commit 19ab2c1793c145f22e7017b570a036f8b3024758
author Sameer Agarwal <sameeragarwal@google.com> Wed Dec 21 16:01:36 2022 -0800
committer Sameer Agarwal <sameeragarwal@google.com> Fri Dec 23 06:45:28 2022 -0800
tree 6ad762e8cd2a56514cc21c71b91ca7259d22d4b3
parent a3a062d72cc8c0f5f1f09b36d8b7c1ea3bef4d73

BlockRandomAccessMatrix Refactor

1. Add threading to all three subclasses of BlockRandomAccessMatrix.
   i.e. BlockRandomAccessDenseMatrix, BlockRandomAccessSparseMatrix
   and BlockRandomAccessDenseMatrix.

   For BlockRandomAccessDenseMatrix and BlockRandomAccessSparseMatrix
   this just means SetZero is parallelized. Which by itself is no
   big deal, but by doing so, the constructor for all three subclasses
   become uniform.

   BlockRandomAccessSparseMatrix::SymmetricRightMultiplyAndAccumulate
   maybe threaded in the future if needed.

   BlockRandomAccessDiagonalMatrix is the biggest beneficiary. SetZero
   Invert and RightMultiplyAndAccumulate are all threaded now.

2. Change the storage in BlockRandomAccessDiagonalMatrix from
   TripletSparseMatrix to CompressedRowSparseMatrix. This has no
   performance implications since we do not really use the capabilities
   of the underlying matrix indexing representation. This is a forward
   looking change when we decide to transfer this matrix to the GPU,
   a CompressedRowSparseMatrix will save on a data conversion.

3. Use std::unique_ptr as needed and eliminate the need for custom
   destructors.

4. Modify CompressedRowSparseMatrix::CreateBlockDiagonalMatrix to
   take a nullptr as the data vector.

Fixes https://github.com/ceres-solver/ceres-solver/issues/936
Fixes https://github.com/ceres-solver/ceres-solver/issues/935

Change-Id: Ia6487f2d924fbe669835bdcc38abf2b451bda4ee