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* STYLE: Remove CMake-language block-end command argumentsGravatar Hans Johnson2019-10-31
| | | | | | Ancient versions of CMake required else(), endif(), and similar block termination commands to have arguments matching the command starting the block. This is no longer the preferred style.
* 1. Fix a bug in psqrt and make it return 0 for +inf arguments.Gravatar Rasmus Munk Larsen2019-11-15
| | | | | | | | | | | | | | | | 2. Simplify handling of special cases by taking advantage of the fact that the builtin vrsqrt approximation handles negative, zero and +inf arguments correctly. This speeds up the SSE and AVX implementations by ~20%. 3. Make the Newton-Raphson formula used for rsqrt more numerically robust: Before: y = y * (1.5 - x/2 * y^2) After: y = y * (1.5 - y * (x/2) * y) Forming y^2 can overflow for very large or very small (denormalized) values of x, while x*y ~= 1. For AVX512, this makes it possible to compute accurate results for denormal inputs down to ~1e-42 in single precision. 4. Add a faster double precision implementation for Knights Landing using the vrsqrt28 instruction and a single Newton-Raphson iteration. Benchmark results: https://bitbucket.org/snippets/rmlarsen/5LBq9o
* bug #1744: fix compilation with MSVC 2017 and AVX512, plog1p/pexpm1 require ↵Gravatar Gael Guennebaud2019-11-15
| | | | plog/pexp, but the later was disabled on some compilers
* bug #1774: fix VectorwiseOp::begin()/end() return types regarding constness.Gravatar Gael Guennebaud2019-11-14
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* PR 751: Fixed compilation issue when compiling using MSVC with /arch:AVX512 flagGravatar Sakshi Goynar2019-10-31
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* Enable CompleteOrthogonalDecomposition::pseudoInverse with non-square ↵Gravatar Gael Guennebaud2019-11-13
| | | | fixed-size matrices.
* Disable AVX on broken xcode versions. See PR 748.Gravatar Gael Guennebaud2019-11-12
| | | | Patch adapted from Hans Johnson's PR 748.
* Add EIGEN_HAS_INTRINSIC_INT128 macroGravatar Rasmus Munk Larsen2019-11-06
| | | | Add a new EIGEN_HAS_INTRINSIC_INT128 macro, and use this instead of __SIZEOF_INT128__. This fixes related issues with TensorIntDiv.h when building with Clang for Windows, where support for 128-bit integer arithmetic is advertised but broken in practice.
* Rollback or PR-746 and partial rollback of ↵Gravatar Rasmus Munk Larsen2019-11-05
| | | | | | | | https://bitbucket.org/eigen/eigen/commits/668ab3fc474e54c7919eda4fbaf11f3a99246494 . std::array is still not supported in CUDA device code on Windows.
* Remove internal::smart_copy and replace with std::copyGravatar Eugene Zhulenev2019-10-29
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* bug #1752: make is_convertible equivalent to the std c++11 equivalent and ↵Gravatar Gael Guennebaud2019-10-10
| | | | fallback to std::is_convertible when c++11 is enabled.
* Explicitly bypass resize and memmoves when there is already the exact right ↵Gravatar Gael Guennebaud2019-10-08
| | | | number of elements available.
* fix one more possible conflicts with real/imagGravatar Gael Guennebaud2019-10-08
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* PR 719: fix real/imag namespace conflictGravatar Gael Guennebaud2019-10-08
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* Address comments on Chebyshev evaluation code:Gravatar Rasmus Munk Larsen2019-10-02
| | | | | 1. Use pmadd when possible. 2. Add casts to avoid c++03 warnings.
* Prevent infinite loop in the nvcc compiler while unrolling the recurrent ↵Gravatar Rasmus Munk Larsen2019-10-01
| | | | templates for Chebyshev polynomial evaluation.
* Fix perf issue in SimplicialLDLT::solve for complexes (again, m_diag is real)Gravatar Gael Guennebaud2019-10-01
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* Fix speed issue with SimplicialLDLT for complexes: the diagonal is real!Gravatar Gael Guennebaud2019-09-30
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* Move implementation of vectorized error function erf() to ↵Gravatar Rasmus Munk Larsen2019-09-27
| | | | SpecialFunctionsImpl.h.
