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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
			*
			*
			* 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_communicator_data.hh"
			#include "solver_vector_petsc.hh"
			/* -------------------------------------------------------------------------- */

			namespace akantu {

			/* -------------------------------------------------------------------------- */
			SparseMatrixPETSc::SparseMatrixPETSc(DOFManagerPETSc & dof_manager,
			const MatrixType & matrix_type,
			const ID & id)
			: SparseMatrix(dof_manager, matrix_type, id), dof_manager(dof_manager) {
			AKANTU_DEBUG_IN();

			auto && mpi_comm = dof_manager.getMPIComm();

			PETSc_call(MatCreate, mpi_comm, &mat);
			detail::PETScSetName(mat, id);

			resize();

			PETSc_call(MatSetFromOptions, mat);

			PETSc_call(MatSetUp, mat);

			PETSc_call(MatSetOption, mat, MAT_ROW_ORIENTED, PETSC_TRUE);
			PETSc_call(MatSetOption, mat, MAT_NEW_NONZERO_LOCATIONS, PETSC_TRUE);

			if (matrix_type == _symmetric) {
			PETSc_call(MatSetOption, mat, MAT_SYMMETRIC, PETSC_TRUE);
			}

			AKANTU_DEBUG_OUT();
			}

			/* -------------------------------------------------------------------------- */
			SparseMatrixPETSc::SparseMatrixPETSc(const SparseMatrixPETSc & matrix,
			const ID & id)
			: SparseMatrix(matrix, id), dof_manager(matrix.dof_manager) {
			PETSc_call(MatDuplicate, matrix.mat, MAT_COPY_VALUES, &mat);
			detail::PETScSetName(mat, id);
			}

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

			if (mat != nullptr) {
			PETSc_call(MatDestroy, &mat);
			}

			AKANTU_DEBUG_OUT();
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::resize() {
			auto local_size = dof_manager.getPureLocalSystemSize();
			PETSc_call(MatSetSizes, mat, local_size, local_size, size_, size_);

			auto & is_ltog_mapping = dof_manager.getISLocalToGlobalMapping();
			PETSc_call(MatSetLocalToGlobalMapping, mat, is_ltog_mapping, is_ltog_mapping);
			}

			/* -------------------------------------------------------------------------- */
			/**
			* 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();

			auto && mpi_comm = dof_manager.getMPIComm();

			/// create Petsc viewer
			PetscViewer viewer;
			PETSc_call(PetscViewerASCIIOpen, mpi_comm, filename.c_str(), &viewer);
			PETSc_call(PetscViewerPushFormat, viewer, PETSC_VIEWER_ASCII_MATRIXMARKET);
			PETSc_call(MatView, mat, viewer);
			PETSc_call(PetscViewerPopFormat, viewer);
			PETSc_call(PetscViewerDestroy, &viewer);

			AKANTU_DEBUG_OUT();
			}

			/* -------------------------------------------------------------------------- */
			/// Equivalent of *gemv in blas
			void SparseMatrixPETSc::matVecMul(const SolverVector & _x, SolverVector & _y,
			Real alpha, Real beta) const {
			const auto & x = aka::as_type<SolverVectorPETSc>(_x);
			auto & y = aka::as_type<SolverVectorPETSc>(_y);

			// y = alpha A x + beta y
			SolverVectorPETSc w(x, this->id + ":tmp");

			// w = A x
			if (release == 0) {
			PETSc_call(VecZeroEntries, w);
			} else {
			PETSc_call(MatMult, mat, x, w);
			}

			if (alpha != 1.) {
			// w = alpha w
			PETSc_call(VecScale, w, alpha);
			}

			// y = w + beta y
			PETSc_call(VecAYPX, y, beta, w);
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::addMeToImpl(SparseMatrixPETSc & B, Real alpha) const {
			PETSc_call(MatAXPY, B.mat, alpha, mat, SAME_NONZERO_PATTERN);

			B.release++;
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::addMeTo(SparseMatrix & B, Real alpha) const {
			if (aka::is_of_type<SparseMatrixPETSc>(B)) {
			auto & B_petsc = aka::as_type<SparseMatrixPETSc>(B);
			this->addMeToImpl(B_petsc, alpha);
			} else {
			AKANTU_TO_IMPLEMENT();
			// this->addMeToTemplated<SparseMatrix>(*this, alpha);
			}
			}

