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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
// * Neither the name of Google Inc. nor the names of its contributors may be
// used to endorse or promote products derived from this software without
// specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Author: keir@google.com (Keir Mierle)
#ifndef CERES_INTERNAL_CGNR_SOLVER_H_
#define CERES_INTERNAL_CGNR_SOLVER_H_
#include <memory>
#include "ceres/conjugate_gradients_solver.h"
#include "ceres/cuda_sparse_matrix.h"
#include "ceres/cuda_vector.h"
#include "ceres/internal/export.h"
#include "ceres/linear_solver.h"
namespace ceres::internal {
class Preconditioner;
class BlockJacobiPreconditioner;
// A conjugate gradients on the normal equations solver. This directly solves
// for the solution to
//
// (A^T A + D^T D)x = A^T b
//
// as required for solving for x in the least squares sense. Currently only
// block diagonal preconditioning is supported.
class CERES_NO_EXPORT CgnrSolver final : public BlockSparseMatrixSolver {
public:
explicit CgnrSolver(LinearSolver::Options options);
CgnrSolver(const CgnrSolver&) = delete;
void operator=(const CgnrSolver&) = delete;
~CgnrSolver() override;
Summary SolveImpl(BlockSparseMatrix* A,
const double* b,
const LinearSolver::PerSolveOptions& per_solve_options,
double* x) final;
private:
const LinearSolver::Options options_;
std::unique_ptr<Preconditioner> preconditioner_;
Vector cg_solution_;
Vector* scratch_[4] = {nullptr, nullptr, nullptr, nullptr};
};
#ifndef CERES_NO_CUDA
class CudaPreconditioner : public ConjugateGradientsLinearOperator<CudaVector> {
public:
virtual void Update(const CompressedRowSparseMatrix& A, const double* D) = 0;
virtual ~CudaPreconditioner() = default;
};
// A Cuda-accelerated version of CgnrSolver.
// This solver assumes that the sparsity structure of A remains constant for its
// lifetime.
class CERES_NO_EXPORT CudaCgnrSolver final
: public CompressedRowSparseMatrixSolver {
public:
explicit CudaCgnrSolver(LinearSolver::Options options);
static std::unique_ptr<CudaCgnrSolver> Create(LinearSolver::Options options,
std::string* error);
~CudaCgnrSolver() override;
Summary SolveImpl(CompressedRowSparseMatrix* A,
const double* b,
const LinearSolver::PerSolveOptions& per_solve_options,
double* x) final;
private:
void CpuToGpuTransfer(const CompressedRowSparseMatrix& A,
const double* b,
const double* D);
LinearSolver::Options options_;
std::unique_ptr<CudaSparseMatrix> A_;
std::unique_ptr<CudaVector> b_;
std::unique_ptr<CudaVector> x_;
std::unique_ptr<CudaVector> Atb_;
std::unique_ptr<CudaVector> Ax_;
std::unique_ptr<CudaVector> D_;
std::unique_ptr<CudaPreconditioner> preconditioner_;
CudaVector* scratch_[4] = {nullptr, nullptr, nullptr, nullptr};
};
#endif // CERES_NO_CUDA
} // namespace ceres::internal
#endif // CERES_INTERNAL_CGNR_SOLVER_H_