* Fix erf in c++03Gravatar Eugene Zhulenev2019-09-25
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* Fix for the HIP build+test errors.Gravatar Deven Desai2019-09-25
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | The errors were introduced by this commit : https://bitbucket.org/eigen/eigen/commits/d38e6fbc27abe0c354ffe90928f6741c378e76e1 After the above mentioned commit, some of the tests started failing with the following error ``` Building HIPCC object unsupported/test/CMakeFiles/cxx11_tensor_reduction_gpu_5.dir/cxx11_tensor_reduction_gpu_5_generated_cxx11_tensor_reduction_gpu.cu.o In file included from /home/rocm-user/eigen/unsupported/test/cxx11_tensor_reduction_gpu.cu:16: In file included from /home/rocm-user/eigen/unsupported/Eigen/CXX11/Tensor:29: In file included from /home/rocm-user/eigen/unsupported/Eigen/CXX11/../SpecialFunctions:70: /home/rocm-user/eigen/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsHalf.h:28:22: error: call to 'erf' is ambiguous return Eigen::half(Eigen::numext::erf(static_cast<float>(a))); ^~~~~~~~~~~~~~~~~~ /home/rocm-user/eigen/unsupported/test/../../Eigen/src/Core/MathFunctions.h:1600:7: note: candidate function [with T = float] float erf(const float &x) { return ::erff(x); } ^ /home/rocm-user/eigen/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h:1897:5: note: candidate function [with Scalar = float] erf(const Scalar& x) { ^ In file included from /home/rocm-user/eigen/unsupported/test/cxx11_tensor_reduction_gpu.cu:16: In file included from /home/rocm-user/eigen/unsupported/Eigen/CXX11/Tensor:29: In file included from /home/rocm-user/eigen/unsupported/Eigen/CXX11/../SpecialFunctions:75: /home/rocm-user/eigen/unsupported/Eigen/CXX11/../src/SpecialFunctions/arch/GPU/GpuSpecialFunctions.h:87:23: error: call to 'erf' is ambiguous return make_double2(erf(a.x), erf(a.y)); ^~~ /home/rocm-user/eigen/unsupported/test/../../Eigen/src/Core/MathFunctions.h:1603:8: note: candidate function [with T = double] double erf(const double &x) { return ::erf(x); } ^ /home/rocm-user/eigen/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h:1897:5: note: candidate function [with Scalar = double] erf(const Scalar& x) { ^ In file included from /home/rocm-user/eigen/unsupported/test/cxx11_tensor_reduction_gpu.cu:16: In file included from /home/rocm-user/eigen/unsupported/Eigen/CXX11/Tensor:29: In file included from /home/rocm-user/eigen/unsupported/Eigen/CXX11/../SpecialFunctions:75: /home/rocm-user/eigen/unsupported/Eigen/CXX11/../src/SpecialFunctions/arch/GPU/GpuSpecialFunctions.h:87:33: error: call to 'erf' is ambiguous return make_double2(erf(a.x), erf(a.y)); ^~~ /home/rocm-user/eigen/unsupported/test/../../Eigen/src/Core/MathFunctions.h:1603:8: note: candidate function [with T = double] double erf(const double &x) { return ::erf(x); } ^ /home/rocm-user/eigen/unsupported/Eigen/CXX11/../src/SpecialFunctions/SpecialFunctionsImpl.h:1897:5: note: candidate function [with Scalar = double] erf(const Scalar& x) { ^ 3 errors generated. ``` This PR fixes the compile error by removing the "old" implementation for "erf" (assuming that the "new" implementation is what we want going forward. from a GPU point-of-view both implementations are the same). This PR also fixes what seems like a cut-n-paste error in the aforementioned commit
* Merged in rmlarsen/eigen (pull request PR-704)Gravatar Rasmus Larsen2019-09-24
|\ | | | | | | Add generic PacketMath implementation of the Error Function (erf).
