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// $Id: work_stream.h 20677 2010-02-23 23:03:29Z kanschat $
// Version: $Name$
//
// Copyright (C) 2008, 2009, 2010 by the deal.II authors
//
// This file is subject to QPL and may not be distributed
// without copyright and license information. Please refer
// to the file deal.II/doc/license.html for the text and
// further information on this license.
//
//---------------------------------------------------------------------------
#ifndef __deal2__work_stream_h
#define __deal2__work_stream_h
#include <base/config.h>
#include <base/multithread_info.h>
#include <base/template_constraints.h>
#include <base/std_cxx1x/function.h>
#include <base/std_cxx1x/bind.h>
#if DEAL_II_USE_MT == 1
# include <base/thread_management.h>
# include <tbb/pipeline.h>
#endif
#include <vector>
#include <utility>
DEAL_II_NAMESPACE_OPEN
/**
* A class whose main template function supports running multiple
* threads each of which operates on a subset of the given range of
* objects. The class uses the Intel Threading Building Blocks (TBB)
* to load balance the individual subranges onto the available
* threads. For a lengthy discussion of the rationale of this class,
* see the @ref threads "Parallel computing with multiple processors"
* module.
*
* The class is built on the following premise: One frequently has some work
* that needs to be done on a sequence of objects; a prototypical example is
* assembling cell contributions to a system matrix or right hand side. In
* many such examples, part of the work can be done entirely independently and
* in parallel, possibly using several processor cores on a machine with
* shared memory. However, some other part of this work may need to be
* synchronised and be done in order. In the example of assembling a matrix,
* the computation of local contributions can be done entirely in parallel,
* but copying the the local contributions into the global matrix requires
* some care: First, several threads can't write at the same time, but need to
* synchronise writing using a mutex; secondly, we want the order in which
* local contributions are added to the global matrix to be always the same
* because floating point addition is not commutative and adding local
* contributions to the global matrix in different orders leads to subtly
* different results that can affect the number of iterations for iterative
* solvers as well as the round-off error in the solution in random
* ways. Consequently, we want to ensure that only one thread at a time writes
* into the global matrix, and that results are copied in a stable and
* reproducible order.
*
* This class implements a framework for this work model. It works with a
* stream of objects given by an iterator range, runs a worker function in
* parallel on all of these objects and then passes each object to a
* postprocessor function that runs sequentially and gets objects in exactly
* the order in which they appear in the input iterator range. None of the
* synchronisation work is exposed to the user of this class.
*
* Internally, the range given to the run() function of this class is split
* into a sequence of "items", which are then distributed according to some
* %internal algorithm onto the number of available threads. An item is an
* element of the range of iterators on which we are to operate; for example,
* for the purpose of assembling matrices or evaluating error indicators, an
* item could be a cell. The TBB library determines how many threads are
* created (typically as many as there are processor cores), but the number of
* items that may be active at any given time is specified by the argument to
* the constructor. It should be bigger or equal to the number of processor
* cores - the default is four times the number of cores on the current system.
*
* Items are created upon request by the TBB whenever one of the worker
* threads is idle or is expected to become idle. It is then handed off to a
* worker function, typically a member function of a main class. These worker
* functions are run in parallel on a number of threads, and there is no
* guarantee that they are asked to work on items in any particular order, in
* particular not necessarily in the order in which items are generated from
* the iterator range.
*
* Typically, worker functions need additional data, for example FEValues
* objects, input data vectors, etc, some of which can not be shared among
* threads. To this end, the run() function takes another template argument,
* ScratchData, which designates a type objects of which are stored with
* each item and which threads can use as private data without having to
* share them with other threads. The run() function takes an additional
* argument with an object of type ScratchData that is going to be copied
* for the arguments passed to each of the worker functions.
*
* In addition, worker functions store their results in objects of template type
* CopyData. These are then handed off to a separate function, called copier,
* that may use the stored results to transfer them into permanent
* storage. For example, it may copy the results of local contributions to a
* matrix computed by a worker function into the global matrix. In contrast to
* the worker function, however, only one instance of the copier is run at any
* given time; it can therefore safely copy local contributions into the
* global matrix without the need to lock the global object using a mutex or
* similar means. Furthermore, it is guaranteed that the copier is run with
* CopyData objects in the same order in which their associated items
* were created; consequently, even if worker threads may compute results in
* unspecified order, the copier always receives the results in exactly the
* same order as the items were created.
