sparse_matrix_petsc.cc
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sparse_matrix_petsc.cc
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	/**
	* @file petsc_matrix.cc
	* @author Aurelia Cuba Ramos <aurelia.cubaramos@epfl.ch>
	* @date Mon Jul 21 17:40:41 2014
	*
	* @brief Implementation of PETSc matrix class
	*
	* @section LICENSE
	*
	* Copyright (©) 2010-2011 EPFL (Ecole Polytechnique Fédérale de Lausanne)
	* Laboratory (LSMS - Laboratoire de Simulation en Mécanique des Solides)
	*
	* Akantu is free software: you can redistribute it and/or modify it under the
	* terms of the GNU Lesser General Public License as published by the Free
	* Software Foundation, either version 3 of the License, or (at your option) any
	* later version.
	*
	* Akantu is distributed in the hope that it will be useful, but WITHOUT ANY
	* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
	* A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more
	* details.
	*
	* You should have received a copy of the GNU Lesser General Public License
	* along with Akantu. If not, see <http://www.gnu.org/licenses/>.
	*
	*/

	/* -------------------------------------------------------------------------- */
	#include "petsc_matrix.hh"
	#include "static_communicator.hh"
	#include "static_communicator_mpi.hh"
	#include "mpi_type_wrapper.hh"
	#include "dof_synchronizer.hh"
	#include "petsc_wrapper.hh"
	/* -------------------------------------------------------------------------- */
	#include <cstring>
	#include <petscsys.h>
	/* -------------------------------------------------------------------------- */

	__BEGIN_AKANTU__

	#if not defined(PETSC_CLANGUAGE_CXX)
	int aka_PETScError(int ierr) {
	CHKERRQ(ierr);
	return 0;
	}
	#endif

	/* -------------------------------------------------------------------------- */
	SparseMatrixPETSc::SparseMatrixPETSc(
	UInt size, const SparseMatrixType & sparse_matrix_type, const ID & id,
	const MemoryID & memory_id)
	: SparseMatrix(size, sparse_matrix_type, id, memory_id),
	petsc_matrix_wrapper(new PETScMatrixWrapper), d_nnz(0, 1, "dnnz"),
	o_nnz(0, 1, "onnz"), first_global_index(0),
	is_petsc_matrix_initialized(false) {
	AKANTU_DEBUG_IN();
	StaticSolver::getStaticSolver().registerEventHandler(*this);
	this->offset = 0;
	this->init();

	AKANTU_DEBUG_OUT();
	}

	/* -------------------------------------------------------------------------- */
	SparseMatrixPETSc::SparseMatrixPETSc(const SparseMatrix & matrix, const ID & id,
	const MemoryID & memory_id)
	: SparseMatrix(matrix, id, memory_id),
	petsc_matrix_wrapper(new PETScMatrixWrapper), d_nnz(0, 1, "dnnz"),
	o_nnz(0, 1, "onnz"), first_global_index(0),
	is_petsc_matrix_initialized(false) {
	AKANTU_DEBUG_TO_IMPLEMENT();
	}

	/* -------------------------------------------------------------------------- */
	SparseMatrixPETSc::~SparseMatrixPETSc() {
	AKANTU_DEBUG_IN();

	/// destroy all the PETSc data structures used for this matrix
	this->destroyInternalData();
	StaticSolver::getStaticSolver().unregisterEventHandler(*this);

	AKANTU_DEBUG_OUT();
	}

	/* -------------------------------------------------------------------------- */
	void SparseMatrixPETSc::init() {
	AKANTU_DEBUG_IN();

	// set the communicator that should be used by PETSc
	#if defined(AKANTU_USE_MPI)
	StaticCommunicator & comm = StaticCommunicator::getStaticCommunicator();
	const StaticCommunicatorMPI & mpi_st_comm =
	dynamic_cast<const StaticCommunicatorMPI &>(
	comm.getRealStaticCommunicator());
	this->petsc_matrix_wrapper->communicator =
	mpi_st_comm.getMPITypeWrapper().getMPICommunicator();
	#else
	this->petsc_matrix_wrapper->communicator = PETSC_COMM_SELF;
	#endif

