Commit Graph

25 Commits

Author SHA1 Message Date
Sameer Agarwal 0a53aa9054 Take abseil as a dependency
1. Add abseil-cpp as a submodule. We are tracking the latest LTS
release, which is lts_2024_01_16.
2. Replace glog/gflags with absl::log and absl::flags.
3. Remove miniglog
4. Also take a whack at making the bazel build work with
   abseil-cpp and gtest.

There are a number of TODOs in this CL that still need to be resolved.

Change-Id: I39355ed7d61375be4ebcbc8596d9cc70acc1c678
2024-07-18 00:24:49 -07:00
Sameer Agarwal 5a30cae583 Preparing for 2.2.0rc1
1. Add a version history
2. Update copyright years across the code base
3. Run format_all.sh
4. Update version strings from 2.1.0 to 2.2.0 in the docs and
   elsewhere.

Change-Id: I46d8d479d54bd6002d532785e67342106e73c9ac
2023-09-21 11:23:38 -07:00
Joydeep Biswas 829089053e CUDA CGNR, Part 4: CudaCgnrSolver
* 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
2022-08-15 23:44:34 -05:00
Sameer Agarwal caf614a6c1 Modernize code using c++17 constructs
Mostly done using

find . \( -name '*.cc' -o -name '*.h' \) -a -type f -exec clang-tidy -p \
cmake-build -checks='-*,google-*,modernize-*,-modernize-use-nodiscard,-modernize-use-trailing-return-type' {} -fix \;

Change-Id: Ifccbcabe7a1d9a32a09d28ac4f3f8466696c1a50
2022-04-22 06:11:18 -07:00
Sameer Agarwal 4705159858 Add missing includes for config.h
covariance.h was using SUITE_SPARSE even when SUITESPARSE
was disabled because it did not have config.h included in it
so it did not see that CERES_NO_SUITESPARSE was defined.

Add more config.h includes to files that are using these
configuration macros.

Change-Id: I6b1d2c2bd9e559de40a6332cd6be85ad4da3377b
2022-03-12 15:55:19 -08:00
Sameer Agarwal 446487c54c Add <memory> header to all files using std::unique_ptr.
Fixes https://github.com/ceres-solver/ceres-solver/issues/758

Change-Id: I884819ec62cf7dcb95368eb46f3c03a46bb5243f
2022-02-12 08:12:05 -08:00
Sameer Agarwal ae65219e04 ClangTidy cleanups
1. NULL -> nullptr
2. foo.reset(new Bar) -> = foo = std::make_unique<Bar>()
3. Missing std library includes & prefixes

Change-Id: I260b261b484554be681ee5a7398126fdb3b3a789
2022-02-09 10:06:49 -08:00
Sergiu Deitsch a35bd1bf90 Use = default for trivial special members
Applied changes correspond to clang-tidy fixes
stemming from the modernize-use-equals-default check.

Change-Id: I254b0908a76d464131564b637cd0e42a6b03fb5a
2022-02-09 18:38:52 +01:00
Nikolaus Demmel 7b8f675bfd fix formatting for (non-generated) internal source files
- Change formatting standard to Cpp11. Main difference is not having
  the space between two closing >> for nested templates. We don't
  choose c++14, because older versions of clang-format (version 9
  and earlier) don't know this value yet, and it doesn't make a
  difference in the formatting.
- Apply clang-format to all (non generated) internal source files.
- Manually fix some code sections (clang-format on/off) and c-strings
- Exclude some embedded external files with very different formatting
  (gtest/gmock)
- Add script to format all source files

Change-Id: Ic6cea41575ad6e37c9e136dbce176b0d505dc44d
2020-09-21 02:52:07 +02:00
Alex Stewart 8f41ca6abc Add Apple's Accelerate framework as a sparse linear algebra library.
- Currently DynamicSparseNormalCholeskySolver is unsupported for
  Accelerate.

Change-Id: I03b5a86bb22fef249c4aecd48947a613e8eff7a5
2018-06-29 09:43:03 +01:00
Mike Vitus f408f89e8b Adds a Ceres Context structure.
A Ceres Context holds common global state that can be re-used within
Ceres.  The Context current contains a thread pool if compiling with
C++11 threading support.  Threads are expensive to create and destroy so
it is good to maintain across multiple Ceres solves.

Tested by compiling with and without TBB support and ran unit tests. Ran
bazel as well.

Change-Id: I82f598dfae642aa0e81a6039dc174608a5e8dbfb
2018-02-26 10:37:53 -08:00
Sameer Agarwal 5c2fd0526a Add DynamicSparseNormalCholeskySolver
This code was currently buried under a bool inside SparseNormalCholeskySolver.
Pulling this out in its own solver makes the code simpler more readable
and more performant in the case of SuiteSparse.

Change-Id: I72379ca9ca162abbb83c12f7ee8ff92bc71e772c
2017-04-11 11:55:43 -07:00
Keir Mierle 7492b0d8de Update copyright headers with new year and URL
Since Ceres is moving to using GitHub for issues, and the Google
Code URL in the current copyright header will soon become invalid,
update all the headers.

Change-Id: I1fce70375d1bcf098591f07b4d8f01a5c1e0789c
2015-03-18 05:43:23 +00:00
Sameer Agarwal b44cfdef25 Let ITERATIVE_SCHUR use an explicit Schur Complement matrix.
Up till now ITERATIVE_SCHUR evaluates matrix-vector products
between the Schur complement and a vector implicitly by exploiting
the algebraic expression for the Schur complement.