*
* Once an item is processed by the copier, it is deleted and the
* ScratchData and CopyData objects that were used in its computation
* are considered unused and may be re-used for the next invokation of
* the worker function, on this or another thread.
*
* This class only really works in parallel when multithread mode was selected
* during deal.II configuration. Otherwise it simply works on each item
* sequentially.
*
* @ingroup threads
* @author Wolfgang Bangerth, 2007, 2008, 2009
*/
namespace WorkStream
{
#if DEAL_II_USE_MT == 1
namespace internal
{
/**
* A class that creates a sequence of
* items from a range of iterators.
*/
template <typename Iterator,
typename ScratchData,
typename CopyData>
class IteratorRangeToItemStream : public tbb::filter
{
public:
/**
* A data type that we use to identify
* items to be worked on.
*
* The first element indicates an array
* of iterators to work on; the second
* the scratch space; the third an
* array of copy data spaces; and the
* last the number of elements to work
* on. This last argument is an integer
* between one and chunk_size. The
* arrays have a length of chunk_size.
*/
typedef
std_cxx1x::tuple<std::vector<Iterator>,
ScratchData*,
std::vector<CopyData>,
unsigned int>
ItemType;
/**
* Constructor. Take an iterator
* range, the size of a buffer that
* can hold items, and the sample
* additional data object that will
* be passed to each worker and
* copier function invokation.
*/
IteratorRangeToItemStream (const Iterator &begin,
const Iterator &end,
const unsigned int buffer_size,
const unsigned int chunk_size,
const ScratchData &sample_scratch_data,
const CopyData &sample_copy_data)
:
tbb::filter (/*is_serial=*/true),
remaining_iterator_range (begin, end),
ring_buffer (buffer_size),
n_emitted_items (0),
chunk_size (chunk_size)
{
// initialize copies of
// additional_data. since
// this is frequently
// expensive (creating
// FEValues objects etc) do
// that in parallel
Threads::TaskGroup<> tasks;
for (unsigned int i=0; i<ring_buffer.size(); ++i)
tasks += Threads::new_task (&IteratorRangeToItemStream::init_buffer_elements,
*this,
i,
std_cxx1x::cref(sample_scratch_data),
std_cxx1x::cref(sample_copy_data));
tasks.join_all ();
}
/**
* Destructor.
*/
~IteratorRangeToItemStream ()
{
for (unsigned int i=0; i<ring_buffer.size(); ++i)
delete std_cxx1x::get<1>(ring_buffer[i]);
}
/**
* Create a item and return a
* pointer to it.
*/
virtual void * operator () (void *)
{
// store the current
// position of the pointer
ItemType *current_item
= &ring_buffer[n_emitted_items % ring_buffer.size()];
// initialize the next item. it may
// consist of at most chunk_size
// elements
std_cxx1x::get<3>(*current_item) = 0;
while ((remaining_iterator_range.first !=
remaining_iterator_range.second)
&&
(std_cxx1x::get<3>(*current_item) < chunk_size))
{
std_cxx1x::get<0>(*current_item)[std_cxx1x::get<3>(*current_item)]
= remaining_iterator_range.first;
++remaining_iterator_range.first;
++std_cxx1x::get<3>(*current_item);
}
if (std_cxx1x::get<3>(*current_item) == 0)
// there were no items
// left. terminate the pipeline
return 0;
else
{
++n_emitted_items;
return current_item;
}
}
private:
/**
* The interval of iterators still to
* be worked on. This range will shrink
* over time.
*/
std::pair<Iterator,Iterator> remaining_iterator_range;
/**
* A ring buffer that will store items.
*/
std::vector<ItemType> ring_buffer;
/**
* Counter for the number of emitted
* items. Each item may consist of up
* to chunk_size iterator elements.
*/
unsigned int n_emitted_items;
/**
* Number of elements of the
* iterator range that each
* thread should work on
* sequentially; a large number
* makes sure that each thread
* gets a significant amount of
* work before the next task
* switch happens, whereas a
* small number is better for
* load balancing.
