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user that the computation failed, possibly due to invalid input.
Make Jacobi and divide-and-conquer fail fast and return info() == InvalidInput if the matrix contains NaN or +/-Inf.
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Currently if compiled by NVCC, the `MatrixBase::bdcSvd()` implementation
is skipped, leading to a linker error. This prevents it from running on
the host as well.
Seems it was disabled 6 years ago (5384e891) to match `jacobiSvd`, but
`jacobiSvd` is now enabled on host. Tested and runs fine on host, but
will not compile/run for device (though it's not labelled as a device
function, so this should be fine).
Fixes #2139
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This fixes compilation issues with RealScalar types that are not implicitly castable from Index (e.g. ceres Jet types).
Reported by Peter Anderson-Sprecher via eMail
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at the middle range without a shift might give a wrong sign.
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This changeset also includes:
* add HouseholderSequence::conjugateIf
* define int as the StorageIndex type for all dense solvers
* dedicated unit tests, including assertion checking
* _check_solve_assertion(): this method can be implemented in derived solver classes to implement custom checks
* CompleteOrthogonalDecompositions: add applyZOnTheLeftInPlace, fix scalar type in applyZAdjointOnTheLeftInPlace(), add missing assertions
* Cholesky: add missing assertions
* FullPivHouseholderQR: Corrected Scalar type in _solve_impl()
* BDCSVD: Unambiguous return type for ternary operator
* SVDBase: Corrected Scalar type in _solve_impl()
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There are two major changes (and a few minor ones which are not listed here...see PR discussion for details)
1. Eigen::half implementations for HIP and CUDA have been merged.
This means that
- `CUDA/Half.h` and `HIP/hcc/Half.h` got merged to a new file `GPU/Half.h`
- `CUDA/PacketMathHalf.h` and `HIP/hcc/PacketMathHalf.h` got merged to a new file `GPU/PacketMathHalf.h`
- `CUDA/TypeCasting.h` and `HIP/hcc/TypeCasting.h` got merged to a new file `GPU/TypeCasting.h`
After this change the `HIP/hcc` directory only contains one file `math_constants.h`. That will go away too once that file becomes a part of the HIP install.
2. new macros EIGEN_GPUCC, EIGEN_GPU_COMPILE_PHASE and EIGEN_HAS_GPU_FP16 have been added and the code has been updated to use them where appropriate.
- `EIGEN_GPUCC` is the same as `(EIGEN_CUDACC || EIGEN_HIPCC)`
- `EIGEN_GPU_DEVICE_COMPILE` is the same as `(EIGEN_CUDA_ARCH || EIGEN_HIP_DEVICE_COMPILE)`
- `EIGEN_HAS_GPU_FP16` is the same as `(EIGEN_HAS_CUDA_FP16 or EIGEN_HAS_HIP_FP16)`
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This commit enables the use of Eigen on HIP kernels / AMD GPUs. Support has been added along the same lines as what already exists for using Eigen in CUDA kernels / NVidia GPUs.
Application code needs to explicitly define EIGEN_USE_HIP when using Eigen in HIP kernels. This is because some of the CUDA headers get picked up by default during Eigen compile (irrespective of whether or not the underlying compiler is CUDACC/NVCC, for e.g. Eigen/src/Core/arch/CUDA/Half.h). In order to maintain this behavior, the EIGEN_USE_HIP macro is used to switch to using the HIP version of those header files (see Eigen/Core and unsupported/Eigen/CXX11/Tensor)
Use the "-DEIGEN_TEST_HIP" cmake option to enable the HIP specific unit tests.
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for complex numbers. Made corresponding unit test actually test that. Also simplify implementation of QR decompositions
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Found using `codespell` and `grep` from downstream FreeCAD
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aliases
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* they're used consistently between the declaration and the definition of a function
* we avoid calling host only methods from host device methods.
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(those used to break old nvcc versions that we propably don't care anymore)
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install(DIRECTORY ...) command.
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scalar types)
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treated by the 2x2 real preconditioner.
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explicitly handle the 1x1 complex case.
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diagonal block of S to positive diagonal form.
This step involve a real 2x2 SVD problem. The respective routine is thus in src/misc/ to be shared by both EVD and AVD modules.
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infinite binary search when compiling with ICC's unsafe optimizations.
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- avoid noise amplification in complex to real conversion
- compare off-diagonal entries to the current biggest diagonal entry: no need to bother about a 2x2 block containing ridiculously small entries compared to the rest of the matrix.
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diagonal 2x2 block.
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warnings
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(grafted from f22036f5f8bbaa349e090327d246c817bac94ee4
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Rasmus Munk Larsen
Antonio Sanchez
Christoph Hertzberg
Gael Guennebaud
Patrick Peltzer
Deven Desai
luz.paz
Eugene Chereshnev
Benoit Steiner
Niels Ole Salscheider