eigen - C++ library for linear algebra

	Commit message (Collapse)	Author	Age
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*	Fixed compilation errors triggered by old versions of gcc	Benoit Steiner	2016-05-12
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*	Eigen cost model part 1. This implements a basic recursive framework to ↵	Rasmus Munk Larsen	2016-04-14
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*	Worked around a constness related issue	Benoit Steiner	2016-03-21
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*	Small cleanup	Benoit Steiner	2016-03-21
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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.
*	Deleted the coordinate based evaluation of tensor expressions, since it's ↵	Benoit Steiner	2016-02-22
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*	Fixed a constness bug	Benoit Steiner	2016-01-21
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*	Record whether the underlying tensor storage can be accessed directly during ↵	Benoit Steiner	2016-01-19
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*	Add alignment requirement for local buffer used by the slicing op.	Benoit Steiner	2015-12-18
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*	Fix return type for TensorEvaluator<TensorSlicingOp>::data	Benoit Steiner	2015-09-17
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*	Many files were missing in previous changeset.	Gael Guennebaud	2015-07-29
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*	Use NumTraits<T>::RequireInitialization instead of ↵	Benoit Steiner	2015-07-07
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*	Misc small fixes to the tensor slicing code.	Benoit Steiner	2015-07-06
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*	Fixed a couple of mistakes in the previous commit.	Benoit Steiner	2015-07-01
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*	Enabled the vectorized evaluation of several tensor expressions that was ↵	Benoit Steiner	2015-07-01
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*	Avoid using the cuda memcpy for small tensor slices since the memcpy kernel ↵	Benoit Steiner	2015-05-19
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*	Sped up the assignment of a tensor to a tensor slice, as well as the ↵	Benoit Steiner	2015-04-20
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*	Fixed another batch of compilation warnings	Benoit Steiner	2015-02-28
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*	Fixed several compilation warnings reported by clang	Benoit Steiner	2015-02-25
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*	Silenced a few compilation warnings generated by nvcc	Benoit Steiner	2015-02-10
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*	Silenced more compilation warnings	Benoit Steiner	2015-02-10
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*	gcc doesn't consider that	Benoit Steiner	2015-01-16
\| \| \| \| \| \| \| \| \| \| \|	template<typename OtherDerived> TensorStridingOp& operator = (const OtherDerived& other) provides a valid assignment operator for the striding operation, and therefore refuses to compile code like: result.stride(foo) = source.stride(bar); Added the explicit TensorStridingOp& operator = (const TensorStridingOp& other) as a workaround to get the code to compile, and did the same in all the operations that can be used as lvalues.
*	Improved support for RowMajor tensors	Benoit Steiner	2015-01-14
\| \| \| \|	Misc fixes and API cleanups.
*	fixed some potential alignment issues.	Benoit Steiner	2014-10-30
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*	Added access to the unerlying raw data of a tnsor slice/chip whenever possible	Benoit Steiner	2014-10-17
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*	Silenced a few compilation warnings	Benoit Steiner	2014-10-16
\| \| \| \|	Generalized a TensorMap constructor
*	Added tests for tensors of const values and tensors of stringswwq::	Benoit Steiner	2014-10-01
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*	Misc fixes.	Benoit Steiner	2014-09-05
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*	Optimized and cleaned up the tensor morphing code	Benoit Steiner	2014-08-23
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*	Added support for fast integer divisions by a constant	Benoit Steiner	2014-08-14
\| \| \| \|	Sped up tensor slicing by a factor of 3 by using these fast integer divisions.
*	Support for in place evaluation of expressions containing slicing and ↵	Benoit Steiner	2014-08-13
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*	Vectorized the evaluation of expressions involving tensor slices.	Benoit Steiner	2014-07-10
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*	Improved the speed of slicing operations.	Benoit Steiner	2014-07-09
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*	Added support for tensor slicing	Benoit Steiner	2014-07-07
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*	Reworked the expression evaluation mechanism in order to make it possible to ↵	Benoit Steiner	2014-06-13
\| \| \| \| \| \| \| \|	efficiently compute convolutions and contractions in the future: * The scheduling of computation is moved out the the assignment code and into a new TensorExecutor class * The assignment itself is now a regular node on the expression tree * The expression evaluators start by recursively evaluating all their subexpressions if needed
*	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