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Like in change 2606abed535744fcaa41b923c71338a06b8ed3fa
, we have hit the threshould again. With
AVX512 builds we would never have Vector8f packets aligned at 64
bytes (the new value of EIGEN_MAX_ALIGN_BYTES after change 405859f18dac56f324e1d93ca8721d5f7fd22c62
,
for AVX512-enabled builds).
This makes test/dynalloc.cpp pass for those builds.
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long
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warnings in that case as well
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it takes several hours to build.
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those we need to by-pass realloc routines and fall-back to allocate as new - copy - delete. The remaining problem is that we don't have any mechanism to accurately determine whether a type is relocatable or not, so currently let's be super conservative using either RequireInitialization or std::is_trivially_copyable
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type to be used in other unit tests.
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them (splitting can thus be avoided for them)
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EIGEN_DECLARE_TEST(mytest) { /* code */ }.
This provide several advantages:
- more flexibility in designing unit tests
- unit tests can be glued to speed up compilation
- unit tests are compiled with same predefined macros, which is a requirement for zapcc
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disable multi-threaded GEMM on non-x86 without c++11.
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instead of re-generating it. This also allows us to modify it without breaking existing build folder.
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indexed_view have to be split unconditionally.
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Adding support for using Eigen in HIP kernels.
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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.
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stack local temporaries via alloca, and let outer-products makes a good use of it.
If successful, we should use it everywhere nested_eval is used to declare local dense temporaries.
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There are two major changes (and a few minor ones which are not listed here...see PR discussion for details)
1. Eigen::half implementations for HIP and CUDA have been merged.
This means that
- `CUDA/Half.h` and `HIP/hcc/Half.h` got merged to a new file `GPU/Half.h`
- `CUDA/PacketMathHalf.h` and `HIP/hcc/PacketMathHalf.h` got merged to a new file `GPU/PacketMathHalf.h`
- `CUDA/TypeCasting.h` and `HIP/hcc/TypeCasting.h` got merged to a new file `GPU/TypeCasting.h`
After this change the `HIP/hcc` directory only contains one file `math_constants.h`. That will go away too once that file becomes a part of the HIP install.
2. new macros EIGEN_GPUCC, EIGEN_GPU_COMPILE_PHASE and EIGEN_HAS_GPU_FP16 have been added and the code has been updated to use them where appropriate.
- `EIGEN_GPUCC` is the same as `(EIGEN_CUDACC || EIGEN_HIPCC)`
- `EIGEN_GPU_DEVICE_COMPILE` is the same as `(EIGEN_CUDA_ARCH || EIGEN_HIP_DEVICE_COMPILE)`
- `EIGEN_HAS_GPU_FP16` is the same as `(EIGEN_HAS_CUDA_FP16 or EIGEN_HAS_HIP_FP16)`
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rewriting them as: s*(A.lazyProduct(B)) to save a costly temporary. Measured speedup from 2x to 5x...
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This commit enables the use of Eigen on HIP kernels / AMD GPUs. Support has been added along the same lines as what already exists for using Eigen in CUDA kernels / NVidia GPUs.
Application code needs to explicitly define EIGEN_USE_HIP when using Eigen in HIP kernels. This is because some of the CUDA headers get picked up by default during Eigen compile (irrespective of whether or not the underlying compiler is CUDACC/NVCC, for e.g. Eigen/src/Core/arch/CUDA/Half.h). In order to maintain this behavior, the EIGEN_USE_HIP macro is used to switch to using the HIP version of those header files (see Eigen/Core and unsupported/Eigen/CXX11/Tensor)
Use the "-DEIGEN_TEST_HIP" cmake option to enable the HIP specific unit tests.
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Gustavo Lima Chaves
Gael Guennebaud
Christoph Hertzberg
Deven Desai