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path: root/unsupported/Eigen/CXX11/src/Tensor/TensorEvaluator.h
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* Enabling per device specialisation of packetsize.Gravatar Mehdi Goli2018-08-01
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* Rename Index to StorageIndex + use Eigen::Array and Eigen::Map when possibleGravatar Eugene Zhulenev2018-07-27
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* Add tiled evaluation support to TensorExecutorGravatar Eugene Zhulenev2018-07-25
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* Avoid using memcpy for non-POD elementsGravatar Weiming Zhao2018-04-11
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* Add a EIGEN_NO_CUDA option, and introduce EIGEN_CUDACC and EIGEN_CUDA_ARCH ↵Gravatar Gael Guennebaud2017-07-17
| | | | aliases
* Merged in mehdi_goli/opencl/DataDependancy (pull request PR-10)Gravatar Benoit Steiner2017-06-28
| | | | | | | | | | 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
* Adding TensorIndexTuple and TensorTupleReduceOP backend (ArgMax/Min) for ↵Gravatar Mehdi Goli2017-03-07
| | | | sycl; fixing the address space issue for const TensorMap; converting all discard_write to write due to data missmatch.
* Converting all parallel for lambda to functor in order to prevent kernel ↵Gravatar Mehdi Goli2016-12-16
| | | | duplication name error; adding tensorConcatinationOp backend for sycl.
* Adding tensor contraction operation backend for Sycl; adding test for ↵Gravatar Mehdi Goli2016-12-14
| | | | contractionOp sycl backend; adding temporary solution to prevent memory leak in buffer; cleaning up cxx11_tensor_buildins_sycl.h
* Merged with default.Gravatar Luke Iwanski2016-09-19
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* | Partial OpenCL support via SYCL compatible with ComputeCpp CE.Gravatar Luke Iwanski2016-09-19
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| * Made the index type an explicit template parameter to help some compilers ↵Gravatar Benoit Steiner2016-09-02
| | | | | | | | compile the code.
| * Adjust Tensor module wrt recent change in nullary functorGravatar Gael Guennebaud2016-09-01
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| * Force the inlining of a simple accessor.Gravatar Benoit Steiner2016-08-18
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* bug #1266: half implementation has been moved to half_impl namespaceGravatar Benoit Steiner2016-07-29
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* Moved assertions to the constructor to make the code more portableGravatar Benoit Steiner2016-06-06
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* Add TernaryFunctors and the betainc SpecialFunction.Gravatar Eugene Brevdo2016-06-02
| | | | | | | | | | | | | | | | | | | 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.
* Added the ability to load fp16 using the texture path.Gravatar Benoit Steiner2016-05-11
| | | | Improved the performance of some reductions on fp16
* Deleted unnecessary variableGravatar Benoit Steiner2016-04-15
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* Eigen Tensor cost model part 2: Thread scheduling for standard evaluators ↵Gravatar Rasmus Munk Larsen2016-04-14
| | | | and reductions. The cost model is turned off by default.
* Eigen cost model part 1. This implements a basic recursive framework to ↵Gravatar Rasmus Munk Larsen2016-04-14
| | | | estimate the cost of evaluating tensor expressions.
* Fixed the tensor chipping code.Gravatar Benoit Steiner2016-03-08
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* Decoupled the packet type definition from the definition of the tensor ops. ↵Gravatar Benoit Steiner2016-03-08
| | | | 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.
* Record whether the underlying tensor storage can be accessed directly during ↵Gravatar Benoit Steiner2016-01-19
| | | | the evaluation of an expression.
* Added support for rank-0 tensorsGravatar Benoit Steiner2015-10-29
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* Fix Tensor module wrt nullary functor recent changeGravatar Gael Guennebaud2015-08-09
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* Use NumTraits<T>::RequireInitialization instead of ↵Gravatar Benoit Steiner2015-07-07
| | | | internal::is_arithmetic<T>::value to check whether it's possible to bypass the type constructor in the tensor code.
* Only attempt to use the texture path on GPUs when it's supported by CUDAGravatar Benoit Steiner2015-07-06
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* Sped up the assignment of a tensor to a tensor slice, as well as the ↵Gravatar Benoit Steiner2015-04-20
| | | | assigment of a constant slice to a tensor
* Fixed the vectorized implementation of the Tensor select() methodGravatar Benoit Steiner2015-03-25
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* Silenced more compilation warningsGravatar Benoit Steiner2015-02-10
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* Silcenced a few compilation warningsGravatar Benoit Steiner2015-02-10
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* Silenced several compilation warningsGravatar Benoit Steiner2015-02-10
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* Fixed the return type of coefficient wise operations. For example, the abs ↵Gravatar Benoit Steiner2015-01-14
| | | | function returns a floating point value when called on a complex input.
* Fixed the return type of the coefficient-wise tensor operations.Gravatar Benoit Steiner2014-11-04
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* Fixed the return types of unary and binary expressions to properly handle ↵Gravatar Benoit Steiner2014-10-16
| | | | the case where it is different from the input type (e.g. abs(complex<float>))
* Misc improvements and cleanupsGravatar Benoit Steiner2014-10-13
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* Added suppor for in place evaluation to simple tensor expressions.Gravatar Benoit Steiner2014-08-13
| | | | Use mempy to speedup tensor copies whenever possible.
* Improved evaluation of tensor expressions when used as rvaluesGravatar Benoit Steiner2014-07-08
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* Reworked the expression evaluation mechanism in order to make it possible to ↵Gravatar Benoit Steiner2014-06-13
| | | | | | | | 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 ↵Gravatar Benoit Steiner2014-06-10
| | | | | | partial template specialization to optimize the strategy of each evaluator for each device type. Started work on partial evaluations.
* Added support for tensor contractionsGravatar Benoit Steiner2014-06-04
| | | | | Updated expression evaluation mechanism to also compute the size of the tensor result Misc fixes and improvements.
* Added support for additional tensor operations:Gravatar Benoit Steiner2014-05-22
| | | | | | | | * 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, ...)Gravatar Benoit Steiner2014-05-16
| | | | | 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.Gravatar Benoit Steiner2014-05-06
| | | | Improved support for tensor expressions.
* Extended support for Tensors:Gravatar Benoit Steiner2014-04-28
* 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.
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