Source code for pymor.parallel.interfaces

# This file is part of the pyMOR project (http://www.pymor.org).
# Copyright 2013-2018 pyMOR developers and contributors. All rights reserved.
# License: BSD 2-Clause License (http://opensource.org/licenses/BSD-2-Clause)

from pymor.core.interfaces import BasicInterface, abstractmethod


[docs]class WorkerPoolInterface(BasicInterface): """Interface for parallel worker pools. |WorkerPools| allow to easily parallelize algorithms which involve no or little communication between the workers at runtime. The interface methods give the user simple means to distribute data to workers (:meth:`~WorkerPoolInterface.push`, :meth:`~WorkerPoolInterface.scatter_array`, :meth:`~WorkerPoolInterface.scatter_list`) and execute functions on the distributed data in parallel (:meth:`~WorkerPoolInterface.apply`), collecting the return values from each function call. A single worker can be instructed to execute a function using the :meth:`WorkerPoolInterface.apply_only` method. Finally, a parallelized :meth:`~WorkerPoolInterface.map` function is available, which automatically scatters the data among the workers. All operations are performed synchronously. """
[docs] @abstractmethod def __len__(self): """The number of workers in the pool.""" pass
[docs] @abstractmethod def push(self, obj): """Push a copy of `obj` to all workers of the pool. A |RemoteObject| is returned as a handle to the pushed object. This object can be used as a keyword argument to :meth:`~WorkerPoolInterface.apply`, :meth:`~WorkerPoolInterface.apply_only`, :meth:`~WorkerPoolInterface.map` and will then be transparently mapped to the respective copy of the pushed object on the worker. |Immutable| objects will be pushed only once. If the same |immutable| object is pushed a second time, the returned |RemoteObject| will refer to the already transferred copy. It is therefore safe to use `push` to ensure that a given |immutable| object is available on the worker. No unnecessary copies will be created. Parameters ---------- obj The object to push to all workers. Returns ------- A |RemoteObject| referring to the pushed data. """ pass
[docs] @abstractmethod def scatter_array(self, U, copy=True): """Distribute |VectorArray| evenly among the workers. On each worker a |VectorArray| is created holding an (up to rounding) equal amount of vectors of `U`. The returned |RemoteObject| therefore refers to different data on each of the workers. Parameters ---------- U The |VectorArray| to distribute. copy If `False`, `U` will be emptied during distribution of the vectors. Returns ------- A |RemoteObject| referring to the scattered data. """ pass
[docs] @abstractmethod def scatter_list(self, l): """Distribute list of objects evenly among the workers. On each worker a `list` is created holding an (up to rounding) equal amount of objects of `l`. The returned |RemoteObject| therefore refers to different data on each of the workers. Parameters ---------- l The list (sequence) of objects to distribute. Returns ------- A |RemoteObject| referring to the scattered data. """ pass
[docs] @abstractmethod def apply(self, function, *args, **kwargs): """Apply function in parallel on each worker. This calls `function` on each worker in parallel, passing `args` as positional and `kwargs` as keyword arguments. Keyword arguments which are |RemoteObjects| are automatically mapped to the respective object on the worker. Moreover, keyword arguments which are |immutable| objects that have already been pushed to the workers will not be transmitted again. (|Immutable| objects which have not been pushed before will be transmitted and the remote copy will be destroyed after function execution.) Parameters ---------- function The function to execute on each worker. args The positional arguments for `function`. kwargs The keyword arguments for `function`. Returns ------- List of return values of the function executions, ordered by worker number (from `0` to `len(pool) - 1`). """ pass
[docs] @abstractmethod def apply_only(self, function, worker, *args, **kwargs): """Apply function on a single worker. This calls `function` on on the worker with number `worker`, passing `args` as positional and `kwargs` as keyword arguments. Keyword arguments which are |RemoteObjects| are automatically mapped to the respective object on the worker. Moreover, keyword arguments which are |immutable| objects that have already been pushed to the workers will not be transmitted again. (|Immutable| objects which have not been pushed before will be transmitted and the remote copy will be destroyed after function execution.) Parameters ---------- function The function to execute. worker The worker on which to execute the function. (Number between `0` and `len(pool) - 1`.) args The positional arguments for `function`. kwargs The keyword arguments for `function`. Returns ------- Return value of the function execution. """ pass
[docs] @abstractmethod def map(self, function, *args, **kwargs): """Parallel version of the builtin :func:`map` function. Each positional argument (after `function`) must be a sequence of same length n. `map` calls `function` in parallel on each of these n positional argument combinations, always passing `kwargs` as keyword arguments. Keyword arguments which are |RemoteObjects| are automatically mapped to the respective object on the worker. Moreover, keyword arguments which are |immutable| objects that have already been pushed to the workers will not be transmitted again. (|Immutable| objects which have not been pushed before will be transmitted and the remote copy will be destroyed after function execution.) Parameters ---------- function The function to execute on each worker. args The sequences of positional arguments for `function`. kwargs The keyword arguments for `function`. Returns ------- List of return values of the function executions, ordered by the sequence of positional arguments. """ pass
[docs]class RemoteObjectInterface(object): """Handle to remote data on the workers of a |WorkerPool|. See documentation of :class:`WorkerPoolInterface` for usage of these handles in conjunction with :meth:`~WorkerPoolInterface.apply`, :meth:`~WorkerPoolInterface.scatter_array`, :meth:`~WorkerPoolInterface.scatter_list`. Remote objects can be used as a context manager: when leaving the context, the remote object's :meth:`~RemoteObjectInterface.remove` method is called to ensure proper cleanup of remote resources. Attributes ---------- removed `True`, after :meth:`remove` has been called. """ removed = False @abstractmethod def _remove(self): """Actual implementation of 'remove'.""" pass
[docs] def remove(self): """Remove the remote object from the workers. Remove the object this handle refers to from all workers. Note that the object will only be destroyed if no other object on the worker holds a reference to that object. Moreover, |immutable| objects will only be destroyed if :meth:`remove` has been called on *all* |RemoteObjects| which refer to the object (see :meth:`~WorkerPoolInterface.push`). """ if self.removed: return self._remove() self.removed = True
def __enter__(self): return self def __exit__(self, exc_type, exc_val, exc_tb): self.remove() def __del__(self): self.remove()