*/
const unsigned int chunk_size;
/**
* Initialize the pointers and vector
* elements in the specified entry of
* the ring buffer.
*/
void init_buffer_elements (const unsigned int element,
const ScratchData &sample_scratch_data,
const CopyData &sample_copy_data)
{
Assert (std_cxx1x::get<1>(ring_buffer[element]) == 0,
ExcInternalError());
std_cxx1x::get<0>(ring_buffer[element])
.resize (chunk_size, remaining_iterator_range.second);
std_cxx1x::get<1>(ring_buffer[element])
= new ScratchData(sample_scratch_data);
std_cxx1x::get<2>(ring_buffer[element])
.resize (chunk_size, sample_copy_data);
}
};
/**
* A class that manages calling the
* worker function on a number of
* parallel threads. Note that it is, in
* the TBB notation, a filter that can
* run in parallel.
*/
template <typename Iterator,
typename ScratchData,
typename CopyData>
class Worker : public tbb::filter
{
public:
/**
* Constructor. Takes a
* reference to the object on
* which we will operate as
* well as a pointer to the
* function that will do the
* assembly.
*/
Worker (const std_cxx1x::function<void (const Iterator &,
ScratchData &,
CopyData &)> &worker)
:
tbb::filter (/* is_serial= */ false),
worker (worker)
{}
/**
* Work on an item.
*/
void * operator () (void *item)
{
// first unpack the current item
typedef
typename IteratorRangeToItemStream<Iterator,ScratchData,CopyData>::ItemType
ItemType;
ItemType *current_item = reinterpret_cast<ItemType*> (item);
// then call the worker function on
// each element of the chunk we
// were given
for (unsigned int i=0; i<std_cxx1x::get<3>(*current_item); ++i)
worker (std_cxx1x::get<0>(*current_item)[i],
*std_cxx1x::get<1>(*current_item),
std_cxx1x::get<2>(*current_item)[i]);
// then return the original pointer
// to the now modified object
return item;
}
private:
/**
* Pointer to the function
* that does the assembling
* on the sequence of cells.
*/
const std_cxx1x::function<void (const Iterator &,
ScratchData &,
CopyData &)> worker;
};
/**
* A class that manages calling the
* copier function. Note that it is, in
* the TBB notation, a filter that runs
* sequentially, ensuring that all items
* are copied in the same order in which
* they are created.
*/
template <typename Iterator,
typename ScratchData,
typename CopyData>
class Copier : public tbb::filter
{
public:
/**
* Constructor. Takes a
* reference to the object on
* which we will operate as
* well as a pointer to the
* function that will do the
* copying from the
* additional data object to
* the global matrix or
* similar.
*/
Copier (const std_cxx1x::function<void (const CopyData &)> &copier)
:
tbb::filter (/* is_serial= */ true),
copier (copier)
{}
/**
* Work on a single item.
*/
void * operator () (void *item)
{
// first unpack the current item
typedef
typename IteratorRangeToItemStream<Iterator,ScratchData,CopyData>::ItemType
ItemType;
ItemType *current_item = reinterpret_cast<ItemType*> (item);
// initiate copying data
for (unsigned int i=0; i<std_cxx1x::get<3>(*current_item); ++i)
copier (std_cxx1x::get<2>(*current_item)[i]);
// return an invalid
// item since we are at
// the end of the
// pipeline
return 0;
}
private:
/**
* Pointer to the function
* that does the copying of
* data.
*/
const std_cxx1x::function<void (const CopyData &)> copier;
};
}
#endif // DEAL_II_USE_MT
/**
* This is the main function of the
* WorkStream concept, doing work as
* described in the introduction to this
* namespace.
*
* This is the function that can be used
* for worker and copier objects that are
* either pointers to non-member
* functions or objects that allow to be
* called with an operator(), for example
* objects created by std::bind.
*
* The argument passed as @p end must be
* convertible to the same type as
* @p begin, but doesn't have to be of the
* same type itself. This allows to write
* code like
* <code>WorkStream().run(dof_handler.begin_active(),
* dof_handler.end(), ...</code> where
* the first is of type
* DoFHandler::active_cell_iterator
* whereas the second is of type
* DoFHandler::raw_cell_iterator.
