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CUDA CGNR, Part 4: CudaCgnrSolver

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* Added CudaCgnrSolver, a new CUDA-accelerated CGNR.
* To use CudaCgnrSolver, the user must select CGNR as the linear_solver
  and CUDA_SPARSE as the sparse_linear_algebra_library.
* Updated ConjugateGradientSolver to work with an array of pointers to
  scratch to support CudaVectors as scratch.
* Moved CUDA initialization to run in Solver::Solve as needed.

Some performance comparisons on an Ubuntu 20.04 desktop with an
Intel i9-9940X CPU @ 3.30GHz, and an nVidia Quadro RTX 6000,
all configurations run with 24 threads, and 10 iterations.

=================================================
CGNR + CUDA_SPARSE + IDENTITY Preconditioner
problem-1778-993923-pre.txt
=================================================
Cost:
Initial                          2.563973e+08
Final                            1.724755e+06
Change                           2.546725e+08

Minimizer iterations                       11
Successful steps                            7
Unsuccessful steps                          4

Time (in seconds):
Preprocessor                         4.020158

  Residual only evaluation           1.567092 (10)
  Jacobian & residual evaluation     7.847130 (7)
  Linear solver                     31.688898 (10)
Minimizer                           46.834987

Postprocessor                        0.353974
Total                               51.209120

=================================================
SPARSE_SCHUR (CPU) + SUITE_SPARSE + AMD
problem-1778-993923-pre.txt
=================================================
Cost:
Initial                          2.563973e+08
Final                            1.651617e+06
Change                           2.547457e+08

Minimizer iterations                       11
Successful steps                           11
Unsuccessful steps                          0

Time (in seconds):
Preprocessor                        35.812003

  Residual only evaluation           1.658980 (10)
  Jacobian & residual evaluation    12.218799 (11)
  Linear solver                     76.409992 (10)
Minimizer                           98.809773

Postprocessor                        0.372712
Total                              134.994489

=================================================
ITERATIVE_SCHUR (CPU) + JACOBI Preconditioner
problem-1778-993923-pre.txt
=================================================
Cost:
Initial                          2.563973e+08
Final                            1.684447e+06
Change                           2.547128e+08

Minimizer iterations                       11
Successful steps                            8
Unsuccessful steps                          3

Time (in seconds):
Preprocessor                        15.331614

  Residual only evaluation           1.606114 (10)
  Jacobian & residual evaluation     8.502166 (8)
  Linear solver                    351.910080 (10)
Minimizer                          368.797327

Postprocessor                        0.363536
Total                              384.492478

=================================================
CGNR + CUDA_SPARSE + IDENTITY Preconditioner
problem-13682-4456117-pre.txt
=================================================
Cost:
Initial                          1.126372e+09
Final                            2.269329e+07
Change                           1.103678e+09

Minimizer iterations                       11
Successful steps                            7
Unsuccessful steps                          4

Time (in seconds):
Preprocessor                        19.140087

  Residual only evaluation           8.721920 (10)
  Jacobian & residual evaluation    41.955923 (7)
  Linear solver                    214.121861 (10)
Minimizer                          296.636890

Postprocessor                        1.971827
Total                              317.748804

Change-Id: I3a09f31aa6903f661e91f595afd39d427583e856
This commit is contained in:
Joydeep Biswas
2022-08-14 19:14:04 -05:00
parent 6ab435d774
commit 829089053e
21 changed files with 413 additions and 59 deletions
Download Patch File Download Diff File Expand all files Collapse all files
examples/bundle_adjuster.cc
+8 -4
View File
@@ -81,8 +81,9 @@ DEFINE_string(blocks_for_inner_iterations, "automatic", "Options are: "
"automatic, cameras, points, cameras,points, points,cameras");
DEFINE_string(linear_solver, "sparse_schur", "Options are: "
"sparse_schur, dense_schur, iterative_schur, sparse_normal_cholesky, "
"dense_qr, dense_normal_cholesky and cgnr.");
"sparse_schur, dense_schur, iterative_schur, "
"sparse_normal_cholesky, dense_qr, dense_normal_cholesky, "
"and cgnr.");
DEFINE_bool(explicit_schur_complement, false, "If using ITERATIVE_SCHUR "
"then explicitly compute the Schur complement.");
DEFINE_string(preconditioner, "jacobi", "Options are: "
@@ -94,11 +95,13 @@ DEFINE_bool(use_spse_initialization, false,
"Use power series expansion to initialize the solution in ITERATIVE_SCHUR linear solver.");
DEFINE_string(sparse_linear_algebra_library, "suite_sparse",
"Options are: suite_sparse, cx_sparse, accelerate_sparse and eigen_sparse.");
"Options are: suite_sparse, accelerate_sparse, eigen_sparse, and "
"cuda_sparse.");
DEFINE_string(dense_linear_algebra_library, "eigen",
"Options are: eigen, lapack, and cuda");
DEFINE_string(ordering_type, "amd", "Options are: amd, nesdis");
DEFINE_string(linear_solver_ordering, "automatic", "Options are: automatic and user");
DEFINE_string(linear_solver_ordering, "automatic",
"Options are: automatic and user");
DEFINE_bool(use_quaternions, false, "If true, uses quaternions to represent "
"rotations. If false, angle axis is used.");
@@ -351,6 +354,7 @@ void SolveProblem(const char* filename) {
SetSolverOptionsFromFlags(&bal_problem, &options);
options.gradient_tolerance = 1e-16;
options.function_tolerance = 1e-16;
options.parameter_tolerance = 1e-16;
Solver::Summary summary;
Solve(options, &problem, &summary);
std::cout << summary.FullReport() << "\n";