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* bug #1741: fix C.noalias() = A*C; with C.innerStride()!=1Gravatar Gael Guennebaud2019-09-10
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* PR 681: Add ndtri function, the inverse of the normal distribution function.Gravatar Srinivas Vasudevan2019-08-12
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* Add more tests for corner cases of log1p and expm1. Add handling of infinite ↵Gravatar Rasmus Munk Larsen2019-08-28
| | | | arguments to log1p such that log1p(inf) = inf.
* Revert changes to std_falback::log1p that broke handling of arguments less ↵Gravatar Rasmus Munk Larsen2019-08-27
| | | | than -1. Fix packet op accordingly.
* Clean up float16 a.k.a. Eigen::half support in Eigen. Move the definition of ↵Gravatar Rasmus Munk Larsen2019-08-27
| | | | half to Core/arch/Default and move arch-specific packet ops to their respective sub-directories.
* Implement vectorized versions of log1p and expm1 in Eigen using Kahan's ↵Gravatar Rasmus Munk Larsen2019-08-12
| | | | | | | | | | | | formulas, and change the scalar implementations to properly handle infinite arguments. Depending on instruction set, significant speedups are observed for the vectorized path: log1p wall time is reduced 60-93% (2.5x - 15x speedup) expm1 wall time is reduced 0-85% (1x - 7x speedup) The scalar path is slower by 20-30% due to the extra branch needed to handle +infinity correctly. Full benchmarks measured on Intel(R) Xeon(R) Gold 6154 here: https://bitbucket.org/snippets/rmlarsen/MXBkpM
* Guard against repeated definition of EIGEN_MPL2_ONLYGravatar Rasmus Munk Larsen2019-08-07
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* [SYCL] This PR adds the minimum modifications to Eigen core required to run ↵Gravatar Mehdi Goli2019-06-27
| | | | | | | | Eigen unsupported modules on devices supporting SYCL. * Adding SYCL memory model * Enabling/Disabling SYCL backend in Core * Supporting Vectorization
* Various fixes for packet ops.Gravatar Rasmus Munk Larsen2019-06-20
| | | | | | 1. Fix buggy pcmp_eq and unit test for half types. 2. Add unit test for pselect and add specializations for SSE 4.1, AVX512, and half types. 3. Get rid of FIXME: Implement faster pnegate for half by XOR'ing with a sign bit mask.
* Merged in Artem-B/eigen (pull request PR-654)Gravatar Rasmus Larsen2019-05-31
|\ | | | | | | | | | | Minor build improvements Approved-by: Rasmus Larsen <rmlarsen@google.com>
* | Clean up CUDA/NVCC version macros and their use in Eigen, and a few other ↵Gravatar Rasmus Munk Larsen2019-05-31
| | | | | | | | CUDA build failures.
| * Minor build improvementsGravatar tra2019-05-31
|/ | | | | | | | * Allow specifying multiple GPU architectures. E.g.: cmake -DEIGEN_CUDA_COMPUTE_ARCH="60;70" * Pass CUDA SDK path to clang. Without it it will default to /usr/local/cuda which may not be the right location, if cmake was invoked with -DCUDA_TOOLKIT_ROOT_DIR=/some/other/CUDA/path
* bug #1707: Fix deprecation warnings, or disable warnings when testing ↵Gravatar Christoph Hertzberg2019-05-10
| | | | deprecated functions
* Add masked_store_available to unpacket_traitsGravatar Eugene Zhulenev2019-05-02
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* Add masked pstoreu to AVX and AVX512 PacketMathGravatar Eugene Zhulenev2019-05-02
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* Adding lowlevel APIs for optimized RHS packet load in TensorFlowGravatar Anuj Rawat2019-04-20
