gmres.hpp

// SPDX-FileCopyrightText: 2017 - 2026 The Ginkgo authors
//
// SPDX-License-Identifier: BSD-3-Clause
 
#ifndef GKO_PUBLIC_CORE_SOLVER_GMRES_HPP_
#define GKO_PUBLIC_CORE_SOLVER_GMRES_HPP_
 
 
#include <vector>
 
#include <ginkgo/core/base/array.hpp>
#include <ginkgo/core/base/exception_helpers.hpp>
#include <ginkgo/core/base/lin_op.hpp>
#include <ginkgo/core/base/math.hpp>
#include <ginkgo/core/base/types.hpp>
#include <ginkgo/core/config/config.hpp>
#include <ginkgo/core/config/registry.hpp>
#include <ginkgo/core/log/logger.hpp>
#include <ginkgo/core/matrix/dense.hpp>
#include <ginkgo/core/matrix/identity.hpp>
#include <ginkgo/core/solver/solver_base.hpp>
#include <ginkgo/core/stop/combined.hpp>
#include <ginkgo/core/stop/criterion.hpp>
 
 
namespace gko {
namespace solver {
 
 
[[deprecated("please use gmres_default_krylov_dim")]] constexpr size_type
    default_krylov_dim = 100u;
 
constexpr size_type gmres_default_krylov_dim = 100u;
 
namespace gmres {
enum class ortho_method {
    mgs,
    cgs,
    cgs2
};
 
std::ostream& operator<<(std::ostream& stream, ortho_method ortho);
 
}  // namespace gmres
 
template <typename ValueType = default_precision>
class Gmres
    : public LinOp,
      public EnablePreconditionedIterativeSolver<ValueType, Gmres<ValueType>>,
      public Transposable {
    GKO_ASSERT_SUPPORTED_VALUE_TYPE;
 
public:
    using value_type = ValueType;
    using transposed_type = Gmres<ValueType>;
 
    std::unique_ptr<LinOp> transpose() const override;
 
    std::unique_ptr<LinOp> conj_transpose() const override;
 
    bool apply_uses_initial_guess() const override { return true; }
 
    size_type get_krylov_dim() const { return parameters_.krylov_dim; }
 
    void set_krylov_dim(size_type other) { parameters_.krylov_dim = other; }
 
    remove_complex<ValueType> get_restart_ratio() const
    {
        return parameters_.restart_ratio;
    }
 
    void set_restart_ratio(remove_complex<ValueType> other)
    {
        parameters_.restart_ratio = other;
    }
 
 
    class Factory;
 
    struct parameters_type
        : enable_preconditioned_iterative_solver_factory_parameters<
              parameters_type, Factory> {
        size_type GKO_FACTORY_PARAMETER_SCALAR(krylov_dim, 0u);
 
        remove_complex<ValueType> GKO_FACTORY_PARAMETER_SCALAR(restart_ratio,
                                                               0.0);
 
        bool GKO_FACTORY_PARAMETER_SCALAR(flexible, false);
 
        gmres::ortho_method GKO_FACTORY_PARAMETER_SCALAR(
            ortho_method, gmres::ortho_method::mgs);
    };
    GKO_ENABLE_LIN_OP_FACTORY(Gmres, parameters, Factory);
    GKO_ENABLE_BUILD_METHOD(Factory);
 
    static parameters_type parse(const config::pnode& config,
                                 const config::registry& context,
                                 const config::type_descriptor& td_for_child =
                                     config::make_type_descriptor<ValueType>());
 
protected:
    void apply_impl(const LinOp* b, LinOp* x) const override;
 
    template <typename VectorType>
    void apply_dense_impl(const VectorType* b, VectorType* x) const;
 
    void apply_impl(const LinOp* alpha, const LinOp* b, const LinOp* beta,
                    LinOp* x) const override;
 
    explicit Gmres(std::shared_ptr<const Executor> exec)
        : LinOp(std::move(exec))
    {}
 
    explicit Gmres(const Factory* factory,
                   std::shared_ptr<const LinOp> system_matrix)
        : LinOp(factory->get_executor(),
                gko::transpose(system_matrix->get_size())),
          EnablePreconditionedIterativeSolver<ValueType, Gmres<ValueType>>{
              std::move(system_matrix), factory->get_parameters()},
          parameters_{factory->get_parameters()}
    {
        if (!parameters_.krylov_dim) {
            parameters_.krylov_dim = gmres_default_krylov_dim;
        }
        GKO_THROW_IF_INVALID(
            parameters_.restart_ratio >= zero<remove_complex<ValueType>>() &&
                parameters_.restart_ratio < one<remove_complex<ValueType>>(),
            "restart_ratio must lie in [0, 1); zero disables the criterion");
    }
};
 
 
template <typename ValueType>
struct nullspace_traits<Gmres<ValueType>> {
    static constexpr bool is_supported = true;
    static constexpr bool requires_hermitian = false;
    static constexpr bool two_sided_projection = false;
};
 
 
template <typename ValueType>
struct workspace_traits<Gmres<ValueType>> {
    using Solver = Gmres<ValueType>;
    // number of vectors used by this workspace
    static int num_vectors(const Solver&);
    // number of arrays used by this workspace
    static int num_arrays(const Solver&);
    // array containing the num_vectors names for the workspace vectors
    static std::vector<std::string> op_names(const Solver&);
    // array containing the num_arrays names for the workspace vectors
    static std::vector<std::string> array_names(const Solver&);
    // array containing all varying scalar vectors (independent of problem size)
    static std::vector<int> scalars(const Solver&);
    // array containing all varying vectors (dependent on problem size)
    static std::vector<int> vectors(const Solver&);
 
    // residual vector
    constexpr static int residual = 0;
    // preconditioned vector
    constexpr static int preconditioned_vector = 1;
    // krylov basis multivector
    constexpr static int krylov_bases = 2;
    // hessenberg matrix
    constexpr static int hessenberg = 3;
    // auxiliary space for CGS2
    constexpr static int hessenberg_aux = 4;
    // givens sin parameters
    constexpr static int givens_sin = 5;
    // givens cos parameters
    constexpr static int givens_cos = 6;
    // coefficients of the residual in Krylov space
    constexpr static int residual_norm_collection = 7;
    // residual norm scalar
    constexpr static int residual_norm = 8;
    // solution of the least-squares problem in Krylov space
    constexpr static int y = 9;
    // solution of the least-squares problem mapped to the full space
    constexpr static int before_preconditioner = 10;
    // preconditioned solution of the least-squares problem
    constexpr static int after_preconditioner = 11;
    // constant 1.0 scalar
    constexpr static int one = 12;
    // constant -1.0 scalar
    constexpr static int minus_one = 13;
    // temporary norm vector of next_krylov to copy into hessenberg matrix
    constexpr static int next_krylov_norm_tmp = 14;
    // preconditioned krylov basis multivector
    constexpr static int preconditioned_krylov_bases = 15;
    // right-hand side projected onto the range of the system matrix
    constexpr static int proj_rhs = 16;
 
    // stopping status array
    constexpr static int stop = 0;
    // reduction tmp array
    constexpr static int tmp = 1;
    // final iteration number array
    constexpr static int final_iter_nums = 2;
};
 
 
}  // namespace solver
}  // namespace gko
 
 
#endif  // GKO_PUBLIC_CORE_SOLVER_GMRES_HPP_