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Add a general sparse iterative solver: CGNR

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This adds a new LinearOperator which implements symmetric
products of a matrix, and a new CGNR solver to leverage
CG to directly solve the normal equations. This also
includes a block diagonal preconditioner. In experiments
on problem-16, the non-preconditioned version is about
1/5 the speed of SPARSE_SCHUR, and the preconditioned
version using block cholesky is about 20% slower than
SPARSE_SCHUR.
This commit is contained in:
Keir Mierle
2012-05-05 20:55:08 -07:00
parent 0a359d6198
commit f7898fba1b
13 changed files with 478 additions and 26 deletions
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examples/bundle_adjuster.cc
+8 -3
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@@ -66,8 +66,8 @@
DEFINE_string(input, "", "Input File name");
DEFINE_string(solver_type, "sparse_schur", "Options are: "
"sparse_schur, dense_schur, iterative_schur, cholesky "
"and dense_qr");
"sparse_schur, dense_schur, iterative_schur, cholesky, "
"dense_qr, and conjugate_gradients");
DEFINE_string(preconditioner_type, "jacobi", "Options are: "
"identity, jacobi, schur_jacobi, cluster_jacobi, "
@@ -75,6 +75,7 @@ DEFINE_string(preconditioner_type, "jacobi", "Options are: "
DEFINE_int32(num_iterations, 5, "Number of iterations");
DEFINE_int32(num_threads, 1, "Number of threads");
DEFINE_double(eta, 1e-2, "Default value for eta.");
DEFINE_bool(use_schur_ordering, false, "Use automatic Schur ordering.");
DEFINE_bool(use_quaternions, false, "If true, uses quaternions to represent "
"rotations. If false, angle axis is used");
@@ -94,6 +95,8 @@ void SetLinearSolver(Solver::Options* options) {
options->linear_solver_type = ceres::ITERATIVE_SCHUR;
} else if (FLAGS_solver_type == "cholesky") {
options->linear_solver_type = ceres::SPARSE_NORMAL_CHOLESKY;
} else if (FLAGS_solver_type == "conjugate_gradients") {
options->linear_solver_type = ceres::CONJUGATE_GRADIENTS;
} else if (FLAGS_solver_type == "dense_qr") {
// DENSE_QR is included here for completeness, but actually using
// this opttion is a bad idea due to the amount of memory needed
@@ -105,7 +108,8 @@ void SetLinearSolver(Solver::Options* options) {
<< FLAGS_solver_type;
}
if (options->linear_solver_type == ceres::ITERATIVE_SCHUR) {
if (options->linear_solver_type == ceres::ITERATIVE_SCHUR ||
options->linear_solver_type == ceres::CONJUGATE_GRADIENTS) {
options->linear_solver_min_num_iterations = 5;
if (FLAGS_preconditioner_type == "identity") {
options->preconditioner_type = ceres::IDENTITY;
@@ -178,6 +182,7 @@ void SetMinimizerOptions(Solver::Options* options) {
options->max_num_iterations = FLAGS_num_iterations;
options->minimizer_progress_to_stdout = true;
options->num_threads = FLAGS_num_threads;
options->eta = FLAGS_eta;
}
void SetSolverOptionsFromFlags(BALProblem* bal_problem,