eigen - C++ library for linear algebra

	Commit message (Collapse)	Author	Age
*	Added support for tensor chips	Benoit Steiner	2014-10-10
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*	Rewrote the TensorBase::random method to support the generation of random ↵	Benoit Steiner	2014-10-09
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*	Added support for the = and / operators to TensorBase	Benoit Steiner	2014-10-08
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*	Added support for tensor reductions and concatenations	Benoit Steiner	2014-10-01
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*	Added support for evaluation of tensor shuffling operations as lvalues	Benoit Steiner	2014-09-04
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*	Added support for broadcasting	Benoit Steiner	2014-08-20
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*	Added support for padding, stridding, and shuffling	Benoit Steiner	2014-08-14
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*	Added support for tensor slicing	Benoit Steiner	2014-07-07
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*	TensorEval are now typed on the device: this will make it possible to use ↵	Benoit Steiner	2014-06-10
\| \| \| \| \| \|	partial template specialization to optimize the strategy of each evaluator for each device type. Started work on partial evaluations.
*	Improved support for rvalues in tensor expressions.	Benoit Steiner	2014-06-09
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*	Added support for convolution and reshaping of tensors.	Benoit Steiner	2014-06-06
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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.