	PetscErrorCode ierr;

	// create the PETSc matrix object
	ierr = MatCreate(this->petsc_matrix_wrapper->communicator,
	&(this->petsc_matrix_wrapper->mat));
	CHKERRXX(ierr);

	/**
	* Set the matrix type
	* @todo PETSc does currently not support a straightforward way to
	* apply Dirichlet boundary conditions for MPISBAIJ
	* matrices. Therefore always the entire matrix is allocated. It
	* would be possible to use MATSBAIJ for sequential matrices in case
	* memory becomes critical. Also, block matrices would give a much
	* better performance. Modify this in the future!
	*/
	ierr = MatSetType(this->petsc_matrix_wrapper->mat, MATAIJ);
	CHKERRXX(ierr);

	this->is_petsc_matrix_initialized = true;

	AKANTU_DEBUG_OUT();
	}

	/* -------------------------------------------------------------------------- */
	/**
	* With this method each processor computes the dimensions of the
	* local matrix, i.e. the part of the global matrix it is storing.
	* @param dof_synchronizer dof synchronizer that maps the local
	* dofs to the global dofs and the equation numbers, i.e., the
	* position at which the dof is assembled in the matrix
	*/
	void SparseMatrixPETSc::setSize() {
	AKANTU_DEBUG_IN();

	PetscErrorCode ierr;

	/// find the number of dofs corresponding to master or local nodes
	UInt nb_dofs = this->dof_synchronizer->getNbDOFs();
	UInt nb_local_master_dofs = 0;

	/// create array to store the global equation number of all local and master
	/// dofs
	Array<Int> local_master_eq_nbs(nb_dofs);
	Array<Int>::scalar_iterator it_eq_nb = local_master_eq_nbs.begin();

	/// get the pointer to the global equation number array
	Int * eq_nb_val =
	this->dof_synchronizer->getGlobalDOFEquationNumbers().storage();

	for (UInt i = 0; i < nb_dofs; ++i) {
	if (this->dof_synchronizer->isLocalOrMasterDOF(i)) {
	*it_eq_nb = eq_nb_val[i];
	++it_eq_nb;
	++nb_local_master_dofs;
	}
	}

	local_master_eq_nbs.resize(nb_local_master_dofs);

	/// set the local size
	this->local_size = nb_local_master_dofs;

	/// resize PETSc matrix
	#if defined(AKANTU_USE_MPI)
	ierr = MatSetSizes(this->petsc_matrix_wrapper->mat, this->local_size,
	this->local_size, this->size, this->size);
	CHKERRXX(ierr);
	#else
	ierr = MatSetSizes(this->petsc_matrix_wrapper->mat, this->local_size,
	this->local_size);
	CHKERRXX(ierr);
	#endif

	/// create mapping from akantu global numbering to petsc global numbering
	this->createGlobalAkantuToPETScMap(local_master_eq_nbs.storage());

	AKANTU_DEBUG_OUT();
	}

	/* -------------------------------------------------------------------------- */
	/**
	* This method generates a mapping from the global Akantu equation
	* numbering to the global PETSc dof ordering
	* @param local_master_eq_nbs_ptr Int pointer to the array of equation
	* numbers of all local or master dofs, i.e. the row indices of the
	* local matrix
	*/
	void
	SparseMatrixPETSc::createGlobalAkantuToPETScMap(Int * local_master_eq_nbs_ptr) {
	AKANTU_DEBUG_IN();

	PetscErrorCode ierr;

	StaticCommunicator & comm = StaticCommunicator::getStaticCommunicator();
	UInt rank = comm.whoAmI();

	// initialize vector to store the number of local and master nodes that are
	// assigned to each processor
	Vector<UInt> master_local_ndofs_per_proc(nb_proc);

