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// $Id: petsc_parallel_vector.h 21358 2010-06-24 23:38:14Z bangerth $
// Version: $Name$
//
// Copyright (C) 2004, 2005, 2006, 2007, 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__petsc_parallel_vector_h
#define __deal2__petsc_parallel_vector_h
#include <base/config.h>
#ifdef DEAL_II_USE_PETSC
# include <base/subscriptor.h>
# include <lac/exceptions.h>
# include <lac/vector.h>
# include <lac/petsc_vector_base.h>
# include <base/index_set.h>
DEAL_II_NAMESPACE_OPEN
// forward declaration
template <typename> class Vector;
class IndexSet;
/*! @addtogroup PETScWrappers
*@{
*/
namespace PETScWrappers
{
/**
* Namespace for PETSc classes that work in parallel over MPI, such as
* distributed vectors and matrices.
*
* @ingroup PETScWrappers
* @author Wolfgang Bangerth, 2004
*/
namespace MPI
{
/**
* Implementation of a parallel vector class based on PETSC and using MPI
* communication to synchronise distributed operations. All the functionality
* is actually in the base class, except for the calls to generate a
* parallel vector. This is possible since PETSc only works on an abstract
* vector type and internally distributes to functions that do the actual work
* depending on the actual vector type (much like using virtual
* functions). Only the functions creating a vector of specific type differ,
* and are implemented in this particular class.
*
* <h3>Parallel communication model</h3>
*
* The parallel functionality of PETSc is built on top of the Message Passing
* Interface (MPI). MPI's communication model is built on collective
* communications: if one process wants something from another, that other
* process has to be willing to accept this communication. A process cannot
* query data from another process by calling a remote function, without that
* other process expecting such a transaction. The consequence is that most of
* the operations in the base class of this class have to be called
* collectively. For example, if you want to compute the l2 norm of a parallel
* vector, @em all processes across which this vector is shared have to call
* the @p l2_norm function. If you don't do this, but instead only call the @p
* l2_norm function on one process, then the following happens: This one
* process will call one of the collective MPI functions and wait for all the
* other processes to join in on this. Since the other processes don't call
* this function, you will either get a time-out on the first process, or,
* worse, by the time the next a callto a PETSc function generates an MPI
* message on the other processes , you will get a cryptic message that only a
* subset of processes attempted a communication. These bugs can be very hard
* to figure out, unless you are well-acquainted with the communication model
* of MPI, and know which functions may generate MPI messages.
*
* One particular case, where an MPI message may be generated unexpectedly is
* discussed below.
*
*
* <h3>Accessing individual elements of a vector</h3>
*
* PETSc does allow read access to individual elements of a vector, but in the
* distributed case only to elements that are stored locally. We implement
* this through calls like <tt>d=vec(i)</tt>. However, if you access an
* element outside the locally stored range, an exception is generated.
*
* In contrast to read access, PETSc (and the respective deal.II wrapper
* classes) allow to write (or add) to individual elements of vectors, even if
* they are stored on a different process. You can do this writing, for
* example, <tt>vec(i)=d</tt> or <tt>vec(i)+=d</tt>, or similar
* operations. There is one catch, however, that may lead to very confusing
* error messages: PETSc requires application programs to call the compress()
* function when they switch from adding, to elements to writing to
* elements. The reasoning is that all processes might accumulate addition
* operations to elements, even if multiple processes write to the same
* elements. By the time we call compress() the next time, all these additions
* are executed. However, if one process adds to an element, and another
* overwrites to it, the order of execution would yield non-deterministic
* behavior if we don't make sure that a synchronisation with compress()
* happens in between.
*
* In order to make sure these calls to compress() happen at the appropriate
* time, the deal.II wrappers keep a state variable that store which is the
* presently allowed operation: additions or writes. If it encounters an
* operation of the opposite kind, it calls compress() and flips the
* state. This can sometimes lead to very confusing behavior, in code that may
* for example look like this:
* @verbatim
* PETScWrappers::MPI::Vector vector;
* ...
* // do some write operations on the vector
* for (unsigned int i=0; i<vector.size(); ++i)
* vector(i) = i;
*
* // do some additions to vector elements, but
* // only for some elements
* for (unsigned int i=0; i<vector.size(); ++i)
* if (some_condition(i) == true)
* vector(i) += 1;
*
* // do another collective operation
* const double norm = vector.l2_norm();
* @endverbatim
*
* This code can run into trouble: by the time we see the first addition
* operation, we need to flush the overwrite buffers for the vector, and the
* deal.II library will do so by calling compress(). However, it will only do
* so for all processes that actually do an addition -- if the condition is
* never true for one of the processes, then this one will not get to the
* actual compress() call, whereas all the other ones do. This gets us into
* trouble, since all the other processes hang in the call to flush the write
* buffers, while the one other process advances to the call to compute the l2
* norm. At this time, you will get an error that some operation was attempted
* by only a subset of processes. This behavior may seem surprising, unless
* you know that write/addition operations on single elements may trigger this
* behavior.