This cost of this evaluation scales with the number of non-zeros
in the Jacobian.

For small to medium sized problems there is a sweet spot where
computing the Schur complement is cheap enough that it is much
more efficient to explicitly compute it and use it for evaluating
the matrix-vector products.

This changes implements support for an explicit Schur complement
in ITERATIVE_SCHUR in combination with the SCHUR_JACOBI preconditioner.

API wise a new bool Solver::Options::use_explicit_schur_complement
has been added.

The implementation extends the SparseSchurComplementSolver to use
Conjugate Gradients.

Example speedup:

use_explicit_schur_complement = false

Time (in seconds):
Preprocessor                            0.585

  Residual evaluation                   0.319
  Jacobian evaluation                   1.590
  Linear solver                        25.685
Minimizer                              27.990

Postprocessor                           0.010
Total                                  28.585

use_explicit_schur_complement = true

Time (in seconds):
Preprocessor                            0.638

  Residual evaluation                   0.318
  Jacobian evaluation                   1.507
  Linear solver                         5.930
Minimizer                               8.144

Postprocessor                           0.010
Total                                   8.791

Which indicates an end-to-end speedup of more than 3x, with the linear
solver being sped up by > 4x.

The idea to explore this optimization was inspired by the recent paper:

Mining structure fragments for smart bundle adjustment
L. Carlone, P. Alcantarilla, H. Chiu, K. Zsolt, F. Dellaert
British Machine Vision Conference, 2014

which uses a more complicated algorithm to compute parts of the
Schur complement to speed up the matrix-vector product.

Change-Id: I95324af0ab351faa1600f5204039a1d2a64ae61d
2014-09-29 10:29:32 -07:00
Sameer Agarwal 62a8d64453 Expand check for lack of a sparse linear algebra library.
The LinearSolver factory was creating a NULL linear solver
if only Eigen's sparse linear algebra backend was available.

Thanks to Michael Samples and Domink Reitzle for reporting this.

Change-Id: I35e3a6c0fd0da2a31934adb5dfe4cad29577cc73
2014-08-28 09:46:10 -07:00
Sameer Agarwal 7135be7b34 Conditionally disable SparseNormalCholesky.
Disable creation of SparseNormalCholesky if CXSparse and
SuiteSparse are not evailable.

Change-Id: I9a3beafef0073d1c55305beb0af31bc67ef39691
2014-05-31 23:44:18 -07:00
Sameer Agarwal 1228a4f332 Move alternate linear solver and preconditioner policy.
Move functions that determine alternatives to Schur type linear
solver and preconditioners into the LinearSolver and Preconditioner
interfaces.

Change-Id: Iae900afb7db17cdbeb7753497005a48c3144e2d7
2014-05-30 15:58:44 -07:00
Sameer Agarwal b9f15a5936 Add a dense Cholesky factorization based linear solver.
For problems with a small number of variables, but a large
number of residuals, it is sometimes beneficial to use the
Cholesky factorization on the normal equations, instead of
the dense QR factorization of the Jacobian, even though it
is numerically the better thing to do.

Change-Id: I3506b006195754018deec964e6e190b7e8c9ac8f
2012-08-19 14:47:38 -07:00
Sameer Agarwal 0beab86dfa Fix glog includes and include sorting order.
Change-Id: I0ec85218e82d1714279d41f7635104d480fb91c3
2012-08-13 15:47:24 -07:00
Keir Mierle 9d5fea19f1 Fix minor include and formatting issues.
Change-Id: I14417b775b4d67bba8b0bbbb37fc0b37efc20fbf
2012-06-24 23:36:40 -07:00
Keir Mierle efe7ac60a0 Port Ceres to Windows
This is a preliminary, but full, port of Ceres to Windows.
Currently all tests compile and run, with only system_test
failing to work correctly due to a path issue.

Change-Id: I4152c1588bf51ffd7f4d9401ef9759f5d28c299c
2012-06-24 23:22:04 -07:00
Sameer Agarwal b051873a55 Multiple sparse linear algebra backends.
1. Added support for CXSparse - SparseNormalCholesky and
   SchurComplementSolver support SuiteSparse and CXSparse now.
   I am not sure I will add suport for visibility based
   preconditioning using CXSparse. Its not a high priority.

2. New enum SparseLinearAlgebraLibraryType which allows the user
   to indicate which sparse linear algebra library should be used.

3. Updated tests for SolverImpl and system_test.

4. Build system changes to automatically detect CXSparse and
   link to it by default -- just like SuiteSparse.

5. Minor bug fixes dealing in the cmake files and VBP.

6. Changed the order of the system test.

7. Deduped the unsymmetric linear solver test.

Change-Id: I33252a103c87b722ecb7ed7b5f0ae7fd91249244
2012-05-29 19:44:43 -07:00
Keir Mierle e2a6cdc081 Address some of the comments on CGNR patch
- Rename BlockDiagonalPreconditioner to BlockJacobiPreconditioner
- Include the diagonal in the block jacobi preconditioner.
- Better flag help for eta.
- Enable test for CGNR
- Rename CONJUGATE_GRADIENTS to CGNR.
- etc.
2012-05-07 06:39:56 -07:00
Keir Mierle f7898fba1b Add a general sparse iterative solver: CGNR
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.
2012-05-05 20:55:08 -07:00
Keir Mierle 8ebb073038 Initial commit of Ceres Solver. 2012-04-30 23:09:08 -07:00