/usr/lib/python2.7/dist-packages/Scientific/MPI/core.py is in python-mpi 2.9.4-1.
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# and imports objects from the C module.
#
# Written by Konrad Hinsen <hinsen@cnrs-orleans.fr>
# and Jakob Schiotz <schiotz@fysik.dtu.dk>
# last revision: 2006-11-23
#
"""
Python interface to the Message Passing Interface (MPI)
This module contains a Python interface to the Message Passing
Interface (MPI), and standardized library for message-passing parallel
computing. Please read an introduction to MPI before using this
module; some terms in the documentation do not make much sense unless
you understand the principles of MPI.
This module contains an object, 'world', which represents the
default communicator in MPI. This communicator can be used directly
for sending and receiving data, or other communicators can be
derived from it.
A number of global constants are also defined (L{max}, L{min}, L{prod},
L{sum}, L{land}, L{lor}, L{lxor}, L{band}, L{bor}, L{bxor}, L{maxloc}),
and L{minloc}). They are used to specify the desired operator in calls to
the 'reduce' and 'allreduce' methods of the communicator objects.
@undocumented: core*
"""
class MPIError(EnvironmentError):
"""
MPI call failed
"""
pass
import sys
if sys.modules.has_key('epydoc'):
# Fake code just for the docstrings!
class MPICommunicator:
"""
MPI Communicator
There is no constructor for MPI Communicator objects. The
default communicator is given by Scientific.MPI.world, and
other communicators can only be created by methods on an
existing communicator object.
A communicator object has two read-only attributes: 'rank' is
an integer which indicates the rank of the current process in
the communicator, and 'size' is an integer equal to the number
of processes that participate in the communicator.
"""
def duplicate(self):
"""
@returns: a new communicator with the same properties
as the original one
@rtype: L{MPICommunicator}
"""
pass
def subset(self, ranks):
"""
Create a communicator for a subset of the processes
The method should be called by all processes simultaneously. The
return value will be the new communicator on those
processes listed in C{ranks} and C{None} for the rest.
@param ranks: a list of ranks, one for each process that should
belong to the new communicator
@type ranks: C{list} of C{int}
@returns: a new communicator containing a subset
of the processes participating in the original one
"""
pass
def send(self, data, destination, tag):
"""
Send data to another process (blocking)
@param data: the data to be sent
@type data: C{str} or C{Numeric.array}. Array arguments
must have contiguous storage. General object arrays
are not allowed.
@param destination: the rank of the destination process
@type destination: C{int}
@param tag: Identifier
@type tag: C{int}
"""
pass
def nonblockingSend(self, data, destination, tag):
"""
Send data to another process (non-blocking)
@param data: the data to be sent
@type data: C{str} or C{Numeric.array}. Array arguments
must have contiguous storage. General object arrays
are not allowed.
@param destination: the rank of the destination process
@type destination: C{int}
@param tag: Identifier
@type tag: C{int}
@returns: MPI request object (used to wait for completion)
@rtype: L{MPIRequest}
"""
pass
def receive(self, data, source=None, tag=None):
"""
Receive data from another process (blocking)
@param data: either a contiguous array object, or a one-letter
typecode (in practice, one would use Numeric.Int,
Numeric.Float, etc.). If an array, the data is
copied to the array, whic must have the right shape.
If a typecode, an array of that type is created
and used as the buffer for incoming data.
@type data: C{Numeric.array} or C{str}
@param source: the rank of the process from which data is
accepted. C{None} means data is accepted from
any process.
@type source: C{int} or C{NoneType}
@param tag: Identifier that acts as a filter; only messages
with a matching tag are received. A value of C{None}
means that any tag will match.
@type tag: C{int} or C{NoneType}
@returns: a tuple containing four elements:
the array containing the data, the source process rank
(an C{int}), the message tag (an C{int}), and the
number of elements that were received (an C{int}).
@rtype: C{tuple}
"""
pass
def receiveString(self, source=None, tag=None):
"""
Receive string data from another process (blocking)
@param source: the rank of the process from which data is
accepted. C{None} means data is accepted from
any process.