*
* The two data types
* <tt>ScratchData</tt> and
* <tt>CopyData</tt> need to have a
* working copy
* constructor. <tt>ScratchData</tt>
* is only used in the
* <tt>worker</tt> function, while
* <tt>CopyData</tt> is the object
* passed from the <tt>worker</tt>
* to the <tt>copier</tt>.
*
* The @p queue_length argument indicates
* the number of items that can be live
* at any given time. Each item consists
* of @p chunk_size elements of the input
* stream that will be worked on by the
* worker and copier functions one after
* the other on the same thread.
*/
template <typename Worker,
typename Copier,
typename Iterator,
typename ScratchData,
typename CopyData>
void
run (const Iterator &begin,
const typename identity<Iterator>::type &end,
Worker worker,
Copier copier,
const ScratchData &sample_scratch_data,
const CopyData &sample_copy_data,
const unsigned int queue_length = 2*multithread_info.n_default_threads,
const unsigned int chunk_size = 8)
{
Assert (queue_length > 0,
ExcMessage ("The queue length must be at least one, and preferably "
"larger than the number of processors on this system."));
Assert (chunk_size > 0,
ExcMessage ("The chunk_size must be at least one."));
// if no work then skip. (only use
// operator!= for iterators since we may
// not have an equality comparison
// operator)
if (!(begin != end))
return;
#if DEAL_II_USE_MT == 1
// create the three stages of the
// pipeline
internal::IteratorRangeToItemStream<Iterator,ScratchData,CopyData>
iterator_range_to_item_stream (begin, end,
queue_length * chunk_size,
chunk_size,
sample_scratch_data,
sample_copy_data);
internal::Worker<Iterator, ScratchData, CopyData> worker_filter (worker);
internal::Copier<Iterator, ScratchData, CopyData> copier_filter (copier);
// now create a pipeline from
// these stages
tbb::pipeline assembly_line;
assembly_line.add_filter (iterator_range_to_item_stream);
assembly_line.add_filter (worker_filter);
assembly_line.add_filter (copier_filter);
// and run it
assembly_line.run (queue_length);
assembly_line.clear ();
#else
// need to copy the sample since it is
// marked const
ScratchData scratch_data = sample_scratch_data;
CopyData copy_data = sample_copy_data;
for (Iterator i=begin; i!=end; ++i)
{
worker (i, scratch_data, copy_data);
copier (copy_data);
}
#endif
}
/**
* This is the main function of the
* WorkStream concept, doing work as
* described in the introduction to this
* namespace.
*
* This is the function that can be
* used for worker and copier functions
* that are member functions of a class.
*
* The argument passed as @p end must be
* convertible to the same type as
* @p begin, but doesn't have to be of the
* same type itself. This allows to write
* code like
* <code>WorkStream().run(dof_handler.begin_active(),
* dof_handler.end(), ...</code> where
* the first is of type
* DoFHandler::active_cell_iterator
* whereas the second is of type
* DoFHandler::raw_cell_iterator.
*
* The @p queue_length argument indicates
* the number of items that can be live
* at any given time. Each item consists
* of @p chunk_size elements of the input
* stream that will be worked on by the
* worker and copier functions one after
* the other on the same thread.
*/
template <typename MainClass,
typename Iterator,
typename ScratchData,
typename CopyData>
void
run (const Iterator &begin,
const typename identity<Iterator>::type &end,
MainClass &main_object,
void (MainClass::*worker) (const Iterator &,
ScratchData &,
CopyData &),
void (MainClass::*copier) (const CopyData &),
const ScratchData &sample_scratch_data,
const CopyData &sample_copy_data,
const unsigned int queue_length = 2*multithread_info.n_default_threads,
const unsigned int chunk_size = 8)
{
// forward to the other function
run (begin, end,
std_cxx1x::bind (worker,
std_cxx1x::ref (main_object),
_1, _2, _3),
std_cxx1x::bind (copier,
std_cxx1x::ref (main_object),
_1),
sample_scratch_data,
sample_copy_data,
queue_length,
chunk_size);
}
}
DEAL_II_NAMESPACE_CLOSE
//---------------------------- work_stream.h ---------------------------
// end of #ifndef __deal2__work_stream_h
#endif
//---------------------------- work_stream.h ---------------------------
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