It is based on the SSE version which is much more accurate, though very slightly slower.
This changeset also includes the following required changes:
- add packet-float to packet-int type traits
- add packet float<->int reinterpret casts
- add faster pselect for AVX based on blendv
1. Eigen/src/Core/arch/GPU/Half.h
Updating the HIPCC implementation half so that it can declared as a __shared__ variable
2. Eigen/src/Core/util/Macros.h, Eigen/src/Core/util/Memory.h
introducing a EIGEN_USE_STD(func) macro that calls
- std::func be default
- ::func when eigen is being compiled with HIPCC
This change was requested in the previous HIP PR
(https://bitbucket.org/eigen/eigen/pull-requests/518/pr-with-hip-specific-fixes-for-the-eigen/diff)
3. unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h
Removing EIGEN_DEVICE_FUNC attribute from pure virtual methods as it is not supported by HIPCC
4. unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
Disabling the template specializations of InnerMostDimReducer as they run into HIPCC link errors
* Support compiling without IO streams
Add the preprocessor definition EIGEN_NO_IO which, if defined,
disables all use of the IO streams part of the standard library.
Compiling the eigen unittests with hip-clang (HIP with clang as the underlying compiler instead of hcc or nvcc), results in compile errors. The changes in this commit fix those compile errors. The main change is to convert a few instances of "__device__" to "EIGEN_DEVICE_FUNC"
This commit fixes the AVX512 implementations of psqrt in the same
way that 3ed67cb0bb
fixed the AVX2 version of this function. The
AVX512 versions of psqrt incorrectly return -0.0 for negative
values, instead of NaN. Fixing the issues requires adding
some additional instructions that slow down the algorithms. A
similar test to the one used in 3ed67cb0bb
shows that the
corrected Packet16f code runs at 73% of the speed of the existing code,
while the corrected Packed8d function runs at 68% of the original.
The major changes are
1. Moving CUDA/PacketMath.h to GPU/PacketMath.h
2. Moving CUDA/MathFunctions.h to GPU/MathFunction.h
3. Moving CUDA/CudaSpecialFunctions.h to GPU/GpuSpecialFunctions.h
The above three changes effectively enable the Eigen "Packet" layer for the HIP platform
4. Merging the "hip_basic" and "cuda_basic" unit tests into one ("gpu_basic")
5. Updating the "EIGEN_DEVICE_FUNC" marking in some places
The change has been tested on the HIP and CUDA platforms.
The AVX512 version of ptranpose for PacketBlock<Packet16h,16> was
reordering the PacketBlock argument incorrectly. This lead to errors in
the multiplication of matrices composed of 16 bit floats on AVX512
machines, if at least of the matrices was using RowMajor order. This
error is responsible for one tensorflow unit test failure on AVX512
machines:
//tensorflow/python/kernel_tests:batch_matmul_op_test