	/// store the nb of master and local dofs on each processor
	master_local_ndofs_per_proc(rank) = this->local_size;

	/// exchange the information among all processors
	comm.allGather(master_local_ndofs_per_proc.storage(), 1);

	/// each processor creates a map for his akantu global dofs to the
	/// corresponding petsc global dofs

	/// determine the PETSc-index for the first dof on each processor

	for (UInt i = 0; i < rank; ++i) {
	this->first_global_index += master_local_ndofs_per_proc(i);
	}

	/// create array for petsc ordering
	Array<Int> petsc_dofs(this->local_size);
	Array<Int>::scalar_iterator it_petsc_dofs = petsc_dofs.begin();

	for (Int i = this->first_global_index;
	i < this->first_global_index + this->local_size; ++i, ++it_petsc_dofs) {
	*it_petsc_dofs = i;
	}

	ierr = AOCreateBasic(this->petsc_matrix_wrapper->communicator,
	this->local_size, local_master_eq_nbs_ptr,
	petsc_dofs.storage(), &(this->petsc_matrix_wrapper->ao));
	CHKERRXX(ierr);

	AKANTU_DEBUG_OUT();
	}

	/* -------------------------------------------------------------------------- */
	// void SparseMatrixPETSc::createLocalAkantuToPETScMap(const DOFSynchronizer &
	// dof_synchronizer) {
	// AKANTU_DEBUG_IN();

	// AKANTU_DEBUG_ASSERT(this->petsc_matrix_wrapper->ao != NULL,
	// "You should first create a mapping from the global"
	// << " Akantu numbering to the global PETSc numbering");

	// PetscErrorCode ierr;

	// this->dof_synchronizer = &const_cast<DOFSynchronizer &>(dof_synchronizer);

	// /// get the number of dofs
	// Int nb_dofs = dof_synchronizer.getNbDOFs();

	// /// get the global equation numbers for each node
	// Array<Int> global_dof_equation_numbers =
	// dof_synchronizer.getGlobalDOFEquationNumbers();

	// /// map the global dof equation numbers to the corresponding PETSc ordering
	// ierr = AOApplicationToPETSc(this->petsc_matrix_wrapper->ao, nb_dofs,
	// global_dof_equation_numbers.storage()); CHKERRXX(ierr);

	// /// create the mapping from the local Akantu ordering to the global PETSc
	// ordering
	// ierr =
	// ISLocalToGlobalMappingCreate(this->petsc_matrix_wrapper->communicator,
	// 1, nb_dofs,
	// global_dof_equation_numbers.storage(),
	// PETSC_COPY_VALUES,
	// &(this->petsc_matrix_wrapper-mapping));
	// CHKERRXX(ierr);

	// AKANTU_DEBUG_OUT();
	// }

	/* -------------------------------------------------------------------------- */
	/**
	* This function creates the non-zero pattern of the PETSc matrix. In
	* PETSc the parallel matrix is partitioned across processors such
	* that the first m0 rows belong to process 0, the next m1 rows belong
	* to process 1, the next m2 rows belong to process 2 etc.. where
	* m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
	* values corresponding to [m x N] submatrix
	* (http://www.mcs.anl.gov/petsc/).
	* @param mesh mesh discretizing the domain we want to analyze
	* @param dof_synchronizer dof synchronizer that maps the local
	* dofs to the global dofs and the equation numbers, i.e., the
	* position at which the dof is assembled in the matrix
	*/

	void SparseMatrixPETSc::buildProfile(const Mesh & mesh,
	const DOFSynchronizer & dof_synchronizer,
	UInt nb_degree_of_freedom) {
	AKANTU_DEBUG_IN();

	// clearProfile();
	this->dof_synchronizer = &const_cast<DOFSynchronizer &>(dof_synchronizer);
	this->setSize();
	PetscErrorCode ierr;

	/// resize arrays to store the number of nonzeros in each row
	this->d_nnz.resize(this->local_size);
	this->o_nnz.resize(this->local_size);

