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path: root/unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
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* Fix more enum arithmetic.Gravatar Rasmus Munk Larsen2021-06-15
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* Fix calls to device functions from host codeGravatar Nathan Luehr2021-05-11
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* Fixing a CUDA / P100 regression introduced by PR 181Gravatar Deven Desai2020-08-20
| | | | | | PR 181 ( https://gitlab.com/libeigen/eigen/-/merge_requests/181 ) adds `__launch_bounds__(1024)` attribute to GPU kernels, that did not have that attribute explicitly specified. That PR seems to cause regressions on the CUDA platform. This PR/commit makes the changes in PR 181, to be applicable for HIP only
* Adding an explicit launch_bounds(1024) attribute for GPU kernels.Gravatar Deven Desai2020-08-05
| | | | | | | | | | Starting with ROCm 3.5, the HIP compiler will change from HCC to hip-clang. This compiler change introduce a change in the default value of the `__launch_bounds__` attribute associated with a GPU kernel. (default value means the value assumed by the compiler as the `__launch_bounds attribute__` value, when it is not explicitly specified by the user) Currently (i.e. for HIP with ROCm 3.3 and older), the default value is 1024. That changes to 256 with ROCm 3.5 (i.e. hip-clang compiler). As a consequence of this change, if a GPU kernel with a `__luanch_bounds__` attribute of 256 is launched at runtime with a threads_per_block value > 256, it leads to a runtime error. This is leading to a couple of Eigen unit test failures with ROCm 3.5. This commit adds an explicit `__launch_bounds(1024)__` attribute to every GPU kernel that currently does not have it explicitly specified (and hence will end up getting the default value of 256 with the change to hip-clang)
* Remove V2 suffix from TensorBlockGravatar Eugene Zhulenev2019-12-10
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* Remove legacy block evaluation supportGravatar Eugene Zhulenev2019-11-12
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* Tensor block evaluation V2 support for unary/binary/broadcstingGravatar Eugene Zhulenev2019-09-24
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* [SYCL] This PR adds the minimum modifications to the Eigen unsupported ↵Gravatar Mehdi Goli2019-06-28
| | | | | | | | | | 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.
* Add block evaluationto CwiseUnaryOp and add PreferBlockAccess enum to all ↵Gravatar Eugene Zhulenev2018-08-10
| | | | evaluators
* Fix init order.Gravatar Rasmus Munk Larsen2018-08-07
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* Fixed compilation errors.Gravatar Benoit Steiner2018-08-06
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* Enabling per device specialisation of packetsize.Gravatar Mehdi Goli2018-08-01
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* Add tiled evaluation support to TensorExecutorGravatar Eugene Zhulenev2018-07-25
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* Introduce gpu_assert for assertion in device-code, and disable them with ↵Gravatar Gael Guennebaud2018-07-13
| | | | clang-cuda.
* merging the CUDA and HIP implementation for the Tensor directory and the ↵Gravatar Deven Desai2018-06-20
| | | | unit tests
* Add a EIGEN_NO_CUDA option, and introduce EIGEN_CUDACC and EIGEN_CUDA_ARCH ↵Gravatar Gael Guennebaud2017-07-17
| | | | aliases
* Fixed syntax errors generated by xcodeGravatar Benoit Steiner2017-07-09
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* 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 non-deferrenciable pointer track for ComputeCpp backend; Adding ↵Gravatar Mehdi Goli2017-01-19
| | | | TensorConvolutionOp for ComputeCpp; fixing typos. modifying TensorDeviceSycl to use the LegacyPointer class.
* Marked a few tensor operations as read onlyGravatar Benoit Steiner2016-05-05
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* Deleted trailing commasGravatar Benoit Steiner2016-04-29
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* Added missing definition of PacketSize in the gpu evaluator of convolutionGravatar Benoit Steiner2016-04-14
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* 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.
* 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.
* Fixed a number of compilation warnings generated by the cuda testsGravatar Benoit Steiner2016-01-31
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* Record whether the underlying tensor storage can be accessed directly during ↵Gravatar Benoit Steiner2016-01-19
| | | | the evaluation of an expression.
* Use numext::mini/numext::maxi instead of std::min/std::max in the tensor codeGravatar Benoit Steiner2015-08-28
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* Many files were missing in previous changeset.Gravatar Gael Guennebaud2015-07-29
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* Added support for multi gpu configuration to the GpuDevice classGravatar Benoit Steiner2015-07-15
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* Misc improvements and optimizationsGravatar Benoit Steiner2015-07-01
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* Enabled the vectorized evaluation of several tensor expressions that was ↵Gravatar Benoit Steiner2015-07-01
| | | | previously disabled by mistake
* Fixed a compilation error triggered by nvcc 7Gravatar Benoit Steiner2015-05-28
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* Added support for convolution of tensors laid out in RowMajor modeGravatar Benoit Steiner2015-03-31
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* Silenced the last batch of compilation warnings triggered by gcc 4.8Gravatar Benoit Steiner2015-02-10
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* Improved support for RowMajor tensorsGravatar Benoit Steiner2015-01-14
| | | | Misc fixes and API cleanups.
* Silenced a few compilation warningsGravatar Benoit Steiner2014-10-16
| | | | Generalized a TensorMap constructor
* Misc improvements and cleanupsGravatar Benoit Steiner2014-10-13
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* Improved the performance of the tensor convolution code by a factor of about 4.Gravatar Benoit Steiner2014-09-03
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* Improved the speed of convolutions when running on cuda devicesGravatar Benoit Steiner2014-08-19
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* Fixed misc typos.Gravatar Benoit Steiner2014-08-13
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* Added missing apis.Gravatar Benoit Steiner2014-08-13
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* Updated the convolution and contraction evaluators to follow the new ↵Gravatar Benoit Steiner2014-08-13
| | | | EvalSubExprsIfNeeded apu.
* Silenced a compilation warningGravatar Benoit Steiner2014-06-13
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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
* Fixed a few compilation errors.Gravatar Benoit Steiner2014-06-10
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* 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.
* Improved support for rvalues in tensor expressions.Gravatar Benoit Steiner2014-06-09
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* Added support for convolution and reshaping of tensors.Gravatar Benoit Steiner2014-06-06
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