* | Tensor block evaluation V2 support for unary/binary/broadcstingGravatar Eugene Zhulenev2019-09-24
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* | bug #1746: Removed implementation of standard copy-constructor and standard ↵Gravatar Christoph Hertzberg2019-09-24
| | | | | | | | copy-assign-operator from PermutationMatrix and Transpositions to allow malloc-less std::move. Added unit-test to rvalue_types
| * Add generic PacketMath implementation of the Error Function (erf).Gravatar Rasmus Munk Larsen2019-09-19
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* | Fix build on setups without AVX512DQ.Gravatar Rasmus Munk Larsen2019-09-19
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* Fix for the HIP build+test errors.Gravatar Deven Desai2019-09-18
| | | | | | | The errors were introduced by this commit : https://bitbucket.org/eigen/eigen/commits/6e215cf109073da9ffb5b491171613b8db24fd9d The fix is switching to using ::<math_func> instead std::<math_func> when compiling for GPU
* Add Bessel functions to SpecialFunctions.Gravatar Srinivas Vasudevan2019-09-14
| | | | | | | | | - Split SpecialFunctions files in to a separate BesselFunctions file. In particular add: - Modified bessel functions of the second kind k0, k1, k0e, k1e - Bessel functions of the first kind j0, j1 - Bessel functions of the second kind y0, y1
* Add packetized versions of i0e and i1e special functions.Gravatar Srinivas Vasudevan2019-09-11
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - In particular refactor the i0e and i1e code so scalar and vectorized path share code. - Move chebevl to GenericPacketMathFunctions. A brief benchmark with building Eigen with FMA, AVX and AVX2 flags Before: CPU: Intel Haswell with HyperThreading (6 cores) Benchmark Time(ns) CPU(ns) Iterations ----------------------------------------------------------------- BM_eigen_i0e_double/1 57.3 57.3 10000000 BM_eigen_i0e_double/8 398 398 1748554 BM_eigen_i0e_double/64 3184 3184 218961 BM_eigen_i0e_double/512 25579 25579 27330 BM_eigen_i0e_double/4k 205043 205042 3418 BM_eigen_i0e_double/32k 1646038 1646176 422 BM_eigen_i0e_double/256k 13180959 13182613 53 BM_eigen_i0e_double/1M 52684617 52706132 10 BM_eigen_i0e_float/1 28.4 28.4 24636711 BM_eigen_i0e_float/8 75.7 75.7 9207634 BM_eigen_i0e_float/64 512 512 1000000 BM_eigen_i0e_float/512 4194 4194 166359 BM_eigen_i0e_float/4k 32756 32761 21373 BM_eigen_i0e_float/32k 261133 261153 2678 BM_eigen_i0e_float/256k 2087938 2088231 333 BM_eigen_i0e_float/1M 8380409 8381234 84 BM_eigen_i1e_double/1 56.3 56.3 10000000 BM_eigen_i1e_double/8 397 397 1772376 BM_eigen_i1e_double/64 3114 3115 223881 BM_eigen_i1e_double/512 25358 25361 27761 BM_eigen_i1e_double/4k 203543 203593 3462 BM_eigen_i1e_double/32k 1613649 1613803 428 BM_eigen_i1e_double/256k 12910625 12910374 54 BM_eigen_i1e_double/1M 51723824 51723991 10 BM_eigen_i1e_float/1 28.3 28.3 24683049 BM_eigen_i1e_float/8 74.8 74.9 9366216 BM_eigen_i1e_float/64 505 505 1000000 BM_eigen_i1e_float/512 4068 4068 171690 BM_eigen_i1e_float/4k 31803 31806 21948 BM_eigen_i1e_float/32k 253637 253692 2763 BM_eigen_i1e_float/256k 2019711 2019918 346 BM_eigen_i1e_float/1M 8238681 8238713 86 After: CPU: Intel Haswell with HyperThreading (6 cores) Benchmark Time(ns) CPU(ns) Iterations ----------------------------------------------------------------- BM_eigen_i0e_double/1 15.8 15.8 44097476 BM_eigen_i0e_double/8 99.3 99.3 7014884 BM_eigen_i0e_double/64 777 777 886612 BM_eigen_i0e_double/512 6180 6181 100000 BM_eigen_i0e_double/4k 48136 48140 14678 BM_eigen_i0e_double/32k 385936 385943 1801 BM_eigen_i0e_double/256k 3293324 3293551 228 BM_eigen_i0e_double/1M 12423600 12424458 57 BM_eigen_i0e_float/1 16.3 16.3 43038042 BM_eigen_i0e_float/8 30.1 30.1 23456931 BM_eigen_i0e_float/64 169 169 4132875 BM_eigen_i0e_float/512 1338 1339 516860 BM_eigen_i0e_float/4k 10191 10191 68513 BM_eigen_i0e_float/32k 81338 81337 8531 BM_eigen_i0e_float/256k 651807 651984 1000 BM_eigen_i0e_float/1M 2633821 2634187 268 BM_eigen_i1e_double/1 16.2 16.2 42352499 BM_eigen_i1e_double/8 110 110 6316524 BM_eigen_i1e_double/64 822 822 851065 BM_eigen_i1e_double/512 6480 6481 100000 BM_eigen_i1e_double/4k 51843 51843 10000 BM_eigen_i1e_double/32k 414854 414852 1680 BM_eigen_i1e_double/256k 3320001 3320568 212 BM_eigen_i1e_double/1M 13442795 13442391 53 BM_eigen_i1e_float/1 17.6 17.6 41025735 BM_eigen_i1e_float/8 35.5 35.5 19597891 BM_eigen_i1e_float/64 240 240 2924237 BM_eigen_i1e_float/512 1424 1424 485953 BM_eigen_i1e_float/4k 10722 10723 65162 BM_eigen_i1e_float/32k 86286 86297 8048 BM_eigen_i1e_float/256k 691821 691868 1000 BM_eigen_i1e_float/1M 2777336 2777747 256 This shows anywhere from a 50% to 75% improvement on these operations. I've also benchmarked without any of these flags turned on, and got similar performance to before (if not better). Also tested packetmath.cpp + special_functions to ensure no regressions.