*
* The problem described here may be avoided by placing additional calls to
* compress(), or making sure that all processes do the same type of
* operations at the same time, for example by placing zero additions if
* necessary.
*
* @ingroup PETScWrappers
* @ingroup Vectors
* @author Wolfgang Bangerth, 2004
*/
class Vector : public VectorBase
{
public:
/**
* Default constructor. Initialize the
* vector as empty.
*/
Vector ();
/**
* Constructor. Set dimension to
* @p n and initialize all
* elements with zero.
*
* @arg local_size denotes the size
* of the chunk that shall be stored
* on the present process.
*
* @arg communicator denotes the MPI
* communicator over which the
* different parts of the vector
* shall communicate
*
* The constructor is made explicit
* to avoid accidents like this:
* <tt>v=0;</tt>. Presumably, the user
* wants to set every element of the
* vector to zero, but instead, what
* happens is this call:
* <tt>v=Vector@<number@>(0);</tt>, i.e. the
* vector is replaced by one of
* length zero.
*/
explicit Vector (const MPI_Comm &communicator,
const unsigned int n,
const unsigned int local_size);
/**
* Copy-constructor from deal.II
* vectors. Sets the dimension to that
* of the given vector, and copies all
* elements.
*
* @arg local_size denotes the size
* of the chunk that shall be stored
* on the present process.
*
* @arg communicator denotes the MPI
* communicator over which the
* different parts of the vector
* shall communicate
*/
template <typename Number>
explicit Vector (const MPI_Comm &communicator,
const dealii::Vector<Number> &v,
const unsigned int local_size);
/**
* Copy-constructor the
* values from a PETSc wrapper vector
* class.
*
* @arg local_size denotes the size
* of the chunk that shall be stored
* on the present process.
*
* @arg communicator denotes the MPI
* communicator over which the
* different parts of the vector
* shall communicate
*/
explicit Vector (const MPI_Comm &communicator,
const VectorBase &v,
const unsigned int local_size);
/**
* Constructs a new parallel PETSc
* vector from an Indexset. Note that
* @p local must be contiguous and
* the global size of the vector is
* determined by local.size(). The
* global indices in @p ghost are
* supplied as ghost indices that can
* also be read locally.
*
* Note that the @p ghost IndexSet
* may be empty and that any indices
* already contained in @p local are
* ignored during construction. That
* way, the ghost parameter can equal
* the set of locally relevant
* degrees of freedom.
*/
explicit Vector (const MPI_Comm &communicator,
const IndexSet & local,
const IndexSet & ghost = IndexSet(0));
/**
* Copy the given vector. Resize the
* present vector if necessary. Also
* take over the MPI communicator of
* @p v.
*/
Vector & operator = (const Vector &v);
/**
* Copy the given sequential
* (non-distributed) vector
* into the present parallel
* vector. It is assumed that
* they have the same size,
* and this operation does
* not change the
* partitioning of the
* parallel vector by which
* its elements are
* distributed across several
* MPI processes. What this
* operation therefore does
* is to copy that chunk of
* the given vector @p v that
* corresponds to elements of
* the target vector that are
* stored locally, and copies
* them. Elements that are
* not stored locally are not
* touched.
*
* This being a parallel
* vector, you must make sure
* that @em all processes
* call this function at the
* same time. It is not
* possible to change the
* local part of a parallel
* vector on only one
* process, independent of
* what other processes do,
* with this function.
*/
Vector & operator = (const PETScWrappers::Vector &v);
/**
* Set all components of the vector to
* the given number @p s. Simply pass
* this down to the base class, but we
* still need to declare this function
* to make the example given in the
* discussion about making the
* constructor explicit work.
*/
Vector & operator = (const PetscScalar s);
/**
* Copy the values of a deal.II vector
* (as opposed to those of the PETSc
* vector wrapper class) into this
* object.
*
* Contrary to the case of sequential
* vectors, this operators requires
* that the present vector already
* has the correct size, since we
* need to have a partition and a
* communicator present which we
* otherwise can't get from the
* source vector.
*/
template <typename number>
Vector & operator = (const dealii::Vector<number> &v);
/**
* Change the dimension of the vector
* to @p N. It is unspecified how
* resizing the vector affects the
* memory allocation of this object;
* i.e., it is not guaranteed that
* resizing it to a smaller size
* actually also reduces memory
* consumption, or if for efficiency
* the same amount of memory is used
*
* @p local_size denotes how many
* of the @p N values shall be
* stored locally on the present
* process.
* for less data.
*
* @p communicator denotes the MPI
* communicator henceforth to be used
* for this vector.
