mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-30 00:50:37 +08:00
Sameer Agarwal
7a3c43b847
By virtue of the modeling layer in Ceres being block oriented, all the matrices used by Ceres are also block oriented. When doing sparse direct factorization of these matrices, the fill-reducing ordering algorithms can either be run on the block or the scalar form of these matrices. Running it on the block form exposes more of the super-nodal structure of the matrix to the Cholesky factorization routines. This leads to substantial gains in factorization performance. This changelist adds support for approximate minimium degree orderings to be computed on the block structure of the Schur complement matrix. This affects, SchurComplementSolver and VisibilityBasedPreconditioner and SparseNormalCholesky when using SuiteSparse. A bool, use_block_amd has been added to Solver::Options and bundle_adjuster.cc has been updated to allow testing with it. When combined with a multithreaded Schur elimination, speed ups can be seen quite uniformly across the board. For some problems this can be dramatic, reducing the factorization time from 70 seconds down to 17 seconds. Change-Id: I15ebb0afcbc85ada032ec8d179ee3a2f7c8d3e46
92 lines
3.4 KiB
C++
92 lines
3.4 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
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// http://code.google.com/p/ceres-solver/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
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//
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// A solver for sparse linear least squares problem based on solving
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// the normal equations via a sparse cholesky factorization.
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#ifndef CERES_INTERNAL_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
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#define CERES_INTERNAL_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
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#ifndef CERES_NO_SUITESPARSE
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#include "cholmod.h"
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#include "ceres/suitesparse.h"
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#endif // CERES_NO_SUITESPARSE
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#include "ceres/linear_solver.h"
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#include "ceres/internal/macros.h"
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namespace ceres {
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namespace internal {
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class CompressedRowSparseMatrix;
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// Solves the normal equations (A'A + D'D) x = A'b, using the CHOLMOD sparse
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// cholesky solver.
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class SparseNormalCholeskySolver : public CompressedRowSparseMatrixSolver {
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public:
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explicit SparseNormalCholeskySolver(const LinearSolver::Options& options);
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virtual ~SparseNormalCholeskySolver();
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private:
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virtual LinearSolver::Summary SolveImpl(
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CompressedRowSparseMatrix* A,
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const double* b,
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const LinearSolver::PerSolveOptions& options,
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double* x);
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LinearSolver::Summary SolveImplUsingSuiteSparse(
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CompressedRowSparseMatrix* A,
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const double* b,
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const LinearSolver::PerSolveOptions& options,
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double* x);
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// Crashes if CSparse is not installed.
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LinearSolver::Summary SolveImplUsingCXSparse(
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CompressedRowSparseMatrix* A,
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const double* b,
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const LinearSolver::PerSolveOptions& options,
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double* x);
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#ifndef CERES_NO_SUITESPARSE
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SuiteSparse ss_;
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// Cached factorization
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cholmod_factor* factor_;
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#endif // CERES_NO_SUITESPARSE
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const LinearSolver::Options options_;
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CERES_DISALLOW_COPY_AND_ASSIGN(SparseNormalCholeskySolver);
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};
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} // namespace internal
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} // namespace ceres
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#endif // CERES_INTERNAL_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
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