* Merged eigen/eigen into defaultGravatar Srinivas Vasudevan2019-09-11
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| * Fix for the HIP build+test errors introduced by the ndtri support.Gravatar Deven Desai2019-09-06
| | | | | | | | | | | | | | The fixes needed are * adding EIGEN_DEVICE_FUNC attribute to a couple of funcs (else HIPCC will error out when non-device funcs are called from global/device funcs) * switching to using ::<math_func> instead std::<math_func> (only for HIPCC) in cases where the std::<math_func> is not recognized as a device func by HIPCC * removing an errant "j" from a testcase (don't know how that made it in to begin with!)
| * bug #1736: fix compilation issue with A(all,{1,2}).col(j) by implementing ↵Gravatar Gael Guennebaud2019-09-11
| | | | | | | | true compile-time "if" for block_evaluator<>::coeff(i)/coeffRef(i)
| * bug #1741: fix self-adjoint*matrix, triangular*matrix, and ↵Gravatar Gael Guennebaud2019-09-11
| | | | | | | | triangular^1*matrix with a destination having a non-trivial inner-stride
| * Fix compilation of BLAS backend and frontendGravatar Gael Guennebaud2019-09-11
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| * Fix some implicit literal to Scalar conversions in SparseCoreGravatar Gael Guennebaud2019-09-11
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| * bug #1741: fix SelfAdjointView::rankUpdate and product to triangular part ↵Gravatar Gael Guennebaud2019-09-10
| | | | | | | | for destination with non-trivial inner stride
| * bug #1741: fix C.noalias() = A*C; with C.innerStride()!=1Gravatar Gael Guennebaud2019-09-10
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| * Fix a circular dependency regarding pshift* functions and ↵Gravatar Gael Guennebaud2019-09-06
| | | | | | | | | | | | | | GenericPacketMathFunctions. Another solution would have been to make pshift* fully generic template functions with partial specialization which is always a mess in c++03.
| * Fix compilation without vector engine available (e.g., x86 with SSE disabled):Gravatar Gael Guennebaud2019-09-05
| | | | | | | | -> ppolevl is required by ndtri even for the scalar path
* | Merged eigen/eigenGravatar Srinivas Vasudevan2019-09-04
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* \ \ Merging from eigen/eigen.Gravatar Srinivas Vasudevan2019-09-03
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* | | | Add ndtri function, the inverse of the normal distribution function.Gravatar Srinivas Vasudevan2019-08-12
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| | | * PR 621: Fix documentation of EIGEN_COMP_EMSCRIPTENGravatar David Tellenbach2019-03-21
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| | * Fix doc issues regarding ndtriGravatar Gael Guennebaud2019-09-04
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| | * Fix possible warning regarding strict equality comparisonsGravatar Gael Guennebaud2019-09-04
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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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| | * Change typedefs from private to protected to fix MSVC compilationGravatar Eugene Zhulenev2019-09-03
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| * Makes Scalar/RealScalar typedefs public in Pardiso's wrappers (see PR 688)Gravatar Gael Guennebaud2019-09-03
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| * More colamd cleanup:Gravatar Gael Guennebaud2019-09-03
| | | | | | | | | | | | - Move colamd implementation in its own namespace to avoid polluting the internal namespace with Ok, Status, etc. - Fix signed/unsigned warning - move some ugly free functions as member functions
| * Eigen_Colamd.h updated to replace constexpr with consts and enums.Gravatar Anshul Jaiswal2019-08-17
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