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | SpatialConvolution Low-level APIs are added in order to optimized packet load in gemm_pack_rhs in TensorFlow SpatialConvolution. The optimization is for scenario when a packet is split across 2 adjacent columns. In this case we read it as two 'partial' packets and then merge these into 1. Currently this only works for Packet16f (AVX512) and Packet8f (AVX2). We plan to add this for other packet types (such as Packet8d) also. This optimization shows significant speedup in SpatialConvolution with certain parameters. Some examples are below. Benchmark parameters are specified as: Batch size, Input dim, Depth, Num of filters, Filter dim Speedup numbers are specified for number of threads 1, 2, 4, 8, 16. AVX512: Parameters | Speedup (Num of threads: 1, 2, 4, 8, 16) ----------------------------|------------------------------------------ 128, 24x24, 3, 64, 5x5 |2.18X, 2.13X, 1.73X, 1.64X, 1.66X 128, 24x24, 1, 64, 8x8 |2.00X, 1.98X, 1.93X, 1.91X, 1.91X 32, 24x24, 3, 64, 5x5 |2.26X, 2.14X, 2.17X, 2.22X, 2.33X 128, 24x24, 3, 64, 3x3 |1.51X, 1.45X, 1.45X, 1.67X, 1.57X 32, 14x14, 24, 64, 5x5 |1.21X, 1.19X, 1.16X, 1.70X, 1.17X 128, 128x128, 3, 96, 11x11 |2.17X, 2.18X, 2.19X, 2.20X, 2.18X AVX2: Parameters | Speedup (Num of threads: 1, 2, 4, 8, 16) ----------------------------|------------------------------------------ 128, 24x24, 3, 64, 5x5 | 1.66X, 1.65X, 1.61X, 1.56X, 1.49X 32, 24x24, 3, 64, 5x5 | 1.71X, 1.63X, 1.77X, 1.58X, 1.68X 128, 24x24, 1, 64, 5x5 | 1.44X, 1.40X, 1.38X, 1.37X, 1.33X 128, 24x24, 3, 64, 3x3 | 1.68X, 1.63X, 1.58X, 1.56X, 1.62X 128, 128x128, 3, 96, 11x11 | 1.36X, 1.36X, 1.37X, 1.37X, 1.37X In the higher level benchmark cifar10, we observe a runtime improvement of around 6% for AVX512 on Intel Skylake server (8 cores). On lower level PackRhs micro-benchmarks specified in TensorFlow tensorflow/core/kernels/eigen_spatial_convolutions_test.cc, we observe the following runtime numbers: AVX512: Parameters | Runtime without patch (ns) | Runtime with patch (ns) | Speedup ---------------------------------------------------------------|----------------------------|-------------------------|--------- BM_RHS_NAME(PackRhs, 128, 24, 24, 3, 64, 5, 5, 1, 1, 256, 56) | 41350 | 15073 | 2.74X BM_RHS_NAME(PackRhs, 32, 64, 64, 32, 64, 5, 5, 1, 1, 256, 56) | 7277 | 7341 | 0.99X BM_RHS_NAME(PackRhs, 32, 64, 64, 32, 64, 5, 5, 2, 2, 256, 56) | 8675 | 8681 | 1.00X BM_RHS_NAME(PackRhs, 32, 64, 64, 30, 64, 5, 5, 1, 1, 256, 56) | 24155 | 16079 | 1.50X BM_RHS_NAME(PackRhs, 32, 64, 64, 30, 64, 5, 5, 2, 2, 256, 56) | 25052 | 17152 | 1.46X BM_RHS_NAME(PackRhs, 32, 256, 256, 4, 16, 8, 8, 1, 1, 256, 56) | 18269 | 18345 | 1.00X BM_RHS_NAME(PackRhs, 32, 256, 256, 4, 16, 8, 8, 2, 4, 256, 56) | 19468 | 19872 | 0.98X BM_RHS_NAME(PackRhs, 32, 64, 64, 4, 16, 3, 3, 1, 1, 36, 432) | 156060 | 42432 | 3.68X BM_RHS_NAME(PackRhs, 32, 64, 64, 4, 16, 3, 3, 2, 2, 36, 432) | 132701 | 36944 | 3.59X AVX2: Parameters | Runtime without patch (ns) | Runtime with patch (ns) | Speedup ---------------------------------------------------------------|----------------------------|-------------------------|--------- BM_RHS_NAME(PackRhs, 128, 24, 24, 3, 64, 5, 5, 1, 1, 256, 56) | 26233 | 12393 | 2.12X BM_RHS_NAME(PackRhs, 32, 64, 64, 32, 64, 5, 5, 1, 1, 256, 56) | 6091 | 6062 | 1.00X BM_RHS_NAME(PackRhs, 32, 64, 64, 32, 64, 5, 5, 2, 2, 256, 56) | 7427 | 7408 | 1.00X BM_RHS_NAME(PackRhs, 32, 64, 64, 30, 64, 5, 5, 1, 1, 256, 56) | 23453 | 20826 | 1.13X BM_RHS_NAME(PackRhs, 32, 64, 64, 30, 64, 5, 5, 2, 2, 256, 56) | 23167 | 22091 | 1.09X BM_RHS_NAME(PackRhs, 32, 256, 256, 4, 16, 8, 8, 1, 1, 256, 56) | 23422 | 23682 | 0.99X BM_RHS_NAME(PackRhs, 32, 256, 256, 4, 16, 8, 8, 2, 4, 256, 56) | 23165 | 23663 | 0.98X BM_RHS_NAME(PackRhs, 32, 64, 64, 4, 16, 3, 3, 1, 1, 36, 432) | 72689 | 44969 | 1.62X BM_RHS_NAME(PackRhs, 32, 64, 64, 4, 16, 3, 3, 2, 2, 36, 432) | 61732 | 39779 | 1.55X All benchmarks on Intel Skylake server with 8 cores.
