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* Fix typo in TypeCasting.hGravatar Rasmus Munk Larsen2020-04-14
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* Fix big in vectorized casting ofGravatar Rasmus Munk Larsen2020-04-14
| | | | | | {uint8, int8} -> {int16, uint16, int32, uint32, float} {uint16, int16} -> {int32, uint32, int64, uint64, float} for NEON. These conversions were advertised as vectorized, but not actually implemented.
* CommaInitializer wrongfully asserted for 0-sized blocksGravatar Christoph Hertzberg2020-04-13
| | | | commainitialier unit-test never actually called `test_block_recursion`, which also was not correctly implemented and would have caused too deep template recursion.
* Fixed commainitializer test.Gravatar Antonio Sanchez2020-04-10
| | | | | | The removed `finished()` call was responsible for enforcing that the initializer was provided the correct number of values. Putting it back in to restore previous behavior.
* Speed up matrix multiplication for small to medium size matrices by using ↵Gravatar Rasmus Munk Larsen2020-04-07
| | | | | | | | | | | | | | | | | | | | | | | | | | | | half- or quarter-packet vectorized loads in gemm_pack_rhs if they have size 4, instead of dropping down the the scalar path. Benchmark measurements below are for computing ```c.noalias() = a.transpose() * b;``` for square RowMajor matrices of varying size. Measured improvement with AVX+FMA: name old time/op new time/op delta BM_MatMul_ATB/8 139ns ± 1% 129ns ± 1% -7.49% (p=0.008 n=5+5) BM_MatMul_ATB/32 1.46µs ± 1% 1.22µs ± 0% -16.72% (p=0.008 n=5+5) BM_MatMul_ATB/64 8.43µs ± 1% 7.41µs ± 0% -12.04% (p=0.008 n=5+5) BM_MatMul_ATB/128 56.8µs ± 1% 52.9µs ± 1% -6.83% (p=0.008 n=5+5) BM_MatMul_ATB/256 407µs ± 1% 395µs ± 3% -2.94% (p=0.032 n=5+5) BM_MatMul_ATB/512 3.27ms ± 3% 3.18ms ± 1% ~ (p=0.056 n=5+5) Measured improvement for AVX512: name old time/op new time/op delta BM_MatMul_ATB/8 167ns ± 1% 154ns ± 1% -7.63% (p=0.008 n=5+5) BM_MatMul_ATB/32 1.08µs ± 1% 0.83µs ± 3% -23.58% (p=0.008 n=5+5) BM_MatMul_ATB/64 6.21µs ± 1% 5.06µs ± 1% -18.47% (p=0.008 n=5+5) BM_MatMul_ATB/128 36.1µs ± 2% 31.3µs ± 1% -13.32% (p=0.008 n=5+5) BM_MatMul_ATB/256 263µs ± 2% 242µs ± 2% -7.92% (p=0.008 n=5+5) BM_MatMul_ATB/512 1.95ms ± 2% 1.91ms ± 2% ~ (p=0.095 n=5+5) BM_MatMul_ATB/1k 15.4ms ± 4% 14.8ms ± 2% ~ (p=0.095 n=5+5)
* Missing struct definition in NumTraitsGravatar Antonio Sanchez2020-04-07
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* Add numeric_limits min and max for boolGravatar Akshay Naresh Modi2020-04-06
| | | | This will allow (among other things) computation of argmax and argmin of bool tensors
* Bugfix: conjugate_gradient did not compile with lazy-evaluated RealScalarGravatar Bernardo Bahia Monteiro2020-03-29
| | | | | | | | | | | | | | | | | The error generated by the compiler was: no matching function for call to 'maxi' RealScalar threshold = numext::maxi(tol*tol*rhsNorm2,considerAsZero); The important part in the following notes was: candidate template ignored: deduced conflicting types for parameter 'T'" ('codi::Multiply11<...>' vs. 'codi::ActiveReal<...>') EIGEN_ALWAYS_INLINE T maxi(const T& x, const T& y) I am using CoDiPack to provide the RealScalar type. This bug was introduced in bc000deaa Fix conjugate-gradient for very small rhs
* Fix bug in ↵Gravatar Rasmus Munk Larsen2020-03-27
| | | | https://gitlab.com/libeigen/eigen/-/commit/52d54278beefee8b2f19dcca4fd900916154e174
* NEON: Fixed MSVC types definitionsGravatar Joel Holdsworth2020-03-26
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* Additional NEON packet-math operationsGravatar Joel Holdsworth2020-03-26
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* Adhere to recommended load/store intrinsics for pp64leGravatar Everton Constantino2020-03-23
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* Fixing float32's pround halfway criteria to match STL's criteria.Gravatar Everton Constantino2020-03-21
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* Fixed:Gravatar Alessio M2020-03-21
| | | | | - access violation when initializing 0x0 matrices - exception can be thrown during stack unwind while comma-initializing a matrix if eigen_assert if configured to throw
* Update VectorwiseOp.h to allow Plugins similar to MatrixBase.h or ArrayBase.hGravatar dlazenby2020-03-20
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* Bug https://gitlab.com/libeigen/eigen/-/issues/1415: add missing ↵Gravatar Masaki Murooka2020-03-20
| | | | EIGEN_DEVICE_FUNC to diagonal_product_evaluator_base.
* Remove reference to non-existent unary_op_base class.Gravatar Rasmus Munk Larsen2020-03-19
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* Add missing arguments to numext::absdiff().Gravatar Rasmus Munk Larsen2020-03-19
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* Add absolute_difference coefficient-wise binary Array functionGravatar Joel Holdsworth2020-03-19
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* Reenabling packetmath unsigned tests, adding dummy pabs for relevant unsignedGravatar Everton Constantino2020-03-19
| | | | types.
