eigen - C++ library for linear algebra

	Commit message (Collapse)	Author	Age
*	bug #1684: partially workaround clang's 6/7 bug #40815	Gael Guennebaud	2019-03-13
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*	updates based on PR feedback	Deven Desai	2018-06-14
\| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \|	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)`
*	Add a EIGEN_NO_CUDA option, and introduce EIGEN_CUDACC and EIGEN_CUDA_ARCH ↵	Gael Guennebaud	2017-07-17
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*	bug #1376: add missing assertion on size mismatch with compound assignment ↵	Gael Guennebaud	2017-01-23
\| \| \| \|	operators (e.g., mat += mat.col(j))
*	Relax mixing-type constraints for binary coefficient-wise operators:	Gael Guennebaud	2016-06-06
\| \| \| \| \| \| \| \| \| \|	- Replace internal::scalar_product_traits<A,B> by Eigen::ScalarBinaryOpTraits<A,B,OP> - Remove the "functor_is_product_like" helper (was pretty ugly) - Currently, OP is not used, but it is available to the user for fine grained tuning - Currently, only the following operators have been generalized: ,/,+,-,=,=,/=,+=,-= - TODO: generalize all other binray operators (comparisons,pow,etc.) - TODO: handle "scalar op array" operators (currently only * is handled) - TODO: move the handling of the "void" scalar type to ScalarBinaryOpTraits
*	bug #1231: fix compilation regression regarding complex_array/=real_array ↵	Gael Guennebaud	2016-05-18
\| \| \| \|	and add respective unit tests
*	Fix vectorization of swap for non trivial expressions	Gael Guennebaud	2015-03-31
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*	Make cuda_basic test compile again by adding lots of EIGEN_DEVICE_FUNC.	Christoph Hertzberg	2014-10-13
\| \| \| \|	Although the test passes now, there might still be some missing.
*	Fix mixing scalar types with evaluators	Gael Guennebaud	2014-02-19
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*	Fix vectorization logic wrt assignment functors	Gael Guennebaud	2014-02-19
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*	bug #99: refactor assignment and compound assignment mechanism through ↵	Gael Guennebaud	2013-11-06
	"assignment functors" and "assignement kernels". The former is very low level and generic. The later abstarct the former for dense expressions. This refactoring permits to get rid of the very ugly SwapWrapper and SelfCwiseBinaryOp classes. In the future, this will also permit to simplify all these evaluation loops and perhaps to reuse them for reduxions. That will also permit to specialize for operations like expr1 += expr2 outside Eigen, and so for any kind of expressions (dense, sparse, tensor, etc.)