Add dynamic_sparsity option.
The standard sparse normal Cholesky solver assumes a fixed
sparsity pattern which is useful for a large number of problems
presented to Ceres. However, some problems are symbolically dense
but numerically sparse i.e. each residual is a function of a
large number of parameters but at any given state the residual
only depends on a sparse subset of them. For these class of
problems it is faster to re-analyse the sparsity pattern of the
jacobian at each iteration of the non-linear optimisation instead
of including all of the zero entries in the step computation.
The proposed solution adds the dynamic_sparsity option which can
be used with SPARSE_NORMAL_CHOLESKY. A
DynamicCompressedRowSparseMatrix type (which extends
CompressedRowSparseMatrix) has been introduced which allows
dynamic addition and removal of elements. A Finalize method is
provided which then consolidates the matrix so that it can be
used in place of a regular CompressedRowSparseMatrix. An
associated jacobian writer has also been provided.
Changes that were required to make this extension were adding the
SetMaxNumNonZeros method to CompressedRowSparseMatrix and adding
a JacobianFinalizer template parameter to the ProgramEvaluator.
Change-Id: Ia5a8a9523fdae8d5b027bc35e70b4611ec2a8d01
diff --git a/internal/ceres/unsymmetric_linear_solver_test.cc b/internal/ceres/unsymmetric_linear_solver_test.cc
index 624db68..412e611 100644
--- a/internal/ceres/unsymmetric_linear_solver_test.cc
+++ b/internal/ceres/unsymmetric_linear_solver_test.cc
@@ -172,6 +172,15 @@
options.use_postordering = true;
TestSolver(options);
}
+
+TEST_F(UnsymmetricLinearSolverTest,
+ SparseNormalCholeskyUsingSuiteSparseDynamicSparsity) {
+ LinearSolver::Options options;
+ options.sparse_linear_algebra_library_type = SUITE_SPARSE;
+ options.type = SPARSE_NORMAL_CHOLESKY;
+ options.dynamic_sparsity = true;
+ TestSolver(options);
+}
#endif
#ifndef CERES_NO_CXSPARSE
@@ -192,6 +201,15 @@
options.use_postordering = true;
TestSolver(options);
}
+
+TEST_F(UnsymmetricLinearSolverTest,
+ SparseNormalCholeskyUsingCXSparseDynamicSparsity) {
+ LinearSolver::Options options;
+ options.sparse_linear_algebra_library_type = CX_SPARSE;
+ options.type = SPARSE_NORMAL_CHOLESKY;
+ options.dynamic_sparsity = true;
+ TestSolver(options);
+}
#endif
} // namespace internal