			/* -------------------------------------------------------------------------- */
			/**
			* 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::applyModifications() {
			this->beginAssembly();
			this->endAssembly();
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::beginAssembly() {
			PETSc_call(MatAssemblyBegin, mat, MAT_FINAL_ASSEMBLY);
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::endAssembly() {
			PETSc_call(MatAssemblyEnd, mat, MAT_FINAL_ASSEMBLY);
			PETSc_call(MatSetOption, mat, MAT_NEW_NONZERO_LOCATIONS, PETSC_FALSE);

			this->release++;
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::copyProfile(const SparseMatrix & other) {
			const auto & A = aka::as_type<SparseMatrixPETSc>(other);

			MatDestroy(&mat);
			MatDuplicate(A.mat, MAT_DO_NOT_COPY_VALUES, &mat);
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::applyBoundary(Real block_val) {
			AKANTU_DEBUG_IN();

			const auto & blocked_dofs = this->dof_manager.getGlobalBlockedDOFs();
			// std::vector<PetscInt> rows;
			// for (auto && data : enumerate(blocked)) {
			// if (std::get<1>(data)) {
			// rows.push_back(std::get<0>(data));
			// }
			// }
			// applyModifications();

			static int c = 0;

			saveMatrix("before_blocked_" + std::to_string(c) + ".mtx");

			PETSc_call(MatZeroRowsColumnsLocal, mat, blocked_dofs.size(),
			blocked_dofs.storage(), block_val, nullptr, nullptr);

			saveMatrix("after_blocked_" + std::to_string(c) + ".mtx");
			++c;

			AKANTU_DEBUG_OUT();
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::mul(Real alpha) {
			PETSc_call(MatScale, mat, alpha);
			this->release++;
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::zero() {
			PETSc_call(MatZeroEntries, mat);
			this->release++;
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::clearProfile() {
			SparseMatrix::clearProfile();
			PETSc_call(MatResetPreallocation, mat);
			PETSc_call(MatSetOption, mat, MAT_NEW_NONZERO_LOCATIONS, PETSC_TRUE);
			// PETSc_call(MatSetOption, MAT_KEEP_NONZERO_PATTERN, PETSC_TRUE);
			// PETSc_call(MatSetOption, MAT_NEW_NONZERO_ALLOCATIONS, PETSC_TRUE);
			// PETSc_call(MatSetOption, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_TRUE);

			this->zero();
			}

			/* -------------------------------------------------------------------------- */
			UInt SparseMatrixPETSc::add(UInt i, UInt j) {
			PETSc_call(MatSetValue, mat, i, j, 0, ADD_VALUES);
			return 0;
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::add(UInt i, UInt j, Real val) {
			PETSc_call(MatSetValue, mat, i, j, val, ADD_VALUES);
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::addLocal(UInt i, UInt j) {
			PETSc_call(MatSetValueLocal, mat, i, j, 0, ADD_VALUES);
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::addLocal(UInt i, UInt j, Real val) {
			PETSc_call(MatSetValueLocal, mat, i, j, val, ADD_VALUES);
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::addLocal(const Vector<Int> & rows,
			const Vector<Int> & cols,
			const Matrix<Real> & values) {
			PETSc_call(MatSetValuesLocal, mat, rows.size(), rows.storage(), cols.size(),
			cols.storage(), values.storage(), ADD_VALUES);
			}

			/* -------------------------------------------------------------------------- */
			void SparseMatrixPETSc::addValues(const Vector<Int> & rows,
			const Vector<Int> & cols,
			const Matrix<Real> & values, MatrixType values_type) {
			if (values_type == _unsymmetric and matrix_type == _symmetric) {
			PETSc_call(MatSetOption, mat, MAT_SYMMETRIC, PETSC_FALSE);
			PETSc_call(MatSetOption, mat, MAT_STRUCTURALLY_SYMMETRIC, PETSC_FALSE);
			}

			PETSc_call(MatSetValues, mat, rows.size(), rows.storage(), cols.size(),
			cols.storage(), values.storage(), ADD_VALUES);
			}

			/* -------------------------------------------------------------------------- */

			} // namespace akantu

rAKA/src/solver/sparse_matrix_petsc.cc205db61909bcbugfixes/41-group-not…

sparse_matrix_petsc.ccView Options

rAKA/src/solver/sparse_matrix_petsc.cc
205db61909bcbugfixes/41-group-not…

sparse_matrix_petsc.cc
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