@type source: C{int} or C{NoneType}
@param tag: Identifier that acts as a filter; only messages
with a matching tag are received. A value of C{None}
means that any tag will match.
@type tag: C{int} or C{NoneType}
@returns: a tuple containing three elements:
the string containing the data, the source process rank
(an C{int}), the message tag (an C{int}).
@rtype: C{tuple}
"""
pass
def nonblockingReceive(self, data, source=None, tag=None):
"""
Receive data from another process (non-blocking)
@param data: a contiguous array object to which the incoming
data is copied. It must have the right shape.
@type data: C{Numeric.array}
@param source: the rank of the process from which data is
accepted. C{None} means data is accepted from
any process.
@type source: C{int} or C{NoneType}
@param tag: Identifier that acts as a filter; only messages
with a matching tag are received. A value of C{None}
means that any tag will match.
@type tag: C{int} or C{NoneType}
@returns: MPI request object (used to wait for completion and
obtain the received data)
@rtype: L{MPIRequest}
"""
pass
def nonblockingProbe(self, source=None, tag=None):
"""
Check for incoming messages
@param source: the rank of the process from which messages are
accepted. C{None} means data is accepted from
any process.
@type source: C{int} or C{NoneType}
@param tag: Identifier that acts as a filter; only messages
with a matching tag are considered. A value of C{None}
means that any tag will match.
@type tag: C{int} or C{NoneType}
@returns: C{None} if no messages are available, otherwise
a tuple containing the source rank and the tag
@rtype: C{NoneType} or C{tuple}
"""
pass
def broadcast(self, array, root):
"""
Send data to all processes
@param array: an array containing the data to be sent on the
sending process and serving as a buffer for the
incoming data on all processes. The shape and type
of the array must be the same on all processes.
@type array: Numeric.array
@param root: the rank of the sending process
@type root: C{int}
@note: The data is sent to all processes, including the sending
one.
"""
pass
def share(self, send, receive):
"""
Distribute data from each processpr to all other processesors
@param send: an array of identical shape and type on all processes.
It contains on each process the data that is sent.
@type send: C{Numeric.array}
@param receive: an array whose type is the same as for the send
array and which has an additional dimension
(the first one) whose length is the number of
processes. After the call, the value
of receive[i] is equal to the contents of the
array send in process i.
@type receive: C{Numeric.array}
"""
pass
def barrier(self):
"""
Wait until all processes in the communicator have
called the same method, then all processes continue.
"""
pass
def abort(self, error_code):
"""
Abort all processes associated with the communicator.
For emergency use only.
@param error_code: error code passed back to the calling
program (usually a shell) under most
Unix implementations of MPI
@type error_code: C{int}
"""
pass
def reduce(self, sendbuffer, receivebuffer, operation, root):
"""
Combine data from all processes and send result to one
@param sendbuffer: an array holding the data that each
process contributes
@type sendbuffer: C{Numeric.array}
@param receivebuffer: an array acting as a buffer for the
result of the reduction. Used only
by the process whose rank is root
@type receivebuffer: C{Numeric.array}
@param operation: one of the operation objects: L{max},
L{min}, L{prod}, L{sum}, L{land}, L{lor},
L{lxor}, L{band}, L{bor}, L{bxor},
L{maxloc} and L{minloc}
@type operation: MPIOperationObject
@param root: the rank of the process that received the result
@type root: C{int}
"""
pass
def allreduce(self, sendbuffer, receivebuffer, operation):
"""
Combine data from all processes and send result to all
@param sendbuffer: an array holding the data that each
process contributes
@type sendbuffer: C{Numeric.array}
@param receivebuffer: an array acting as a buffer for the
result of the reduction
@type receivebuffer: C{Numeric.array}
@param operation: one of the operation objects: L{max},
L{min}, L{prod}, L{sum}, L{land}, L{lor},
L{lxor}, L{band}, L{bor}, L{bxor},
L{maxloc} and L{minloc}
@type operation: MPIOperationObject
"""
pass
class MPIRequest:
"""
MPI Request
There is no constructor for MPI Request objects. They are
returned by nonblocking send and receives, and are used to
query the status of the message.