	/// set arrays to zero everywhere
	this->d_nnz.set(0);
	this->o_nnz.set(0);

	// if(irn_jcn_to_k) delete irn_jcn_to_k;
	// irn_jcn_to_k = new std::map<std::pair<UInt, UInt>, UInt>;

	coordinate_list_map::iterator irn_jcn_k_it;

	Int * eq_nb_val = dof_synchronizer.getGlobalDOFEquationNumbers().storage();
	UInt nb_global_dofs = dof_synchronizer.getNbGlobalDOFs();
	Array<Int> index_pair(2);

	/// Loop over all the ghost types
	for (ghost_type_t::iterator gt = ghost_type_t::begin();
	gt != ghost_type_t::end(); ++gt) {
	const GhostType & ghost_type = *gt;
	Mesh::type_iterator it =
	mesh.firstType(mesh.getSpatialDimension(), ghost_type, _ek_not_defined);
	Mesh::type_iterator end =
	mesh.lastType(mesh.getSpatialDimension(), ghost_type, _ek_not_defined);
	for (; it != end; ++it) {
	UInt nb_element = mesh.getNbElement(*it, ghost_type);
	UInt nb_nodes_per_element = Mesh::getNbNodesPerElement(*it);
	UInt size_mat = nb_nodes_per_element * nb_degree_of_freedom;

	UInt * conn_val = mesh.getConnectivity(*it, ghost_type).storage();
	Int * local_eq_nb_val =
	new Int[nb_degree_of_freedom * nb_nodes_per_element];

	for (UInt e = 0; e < nb_element; ++e) {
	Int * tmp_local_eq_nb_val = local_eq_nb_val;
	for (UInt i = 0; i < nb_nodes_per_element; ++i) {
	UInt n = conn_val[i];
	for (UInt d = 0; d < nb_degree_of_freedom; ++d) {
	/**
	* !!!!!!Careful!!!!!! This is a ugly fix. @todo this is a
	* very ugly fix, because the offset for the global
	* equation number, where the dof will be assembled, is
	* hardcoded. In the future a class dof manager has to be
	* added to Akantu to handle the mapping between the dofs
	* and the equation numbers
	*
	*/

	*tmp_local_eq_nb_val++ =
	eq_nb_val[n * nb_degree_of_freedom + d] -
	(dof_synchronizer.isPureGhostDOF(n * nb_degree_of_freedom + d)
	? nb_global_dofs
	: 0);
	}
	}

	for (UInt i = 0; i < size_mat; ++i) {
	Int c_irn = local_eq_nb_val[i];
	UInt j_start = 0;
	for (UInt j = j_start; j < size_mat; ++j) {
	Int c_jcn = local_eq_nb_val[j];
	index_pair(0) = c_irn;
	index_pair(1) = c_jcn;
	AOApplicationToPetsc(this->petsc_matrix_wrapper->ao, 2,
	index_pair.storage());
	if (index_pair(0) >= first_global_index &&
	index_pair(0) < first_global_index + this->local_size) {
	KeyCOO irn_jcn = keyPETSc(c_irn, c_jcn);
	irn_jcn_k_it = irn_jcn_k.find(irn_jcn);

	if (irn_jcn_k_it == irn_jcn_k.end()) {
	irn_jcn_k[irn_jcn] = nb_non_zero;

	// check if node is slave node
	if (index_pair(1) >= first_global_index &&
	index_pair(1) < first_global_index + this->local_size)
	this->d_nnz(index_pair(0) - first_global_index) += 1;
	else
	this->o_nnz(index_pair(0) - first_global_index) += 1;
	nb_non_zero++;
	}
	}
	}
	}
	conn_val += nb_nodes_per_element;
	}

	delete[] local_eq_nb_val;
	}
	}

	// /// for pbc @todo correct it for parallel
	// if(StaticCommunicator::getStaticCommunicator().getNbProc() == 1) {
	// for (UInt i = 0; i < size; ++i) {
	// KeyCOO irn_jcn = key(i, i);
	// irn_jcn_k_it = irn_jcn_k.find(irn_jcn);
	// if(irn_jcn_k_it == irn_jcn_k.end()) {
	// irn_jcn_k[irn_jcn] = nb_non_zero;
	// irn.push_back(i + 1);
	// jcn.push_back(i + 1);
	// nb_non_zero++;
	// }
	// }
	// }

