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
cuDSS could be used as an alternative for SuiteSparse and EigenSparse
in case if CUDA capable GPU is available.
Change-Id: I7a567093ce91363478118153e181134ed5804573
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
- Perform temporary buffer size estimation only once
- Allow construction from existing buffers with col/row structure
Change-Id: I73c291328f1e8ed9184aba5d7058df71cbc6a15d
* All Cuda* objects now take in a ContextImpl* during
construction, and save the context instead of individual
handles.
* Since we no longer use the legacy default stream, we need to
explicitly synchronize the stream before performing GPU->CPU
transfers, and CudaBuffer is responsible for such synchronization
when asked to perform GPU to CPU transfers.
* Remove all manual syncs and relegate syncing to CudaBuffer
before performing GPU to CPU transfers.
Change-Id: Ic73cb24174a1e09842827323280e90241716cc20
These methods were historically poorly named and every time I read code
I get confused whether they are just multiplying or multiplying and
adding. Clarifying them also gives us the changce to introduce
RightMultiply and LeftMultiply methods in the base class which will
simplify a number call sites in a subsequent CL.
Fixes https://github.com/ceres-solver/ceres-solver/issues/855
Change-Id: Ice4fb483f1acd02527a6dd753ef0c5a66037f4b0
* Fixed an alignment bug with EventLogger.
* Added expected solutions to some LinearLeastSquaresProblem tests.
* Expanded ContextImpl to initialize cuSparse.
Change-Id: I2d7556a0509e9b7c56c9cd5cfa75cb85614395dc
* Renamed several interfaces to CudaBuffer for clarity and consistency.
* Added unit tests for custom Cuda kernels.
* Set specific CUDA architectures if the CMake version supports it.
Change-Id: I269fb1089b80b25e17bca772ef8d70e7894214b8
On problem-744-543562-pre.txt
The time spent in linear solver on my M1 Pro is
eigen 81.550970
eigen+mixed 54.107383
LAPACK 47.078127
LAPACK+mixed 28.639868
Solution quality is unaffected.
The implementation of RefinedDenseCholesky and DenseIterativeRefiner
are straightforward ports of RefinedSparseCholesky and
SparseIterativeRefiner (formerly IterativeRefiner).
It maybe possible to refactor the SparseCholesky and DenseCholesky
interfaces so that this code duplication can be removed in the
future.
Change-Id: I921334224cb97629a60390f2add822de207f7923
1. Add CUDADenseQR & tests.
CUDADenseQR uses the cuSolverDN LAPACK implementation
of QR factorization. A key limitation, however, is that
this solver does not perform singularity checking --
this is because cuSolverDN does not have a trtrs
implementation; we instead use cuBLAS' trsv for
backsubstitution.
2. All CPU -> GPU memory transfers are now async, and both
CUDADenseQR and CUDADenseCholesky explicitly manage their
own streams for async operations.
3. Simplified CUDADenseCholesky to only use the legacy 32-bit
cuSolverDN API.
Change-Id: I2a9b7b65469658ddfe33b5b2a3892c8744d6e437
Applied changes correspond to clang-tidy fixes
stemming from the modernize-use-equals-default check.
Change-Id: I254b0908a76d464131564b637cd0e42a6b03fb5a
1. Add CUDADenseCholesky64Bit, CUDADenseCholesky32Bit, & tests.
CUDADenseCholesky32Bit uses the legacy versions of potrf/potrs
in cuSolverDN, while CUDADenseCholesky64Bit uses the new 64-bit
versions available since Cuda 11.1. The legacy versions are
provided since some platforms such as the Nvidia Jetsons only
support Cuda 10.2.
2. Expose CUDA as a new option under DenseLinearAlgebraLibraryType.
The relevant option to string and string to option helper functions
are modified accordingly.
3. Add cuda as a dense_linear_algebra_library option in bundle_adjuster
to demonstrate the use of the new CUDA option.
Change-Id: I23615e1d301df5185ed646b3e33ee802508dae86
Sameer Agarwal