"""
def wait(self):
"""
Wait till the communication has completed.
If the operation was a nonblocking send, there is no return value.
If the operation was a nonblocking receive, the return
value is a tuple containing four elements: the array
containing the data, the source process rank (an integer),
the message tag (an integer), and the number of elements
that were received (an integer).
"""
pass
def test(self):
"""
Test if communications have completed.
If the operation was a nonblocking send, it returns 0 if
the operation has not completed, and 1 if it has.
If the operation was a nonblocking receive, 0 is returned
if the operation was not completed, and a tuple containing
four elements if it was completed. The four elements are:
the array containing the data, the source process rank (an
integer), the message tag (an integer), and the number of
elements that were received (an integer).
Once a test has been successful (i.e. the operation has
completed), it is no longer possible to call wait() or
test() on the MPI Request object.
"""
pass
world = MPICommunicator()
world.rank = 0
world.size = 1
if 1:
class MPIOperationObject:
pass
class max(MPIOperationObject):
"""The 'maximum' operation in reduce/allreduce communications."""
pass
class min(MPIOperationObject):
"""The 'minimum' operation in reduce/allreduce communications."""
pass
class prod(MPIOperationObject):
"""The 'product' operation in reduce/allreduce communications."""
pass
class sum(MPIOperationObject):
"""The 'sum' operation in reduce/allreduce communications."""
pass
class land(MPIOperationObject):
"""The 'logical and' operation in reduce/allreduce communications."""
pass
class lor(MPIOperationObject):
"""The 'logical or' operation in reduce/allreduce communications."""
pass
class lxor(MPIOperationObject):
"""The 'logical exclusive-or' operation."""
pass
class band(MPIOperationObject):
"""The 'bitwise and' operation in reduce/allreduce communications."""
pass
class bor(MPIOperationObject):
"""The 'bitwise or' operation in reduce/allreduce communications."""
pass
class bxor(MPIOperationObject):
"""The 'bitwise exclusive-or' operation."""
pass
class maxloc(MPIOperationObject):
"""The 'location of the maximum' operation."""
pass
class minloc(MPIOperationObject):
"""The 'location of the minimum' operation."""
pass
class replace(MPIOperationObject):
"""The 'replace' operation. (MPI 2.0)"""
pass
_C_API = None
else:
try:
from Scientific_mpi import *
from Scientific_mpi import _C_API, _registerErrorObject
_registerErrorObject(MPIError)
del _registerErrorObject
except ImportError:
import Scientific.N as Numeric
_C_API = None
class DummyCommunicator:
def __init__(self):
self.size = 1
self.rank = 0
self.messages = []
def duplicate(self):
return DummyCommunicator()
def send(self, data, destination, tag):
if destination != 0:
raise MPIError("invalid MPI destination")
self.messages.append((tag, Numeric.array(data, copy=1).ravel()))
def nonblockingSend(self, data, destination, tag):
self.send(data, destination, tag)
return DummyRequest(None)
def receive(self, array, source=None, tag=None):
if source != 0 and source != None:
raise MPIError("invalid MPI source")
for i in range(len(self.messages)):
data_tag, data = self.messages[i]
if tag is None or tag == data_tag:
del self.messages[i]
return data, 0, data_tag, len(data)
raise MPIError("no message received")
def receiveString(self, source=None, tag=None):
array, source, tag, length = self.receive(source, tag)
return array.tostring(), source, tag
def nonblockingReceive(self, array, source=None, tag=None):
return DummyRequest(self.receive(array, source, tag))
def nonblockingProbe(self, source=None, tag=None):
if source != 0 and source != None:
raise MPIError, "invalid MPI source"
for i in range(len(self.messages)):
data_tag, data = self.messages[i]
if tag is None or tag == data_tag:
return 0, data_tag
return None
def broadcast(self, array, root):
if root != 0:
raise MPIError("invalid MPI rank")
return array
def share(self, send, receive):
receive[0] = send
def barrier(self):
pass
def abort(self):
raise MPIError("abort")
class DummyRequest:
def __init__(self, arg):
self.arg = arg
def wait(self):
return self.arg
world = DummyCommunicator()
del sys
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