	// std::string mat_type;
	// mat_type.resize(20, 'a');
	// std::cout << "MatType: " << mat_type << std::endl;
	// const char * mat_type_ptr = mat_type.c_str();
	MatType type;
	MatGetType(this->petsc_matrix_wrapper->mat, &type);
	/// std::cout << "the matrix type is: " << type << std::endl;
	/**
	* PETSc will use only one of the following preallocation commands
	* depending on the matrix type and ignore the rest. Note that for
	* the block matrix format a block size of 1 is used. This might
	* result in bad performance. @todo For better results implement
	* buildProfile() with larger block size.
	*
	*/
	/// build profile:
	if (strcmp(type, MATSEQAIJ) == 0) {
	ierr = MatSeqAIJSetPreallocation(this->petsc_matrix_wrapper->mat, 0,
	d_nnz.storage());
	CHKERRXX(ierr);
	} else if ((strcmp(type, MATMPIAIJ) == 0)) {
	ierr = MatMPIAIJSetPreallocation(this->petsc_matrix_wrapper->mat, 0,
	d_nnz.storage(), 0, o_nnz.storage());
	CHKERRXX(ierr);
	} else {
	AKANTU_DEBUG_ERROR("The type " << type
	<< " of PETSc matrix is not handled by"
	<< " akantu in the preallocation step");
	}

	// ierr = MatSeqSBAIJSetPreallocation(this->petsc_matrix_wrapper->mat, 1,
	// 0, d_nnz.storage()); CHKERRXX(ierr);

	if (this->sparse_matrix_type == _symmetric) {
	/// set flag for symmetry to enable ICC/Cholesky preconditioner
	ierr = MatSetOption(this->petsc_matrix_wrapper->mat, MAT_SYMMETRIC,
	PETSC_TRUE);
	CHKERRXX(ierr);
	/// set flag for symmetric positive definite
	ierr = MatSetOption(this->petsc_matrix_wrapper->mat, MAT_SPD, PETSC_TRUE);
	CHKERRXX(ierr);
	}
	/// once the profile has been build ignore any new nonzero locations
	ierr = MatSetOption(this->petsc_matrix_wrapper->mat,
	MAT_NEW_NONZERO_LOCATIONS, PETSC_TRUE);
	CHKERRXX(ierr);

	AKANTU_DEBUG_OUT();
	}

	/* -------------------------------------------------------------------------- */
	/**
	* Method to save the nonzero pattern and the values stored at each position
	* @param filename name of the file in which the information will be stored
	*/
	void SparseMatrixPETSc::saveMatrix(const std::string & filename) const {
	AKANTU_DEBUG_IN();

	PetscErrorCode ierr;

	/// create Petsc viewer
	PetscViewer viewer;
	ierr = PetscViewerASCIIOpen(this->petsc_matrix_wrapper->communicator,
	filename.c_str(), &viewer);
	CHKERRXX(ierr);

	/// set the format
	PetscViewerSetFormat(viewer, PETSC_VIEWER_DEFAULT);
	CHKERRXX(ierr);
	/// save the matrix
	/// @todo Write should be done in serial -> might cause problems
	ierr = MatView(this->petsc_matrix_wrapper->mat, viewer);
	CHKERRXX(ierr);

	/// destroy the viewer
	ierr = PetscViewerDestroy(&viewer);
	CHKERRXX(ierr);