* fix unit test in c++03: c++03 does not allow passing local or anonymous enum ↵Gravatar Gael Guennebaud2019-03-18
| | | | as template param
* bug #1692: enable enum as sizes of Matrix and ArrayGravatar Gael Guennebaud2019-03-17
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* Remove undefined std::complex<int>Gravatar David Tellenbach2019-03-14
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* PR 593: Add variadtic ctor for DiagonalMatrix with unit testsGravatar David Tellenbach2019-03-14
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* revert debug stuffGravatar Gael Guennebaud2019-03-14
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* bug #1684: partially workaround clang's 6/7 bug #40815Gravatar Gael Guennebaud2019-03-13
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* Enable construction of Ref<VectorType> from a runtime vector.Gravatar Gael Guennebaud2019-03-03
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* bug #1684: add simplified regression test for respective clang's bug (this ↵Gravatar Gael Guennebaud2019-02-22
| | | | also reveal the same bug in Apples's clang)
* Add fully generic Vector<Type,Size> and RowVector<Type,Size> type aliases.Gravatar Gael Guennebaud2019-02-20
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* Protect c++11 type alias with Eigen's macro, and add respective unit test.Gravatar Gael Guennebaud2019-02-20
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* Fix compilation with gcc and remove TR1 stuff.Gravatar Gael Guennebaud2019-02-20
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* bug #1409: make EIGEN_MAKE_ALIGNED_OPERATOR_NEW* macros empty in c++17 mode:Gravatar Gael Guennebaud2019-02-20
| | | | | - this helps clang 5 and 6 to support alignas in STL's containers. - this makes the public API of our (and users) classes cleaner
* bug #899: make sparseqr unit test more stable by 1) trying with larger ↵Gravatar Gael Guennebaud2019-02-19
| | | | threshold and 2) relax rank computation for rank-deficient problems.
* Fix C++17 compilationGravatar Gael Guennebaud2019-02-19
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* fix unit compilation in c++17: std::ptr_fun has been removed.Gravatar Gael Guennebaud2019-02-19
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* bug #1046: add unit tests for correct propagation of alignment through ↵Gravatar Gael Guennebaud2019-02-19
| | | | std::alignment_of
* Add unit test for LinSpaced and complex numbers.Gravatar Gael Guennebaud2019-02-18
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* Fix regression: .conjugate() was popped out but not re-introduced.Gravatar Gael Guennebaud2019-02-18
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* Set cost of conjugate to 0 (in practice it boils down to a no-op).Gravatar Gael Guennebaud2019-02-18
| | | | | This is also important to make sure that A.conjugate() * B.conjugate() does not evaluate its arguments into temporaries (e.g., if A and B are fixed and small, or * fall back to lazyProduct)
* GEMM: catch all scalar-multiple variants when falling-back to a coeff-based ↵Gravatar Gael Guennebaud2019-02-18
| | | | | | | product. Before only s*A*B was caught which was both inconsistent with GEMM, sub-optimal, and could even lead to compilation-errors (https://stackoverflow.com/questions/54738495).
* Enable unit tests of PartialPivLU on fixed size matrices, and increase ↵Gravatar Gael Guennebaud2019-02-11
| | | | tested matrix size (blocking was not tested!)
* bug #1669: fix PartialPivLU/inverse with zero-sized matrices.Gravatar Gael Guennebaud2019-01-29
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* bug #1574: implement "sparse_matrix =,+=,-= diagonal_matrix" with smart ↵Gravatar Gael Guennebaud2019-01-28
| | | | insertion strategies of missing diagonal coeffs.
* bug #1672: fix unit test compilation with MSVC by adding overloads of ↵Gravatar Gael Guennebaud2019-01-28
| | | | test_is* for long long (and factorize copy/paste code through a macro)
* Avoid `I` as an identifier, since it may clash with the C-header complex.hGravatar Christoph Hertzberg2019-01-25
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* More thoroughly check variadic template ctor of fixed-size vectorsGravatar Gael Guennebaud2019-01-24
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* PR 572: Add initializer list constructors to Matrix and Array (include unit ↵Gravatar David Tellenbach2019-01-21
| | | | | | | | tests and doc) - {1,2,3,4,5,...} for fixed-size vectors only - {{1,2,3},{4,5,6}} for the general cases - {{1,2,3,4,5,....}} is allowed for both row and column-vector
* Add more extensive tests of Array ctors, including {} variantsGravatar Gael Guennebaud2019-01-22
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* Fix compilation of unit tests with gcc and c++17Gravatar Gael Guennebaud2019-01-18
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* After fixing bug #1557, boostmultiprec_7 failed with NumericalIssue instead ↵Gravatar Christoph Hertzberg2019-01-17
| | | | of NoConvergence (all that matters here is no Success)
* Make nestByValue works again (broken since 3.3) and add unit tests.Gravatar Gael Guennebaud2019-01-17
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* Extend reshaped unit tests and remove useless const_castGravatar Gael Guennebaud2019-01-17
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* Cleanup useless const_cast and add missing broadcast assignment testsGravatar Gael Guennebaud2019-01-17
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* Boosttest only available for Boost version >= 1.53.0Gravatar Patrick Peltzer2019-01-17
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