eigen - C++ library for linear algebra

	Commit message (Collapse)	Author	Age
*	[SYCL] This PR adds the minimum modifications to the Eigen unsupported ↵	Mehdi Goli	2019-06-28
\| \| \| \| \| \| \| \| \| \|	module required to run it on devices supporting SYCL. * Abstracting the pointer type so that both SYCL memory and pointer can be captured. * Converting SYCL virtual pointer to SYCL device memory in Eigen evaluator class. * Binding SYCL placeholder accessor to command group handler by using bind method in Eigen evaluator node. * Adding SYCL macro for controlling loop unrolling. * Modifying the TensorDeviceSycl.h and SYCL executor method to adopt the above changes.
*	Fixed syntax errors generated by xcode	Benoit Steiner	2017-07-09
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*	Merged in mehdi_goli/opencl/DataDependancy (pull request PR-10)	Benoit Steiner	2017-06-28
\| \| \| \| \| \| \| \| \| \|	DataDependancy * Wrapping data type to the pointer class for sycl in non-terminal nodes; not having that breaks Tensorflow Conv2d code. * Applying Ronnan's Comments. * Applying benoit's comments
*	Fixed a few typos in the ternary tensor expressions types	Benoit Steiner	2016-10-19
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*	Moved assertions to the constructor to make the code more portable	Benoit Steiner	2016-06-06
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*	Add TernaryFunctors and the betainc SpecialFunction.	Eugene Brevdo	2016-06-02
\| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \| \|	TernaryFunctors and their executors allow operations on 3-tuples of inputs. API fully implemented for Arrays and Tensors based on binary functors. Ported the cephes betainc function (regularized incomplete beta integral) to Eigen, with support for CPU and GPU, floats, doubles, and half types. Added unit tests in array.cpp and cxx11_tensor_cuda.cu Collapsed revision * Merged helper methods for betainc across floats and doubles. * Added TensorGlobalFunctions with betainc(). Removed betainc() from TensorBase. * Clean up CwiseTernaryOp checks, change igamma_helper to cephes_helper. * betainc: merge incbcf and incbd into incbeta_cfe. and more cleanup. * Update TernaryOp and SpecialFunctions (betainc) based on review comments.
*	Marked a few tensor operations as read only	Benoit Steiner	2016-05-05
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*	Deleted useless trailing commas	Benoit Steiner	2016-04-29
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*	Decoupled the packet type definition from the definition of the tensor ops. ↵	Benoit Steiner	2016-03-08
\| \| \| \|	All the vectorization is now defined in the tensor evaluators. This will make it possible to relialably support devices with different packet types in the same compilation unit.
*	Added a few missing EIGEN_DEVICE_FUNC statements	Benoit Steiner	2015-05-26
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*	Fixed the return type of coefficient wise operations. For example, the abs ↵	Benoit Steiner	2015-01-14
\| \| \| \|	function returns a floating point value when called on a complex input.
*	Fixed the return types of unary and binary expressions to properly handle ↵	Benoit Steiner	2014-10-16
\| \| \| \|	the case where it is different from the input type (e.g. abs(complex<float>))
*	Improved support for rvalues in tensor expressions.	Benoit Steiner	2014-06-09
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*	Added support for tensor contractions	Benoit Steiner	2014-06-04
\| \| \| \| \|	Updated expression evaluation mechanism to also compute the size of the tensor result Misc fixes and improvements.
*	Added support for additional tensor operations:	Benoit Steiner	2014-05-22
\| \| \| \| \| \| \| \|	* comparison (<, <=, ==, !=, ...) * selection * nullary ops such as random or constant generation * misc unary ops such as log(), exp(), or a user defined unaryExpr() Cleaned up the code a little.
*	Vectorized the evaluation of tensor expression (using SSE, AVX, NEON, ...)	Benoit Steiner	2014-05-16
\| \| \| \| \|	Added the ability to parallelize the evaluation of a tensor expression over multiple cpu cores. Added the ability to offload the evaluation of a tensor expression to a GPU.
*	Added support for fixed sized tensors.	Benoit Steiner	2014-05-06
\| \| \| \|	Improved support for tensor expressions.
*	Extended support for Tensors:	Benoit Steiner	2014-04-28
	* Added ability to map a region of the memory to a tensor * Added basic support for unary and binary coefficient wise expressions, such as addition or square root * Provided an emulation layer to make it possible to compile the code with compilers (such as nvcc) that don't support cxx11.