	AKANTU_DEBUG_OUT();
	}

	/* -------------------------------------------------------------------------- */
	/**
	* Method to add an Akantu sparse matrix to the PETSc matrix
	* @param matrix Akantu sparse matrix to be added
	* @param alpha the factor specifying how many times the matrix should be added
	*/
	void SparseMatrixPETSc::add(const SparseMatrix & matrix, Real alpha) {
	PetscErrorCode ierr;
	// AKANTU_DEBUG_ASSERT(nb_non_zero == matrix.getNbNonZero(),
	// "The two matrix don't have the same profiles");

	Real val_to_add = 0;
	Array<Int> index(2);
	for (UInt n = 0; n < matrix.getNbNonZero(); ++n) {
	UInt mat_to_add_offset = matrix.getOffset();
	index(0) = matrix.getIRN()(n) - mat_to_add_offset;
	index(1) = matrix.getJCN()(n) - mat_to_add_offset;
	AOApplicationToPetsc(this->petsc_matrix_wrapper->ao, 2, index.storage());
	if (this->sparse_matrix_type == _symmetric && index(0) > index(1))
	std::swap(index(0), index(1));

	val_to_add = matrix.getA()(n) * alpha;
	/// MatSetValue might be very slow for MATBAIJ, might need to use
	/// MatSetValuesBlocked
	ierr = MatSetValue(this->petsc_matrix_wrapper->mat, index(0), index(1),
	val_to_add, ADD_VALUES);
	CHKERRXX(ierr);
	/// chek if sparse matrix to be added is symmetric. In this case
	/// the value also needs to be added at the transposed location in
	/// the matrix because PETSc is using the full profile, also for symmetric
	/// matrices
	if (matrix.getSparseMatrixType() == _symmetric && index(0) != index(1))
	ierr = MatSetValue(this->petsc_matrix_wrapper->mat, index(1), index(0),
	val_to_add, ADD_VALUES);
	CHKERRXX(ierr);
	}

	this->performAssembly();
	}

	/* -------------------------------------------------------------------------- */
	/**
	* Method to add another PETSc matrix to this PETSc matrix
	* @param matrix PETSc matrix to be added
	* @param alpha the factor specifying how many times the matrix should be added
	*/
	void SparseMatrixPETSc::add(const SparseMatrixPETSc & matrix, Real alpha) {
	PetscErrorCode ierr;

	ierr = MatAXPY(this->petsc_matrix_wrapper->mat, alpha,
	matrix.petsc_matrix_wrapper->mat, SAME_NONZERO_PATTERN);
	CHKERRXX(ierr);

	this->performAssembly();
	}

	/* -------------------------------------------------------------------------- */
	/**
	* MatSetValues() generally caches the values. The matrix is ready to
	* use only after MatAssemblyBegin() and MatAssemblyEnd() have been
	* called. (http://www.mcs.anl.gov/petsc/)
	*/
	void SparseMatrixPETSc::performAssembly() {
	PetscErrorCode ierr;
	ierr = MatAssemblyBegin(this->petsc_matrix_wrapper->mat, MAT_FINAL_ASSEMBLY);
	CHKERRXX(ierr);
	ierr = MatAssemblyEnd(this->petsc_matrix_wrapper->mat, MAT_FINAL_ASSEMBLY);
	CHKERRXX(ierr);
	}

	/* -------------------------------------------------------------------------- */
	/**
	* Method is called when the static solver is destroyed, just before
	* PETSc is finalized. So all PETSc objects need to be destroyed at
	* this point.
	*/
	void SparseMatrixPETSc::beforeStaticSolverDestroy() {
	AKANTU_DEBUG_IN();

	try {
	this->destroyInternalData();
	} catch (...) {}

	AKANTU_DEBUG_OUT();
	}

	/* -------------------------------------------------------------------------- */
	/// destroy all the PETSc data structures used for this matrix
	void SparseMatrixPETSc::destroyInternalData() {
	AKANTU_DEBUG_IN();

	if (this->is_petsc_matrix_initialized) {

	PetscErrorCode ierr;

	ierr = MatDestroy(&(this->petsc_matrix_wrapper->mat));
	CHKERRXX(ierr);
	delete petsc_matrix_wrapper;

	this->is_petsc_matrix_initialized = false;
	}

	AKANTU_DEBUG_OUT();
	}

	/* -------------------------------------------------------------------------- */
	/// access K(i, j). Works only for dofs on this processor!!!!
	Real SparseMatrixPETSc::operator()(UInt i, UInt j) const {
	AKANTU_DEBUG_IN();

