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"
# - https://github.com/uqfoundation/pyina/blob/master/LICENSE
from pyina.launchers import Mpi
#XXX:: can fail with NameError: global name 'func' is not defined
#XXX:: can fail with RuntimeError: maximum recursion depth exceeded
#from mystic.models.poly import chebyshev8cost as func
def host(coeffs):
from mystic.models.poly import chebyshev8cost as func
return "Chebyshev%s = %s" % (coeffs, func(coeffs))
params = [(i,0,-2*i,0,4*i,0,-2*i,0,i) for i in range(10)]
pool = Mpi()
print("Evaluate the 8th order Chebyshev polynomial...")
print("Using 'dill' for 10 combinations over 4 nodes")
pool.nodes = 4
res1 = pool.map(host, params)
print(pool)
print('\n'.join(res1))
print('')
print("Using 'dill.source' for 10 combinations over 4 nodes")
pool.source = True
res2 = pool.map(host, params)
print(pool)
print('\n'.join(res2))
# end of file
# - https://github.com/uqfoundation/pyina/blob/master/LICENSE
from pyina.launchers import Mpi
#XXX:: can fail with NameError: global name 'func' is not defined
#XXX:: can fail with RuntimeError: maximum recursion depth exceeded
#from mystic.models.poly import chebyshev8cost as func
def host(coeffs):
from mystic.models.poly import chebyshev8cost as func
return "Chebyshev%s = %s" % (coeffs, func(coeffs))
params = [(i,0,-2*i,0,4*i,0,-2*i,0,i) for i in range(10)]
pool = Mpi()
print("Evaluate the 8th order Chebyshev polynomial...")
print("Using 'dill' for 10 combinations over 4 nodes")
pool.nodes = 4
res1 = pool.map(host, params)
print(pool)
print('\n'.join(res1))
print('')
print("Using 'dill.source' for 10 combinations over 4 nodes")
pool.source = True
res2 = pool.map(host, params)
print(pool)
print('\n'.join(res2))
# end of file