*
* If @p fast is false, the vector
* is filled by zeros. Otherwise, the
* elements are left an unspecified
* state.
*/
void reinit (const MPI_Comm &communicator,
const unsigned int N,
const unsigned int local_size,
const bool fast = false);
/**
* Change the dimension to that of
* the vector @p v, and also take
* over the partitioning into local
* sizes as well as the MPI
* communicator. The same applies as
* for the other @p reinit function.
*
* The elements of @p v are not
* copied, i.e. this function is the
* same as calling
* <tt>reinit(v.size(),
* v.local_size(), fast)</tt>.
*/
void reinit (const Vector &v,
const bool fast = false);
/**
* Reinit as a ghosted vector. See
* constructor with same signature
* for more details.
*/
void reinit (const MPI_Comm &communicator,
const IndexSet & local,
const IndexSet & ghost = IndexSet(0));
/**
* Return a reference to the MPI
* communicator object in use with
* this vector.
*/
const MPI_Comm & get_mpi_communicator () const;
protected:
/**
* Create a vector of length
* @p n. For this class, we create a
* parallel vector. @p n denotes
* the total size of the vector to be
* created. @p local_size denotes
* how many of these elements shall
* be stored locally.
*/
virtual void create_vector (const unsigned int n,
const unsigned int local_size);
/**
* Create a vector of global length
* @p n, local size @p local_size and
* with the specified ghost
* indices. Note that you need to
* call update_ghost_values() before
* accessing those.
*/
virtual void create_vector (const unsigned int n,
const unsigned int local_size,
const IndexSet & ghostnodes);
private:
/**
* Copy of the communicator object to
* be used for this parallel vector.
*/
MPI_Comm communicator;
};
// ------------------ template and inline functions -------------
/**
* Global function @p swap which overloads the default implementation
* of the C++ standard library which uses a temporary object. The
* function simply exchanges the data of the two vectors.
*
* @relates PETScWrappers::MPI::Vector
* @author Wolfgang Bangerth, 2004
*/
inline
void swap (Vector &u, Vector &v)
{
u.swap (v);
}
#ifndef DOXYGEN
template <typename number>
Vector::Vector (const MPI_Comm &communicator,
const dealii::Vector<number> &v,
const unsigned int local_size)
:
communicator (communicator)
{
Vector::create_vector (v.size(), local_size);
*this = v;
}
inline
Vector &
Vector::operator = (const PetscScalar s)
{
VectorBase::operator = (s);
return *this;
}
inline
Vector &
Vector::operator = (const Vector &v)
{
// if the vectors have different sizes,
// then first resize the present one
if (size() != v.size())
reinit (v.communicator, v.size(), v.local_size(), true);
const int ierr = VecCopy (v.vector, vector);
AssertThrow (ierr == 0, ExcPETScError(ierr));
return *this;
}
template <typename number>
inline
Vector &
Vector::operator = (const dealii::Vector<number> &v)
{
Assert (size() == v.size(),
ExcDimensionMismatch (size(), v.size()));
// the following isn't necessarily fast,
// but this is due to the fact that PETSc
// doesn't offer an inlined access
// operator.
//
// if someone wants to contribute some
// code: to make this code faster, one
// could either first convert all values
// to PetscScalar, and then set them all
// at once using VecSetValues. This has
// the drawback that it could take quite
// some memory, if the vector is large,
// and it would in addition allocate
// memory on the heap, which is
// expensive. an alternative would be to
// split the vector into chunks of, say,
// 128 elements, convert a chunk at a
// time and set it in the output vector
// using VecSetValues. since 128 elements
// is small enough, this could easily be
// allocated on the stack (as a local
// variable) which would make the whole
// thing much more efficient.
//
// a second way to make things faster is
// for the special case that
// number==PetscScalar. we could then
// declare a specialization of this
// template, and omit the conversion. the
// problem with this is that the best we
// can do is to use VecSetValues, but
// this isn't very efficient either: it
// wants to see an array of indices,
// which in this case a) again takes up a
// whole lot of memory on the heap, and
// b) is totally dumb since its content
// would simply be the sequence
// 0,1,2,3,...,n. the best of all worlds
// would probably be a function in Petsc
// that would take a pointer to an array
// of PetscScalar values and simply copy
// n elements verbatim into the vector...
for (unsigned int i=0; i<v.size(); ++i)
(*this)(i) = v(i);
compress ();
return *this;
}
inline
const MPI_Comm &
Vector::get_mpi_communicator () const
{
return communicator;
}
#endif // DOXYGEN
}
}
/**@}*/
DEAL_II_NAMESPACE_CLOSE
#endif // DEAL_II_USE_PETSC
/*---------------------------- petsc_parallel_vector.h ---------------------------*/
#endif
/*---------------------------- petsc_parallel_vector.h ---------------------------*/
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