	AKANTU_DEBUG_ASSERT(this->dof_synchronizer->isLocalOrMasterDOF(i) &&
	this->dof_synchronizer->isLocalOrMasterDOF(j),
	"Operator works only for dofs on this processor");

	Array<Int> index(2, 1);
	index(0) = this->dof_synchronizer->getDOFGlobalID(i);
	index(1) = this->dof_synchronizer->getDOFGlobalID(j);
	AOApplicationToPetsc(this->petsc_matrix_wrapper->ao, 2, index.storage());

	Real value = 0;

	PetscErrorCode ierr;
	/// @todo MatGetValue might be very slow for MATBAIJ, might need to use
	/// MatGetValuesBlocked
	ierr = MatGetValues(this->petsc_matrix_wrapper->mat, 1, &index(0), 1,
	&index(1), &value);
	CHKERRXX(ierr);

	AKANTU_DEBUG_OUT();

	return value;
	}

	/* -------------------------------------------------------------------------- */
	/**
	* Apply Dirichlet boundary conditions by zeroing the rows and columns which
	* correspond to blocked dofs
	* @param boundary array of booleans which are true if the dof at this position
	* is blocked
	* @param block_val the value in the diagonal entry of blocked rows
	*/
	void SparseMatrixPETSc::applyBoundary(const Array<bool> & boundary,
	Real block_val) {
	AKANTU_DEBUG_IN();

	PetscErrorCode ierr;

	/// get the global equation numbers to find the rows that need to be zeroed
	/// for the blocked dofs
	Int * eq_nb_val = dof_synchronizer->getGlobalDOFEquationNumbers().storage();

	/// every processor calls the MatSetZero() only for his local or master dofs.
	/// This assures that not two processors or more try to zero the same row
	UInt nb_component = boundary.getNbComponent();
	UInt size = boundary.getSize();
	Int nb_blocked_local_master_eq_nb = 0;
	Array<Int> blocked_local_master_eq_nb(this->local_size);
	Int * blocked_lm_eq_nb_ptr = blocked_local_master_eq_nb.storage();

	for (UInt i = 0; i < size; ++i) {
	for (UInt j = 0; j < nb_component; ++j) {
	UInt local_dof = i * nb_component + j;
	if (boundary(i, j) == true &&
	this->dof_synchronizer->isLocalOrMasterDOF(local_dof)) {
	Int global_eq_nb = *eq_nb_val;
	*blocked_lm_eq_nb_ptr = global_eq_nb;
	++nb_blocked_local_master_eq_nb;
	++blocked_lm_eq_nb_ptr;
	}
	++eq_nb_val;
	}
	}
	blocked_local_master_eq_nb.resize(nb_blocked_local_master_eq_nb);

	ierr = AOApplicationToPetsc(this->petsc_matrix_wrapper->ao,
	nb_blocked_local_master_eq_nb,
	blocked_local_master_eq_nb.storage());
	CHKERRXX(ierr);
	ierr = MatZeroRowsColumns(
	this->petsc_matrix_wrapper->mat, nb_blocked_local_master_eq_nb,
	blocked_local_master_eq_nb.storage(), block_val, 0, 0);
	CHKERRXX(ierr);

	this->performAssembly();
	AKANTU_DEBUG_OUT();
	}

	/* -------------------------------------------------------------------------- */
	/// set all entries to zero while keeping the same nonzero pattern
	void SparseMatrixPETSc::clear() {
	MatZeroEntries(this->petsc_matrix_wrapper->mat);
	}

	__END_AKANTU__

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