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rAKA/src/solver/sparse_matrix_petsc.cc
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sparse_matrix_petsc.cc
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/**
* @file sparse_matrix_petsc.cc
*
* @author Aurelia Isabel Cuba Ramos <aurelia.cubaramos@epfl.ch>
*
* @date creation: Mon Dec 13 2010
* @date last modification: Sat Feb 03 2018
*
* @brief Implementation of PETSc matrix class
*
* @section LICENSE
*
* Copyright (©) 2010-2018 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 "sparse_matrix_petsc.hh"
#include "dof_manager_petsc.hh"
#include "mpi_type_wrapper.hh"
#include "static_communicator.hh"
/* -------------------------------------------------------------------------- */
#include <cstring>
#include <petscsys.h>
/* -------------------------------------------------------------------------- */
namespace akantu {
#if not defined(PETSC_CLANGUAGE_CXX)
int aka_PETScError(int ierr) {
CHKERRQ(ierr);
return 0;
}
#endif
/* -------------------------------------------------------------------------- */
SparseMatrixPETSc::SparseMatrixPETSc(DOFManagerPETSc & dof_manager,
const MatrixType & sparse_matrix_type,
const ID & id, const MemoryID & memory_id)
: SparseMatrix(dof_manager, matrix_type, id, memory_id),
dof_manager(dof_manager), d_nnz(0, 1, "dnnz"), o_nnz(0, 1, "onnz"),
first_global_index(0) {
AKANTU_DEBUG_IN();
PetscErrorCode ierr;
// create the PETSc matrix object
ierr = MatCreate(PETSC_COMM_WORLD, &this->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->mat, MATAIJ);
CHKERRXX(ierr);
AKANTU_DEBUG_OUT();
}
/* -------------------------------------------------------------------------- */
SparseMatrixPETSc::~SparseMatrixPETSc() {
AKANTU_DEBUG_IN();
/// destroy all the PETSc data structures used for this matrix
PetscErrorCode ierr;
ierr = MatDestroy(&this->mat);
CHKERRXX(ierr);
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_manager.getLocalSystemSize();
// 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();
throw;
/// 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(PETSC_COMM_WORLD, this->local_size, local_master_eq_nbs_ptr,
petsc_dofs.storage(), &(this->ao));
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(PETSC_COMM_WORLD, 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->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->mat, alpha, matrix.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() {
this->beginAssembly();
this->endAssembly();
}
/* -------------------------------------------------------------------------- */
void SparseMatrixPETSc::beginAssembly() {
PetscErrorCode ierr;
ierr = MatAssemblyBegin(this->mat, MAT_FINAL_ASSEMBLY);
CHKERRXX(ierr);
ierr = MatAssemblyEnd(this->mat, MAT_FINAL_ASSEMBLY);
CHKERRXX(ierr);
}
/* -------------------------------------------------------------------------- */
void SparseMatrixPETSc::endAssembly() {
PetscErrorCode ierr;
ierr = MatAssemblyEnd(this->mat, MAT_FINAL_ASSEMBLY);
CHKERRXX(ierr);
}
/* -------------------------------------------------------------------------- */
/// 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;
return 0.;
}
/* -------------------------------------------------------------------------- */
/**
* 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.size();
// 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->mat); }
} // akantu
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