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rAKA/src/solver/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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