When using the SchurEliminator to compute a preconditioner, there
is no rhs. This CL removes that limitation and simplifies the
call sites in the two preconditioners.
https://github.com/ceres-solver/ceres-solver/issues/271
Change-Id: I05b8518fdc9f0d1a6d88ae76d3a7e8e838e7204a
1. Replace HashMap and HashSet with std::unordered_map and
std::unordered_set respectively.
2. Extract the pair hasher into a struct pair_hash.
3. Delete collections_port.h
4. Convert explicit iterator based loops to auto based
loops where sensible.
Change-Id: Ib88bcd13a7463d18435639d3b771abaa52080efb
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
SchurEliminator::Init now takes a bool that tells it whether
it can assume that the diagonal blocks it is inverting can
be assumed to be full rank or not.
This information is then passed onto InvertPSDMatrix.
Change-Id: I26037b6233f2aad5584fed245f631c3959928afe
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
For historical reasons we had a "using namespace std;" in port.h. This
is generally a bad idea. So removing it and along the way doing a bunch
of cpplint cleanup.
Change-Id: Ia125601a55ae62695e247fb0250df4c6f86c46c6
1. Extend the implementation of BlockRandomAccessDiagonalMatrix
by adding Invert and RightMultiply methods.
2. Simplify the implementation of the Schur Jacobi preconditioner
using these new methods.
3. Replace the custom storage used inside Block Jacobi preconditioner
with BlockRandomAccessDiagonalMatrix and simplify its implementation
too.
Change-Id: I9d4888b35f0f228c08244abbdda5298b3ce9c466
This class is used in the SchurJacobiPreconditioner for
storing the preconditioner matrix. Using it speeds up
the computation of the preconditioner by ~15% due to
the elimination of a hash table lookup.
Change-Id: Iba2b34aad0d9eb9bcb7f6e6fad16aa416aac0d2a
colPivHouseholderQR -> householderQR
ldlt -> llt.
The resulting performance differences are significant enough
to justify switching.
LAPACK's dgels routine used for solving linear least squares
problems does not use pivoting either.
Similarly, we are not actually using the fact that the matrix
being factorized can be indefinite when using LDLT factorization, so
its not clear that the performance hit is worth it.
These two changes result in Eigen being able to use blocking
algorithms, which for Cholesky factorization, brings the performance
closer to hardware optimized LAPACK. Similarly for dense QR
factorization, on intel there is a 2x speedup.
Change-Id: I4459ee0fc8eb87d58e2b299dfaa9e656d539dc5e
This sets the stage of preconditioners that can utilize
different kinds of matrix layouts, just like the LinearSolver
class hierarchy.
Change-Id: I3579cf344bcd2eeeecb1ae621cab02a3c9a0f920
1. Added a Preconditioner interface.
2. SCHUR_JACOBI is now its own class and is independent of
SuiteSparse.
Change-Id: Id912ab19cf3736e61d1b90ddaf5bfba33e877ec4
Kuang Fangjun