* Add shift_left<N> and shift_right<N> coefficient-wise unary Array functionsGravatar Joel Holdsworth2020-03-19
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* Implement integer square-root for NEONGravatar Joel Holdsworth2020-03-19
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* Update NullaryFunctors.hGravatar Allan Leal2020-03-16
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* Fixing HIP breakage caused by the recent commit that introduces Packet4h2 as ↵Gravatar Deven Desai2020-03-12
| | | | the Eigen::Half packet type
* NEON: Added int64_t and uint64_t packet mathGravatar Joel Holdsworth2020-03-10
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* NEON: Added int8_t and uint8_t packet mathGravatar Joel Holdsworth2020-03-10
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* NEON: Added int16_t and uint16_t packet mathGravatar Joel Holdsworth2020-03-10
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* NEON: Added uint32_t packet mathGravatar Joel Holdsworth2020-03-10
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* NEON: Implemented half-size vectorsGravatar Joel Holdsworth2020-03-10
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* NEON: Set packet_traits<double> flagsGravatar Joel Holdsworth2020-03-10
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* remove duplicate pset1 for half and add some comments about why we need ↵Gravatar Sami Kama2020-03-10
| | | | expose pmul/add/div/min/max on host
* Revert "avoid selecting half-packets when unnecessary"Gravatar Rasmus Munk Larsen2020-02-25
| | | This reverts commit 5ca10480b0756e40b0723d90adeba8506291fc7c
* Revert "Pick full packet unconditionally when EIGEN_UNALIGNED_VECTORIZE"Gravatar Rasmus Munk Larsen2020-02-25
| | | This reverts commit 44df2109c8c700222643a9a45f144676348f4df1
* Revert "do not pick full-packet if it'd result in more operations"Gravatar Rasmus Munk Larsen2020-02-25
| | | This reverts commit e9cc0cd353803a818204e48054bd89699b84e6c6
* Include <sstream> explicitly, and don't rely on the implicit include via ↵Gravatar Tobias Bosch2020-02-24
| | | | | <complex>. This implicit dependency does no longer exist in a recent llbm release (sha 78be61871704).
* do not pick full-packet if it'd result in more operationsGravatar Francesco Mazzoli2020-02-07
| | | | | See comment and <https://gitlab.com/libeigen/eigen/merge_requests/46#note_270622952>.
* Pick full packet unconditionally when EIGEN_UNALIGNED_VECTORIZEGravatar Francesco Mazzoli2020-02-07
| | | | See comment for details.
* avoid selecting half-packets when unnecessaryGravatar Francesco Mazzoli2020-02-07
| | | | | | | | | | | | | | | | | | | | | | | | | | | See <https://stackoverflow.com/questions/59709148/ensuring-that-eigen-uses-avx-vectorization-for-a-certain-operation> for an explanation of the problem this solves. In short, for some reason, before this commit the half-packet is selected when the array / matrix size is not a multiple of `unpacket_traits<PacketType>::size`, where `PacketType` starts out being the full Packet. For example, for some data of 100 `float`s, `Packet4f` will be selected rather than `Packet8f`, because 100 is not a multiple of 8, the size of `Packet8f`. This commit switches to selecting the half-packet if the size is less than the packet size, which seems to make more sense. As I stated in the SO post I'm not sure that I'm understanding the issue correctly, but this fix resolves the issue in my program. Moreover, `make check` passes, with the exception of line 614 and 616 in `test/packetmath.cpp`, which however also fail on master on my machine: CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_i0, internal::pbessel_i0); ... CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_i1, internal::pbessel_i1);
* Remove rogue include in TypeCasting.h. Meta.h is already included by the ↵Gravatar Rasmus Munk Larsen2020-01-14
| | | | top-level header in Eigen/Core.
* Switching unpacket_traits<Packet4i> to vectorizable=true.Gravatar Everton Constantino2020-01-13
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* Adding correct cache sizes for PPC architecture.Gravatar Everton Constantino2020-01-13
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* call Explicitly ::rint and ::rintf for targets without c++11. Without this, ↵Gravatar Rasmus Munk Larsen2020-01-10
| | | | the Windows build breaks when trying to compile numext::rint<double>.
* Improvements to the tidiness and completeness of the NEON implementationGravatar Joel Holdsworth2020-01-10
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* Fix for gcc build error when using Eigen headers with AVX512Gravatar Anuj Rawat2020-01-10
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* Adding RInt vector support for SYCL.Gravatar mehdi-goli2020-01-10
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* Don't add EIGEN_DEVICE_FUNC to random() since ::rand is not available in Cuda.Gravatar Rasmus Munk Larsen2020-01-09
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* Add missing EIGEN_DEVICE_FUNC annotations in MathFunctions.h.Gravatar Rasmus Munk Larsen2020-01-09
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* Don't use the rational approximation to the logistic function on GPUs as it ↵Gravatar Rasmus Munk Larsen2020-01-09
| | | | appears to be slightly slower.
* The upper limits for where to use the rational approximation to the logistic ↵Gravatar Rasmus Munk Larsen2020-01-08
| | | | function were not set carefully enough in the original commit, and some arguments would cause the function to return values greater than 1. This change set the versions found by scanning all floating point numbers (using std::nextafterf()).
* Bug #1785: Introduce numext::rint.Gravatar Ilya Tokar2020-01-07
| | | | | | This provides a new op that matches std::rint and previous behavior of pround. Also adds corresponding unsupported/../Tensor op. Performance is the same as e. g. floor (tested SSE/AVX).
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