
torque = Torque(queue='productionQ', timelimit='20:00:00', workdir='.')
pool = SerialMapper(scheduler=torque)
res = pool.map(host, range(5))
print pool
print '\n'.join(res)
# end of file
