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4093 Commits

Author SHA1 Message Date
Rasmus Munk Larsen
988f24b730 Various fixes for packet ops. 
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.
 2019-06-20 11:47:49 -07:00
Christoph Hertzberg
e0be7f30e1 bug #1724: Mask buggy warnings with g++-7 
(grafted from 427f2f66d6
)
 2019-06-14 14:57:46 +02:00
Rasmus Munk Larsen
6d432eae5d Make is_valid_index_type return false for float and double when EIGEN_HAS_TYPE_TRAITS is off. 2019-06-05 16:42:27 -07:00
Rasmus Munk Larsen
f715f6e816 Add workaround for choosing the right include files with FP16C support with clang. 2019-06-05 13:36:37 -07:00
Rasmus Munk Larsen
b08527b0c1 Clean up CUDA/NVCC version macros and their use in Eigen, and a few other CUDA build failures. 2019-05-31 15:26:06 -07:00
Deven Desai
2c38930161 fix for HIP build errors that were introduced by a commit earlier this week 2019-05-24 14:25:32 +00:00
Gustavo Lima Chaves
56bc4974fb GEMV: remove double declaration of constant. 
That was hurting users with compilers that would object to proceed with
that:

"""
./Eigen/src/Core/products/GeneralMatrixVector.h:356:10: error: declaration shadows a static data member of 'general_matrix_vector_product<type-parameter-0-0, type-parameter-0-1, type-parameter-0-2, 1, ConjugateLhs, type-parameter-0-4, type-parameter-0-5, ConjugateRhs, Version>' [-Werror,-Wshadow]
         LhsPacketSize = Traits::LhsPacketSize,
         ^
./Eigen/src/Core/products/GeneralMatrixVector.h:307:22: note: previous declaration is here
  static const Index LhsPacketSize = Traits::LhsPacketSize;
"""
 2019-05-23 14:50:29 -07:00
Rasmus Munk Larsen
3eb5ad0ed0 Enable support for F16C with Clang. The required intrinsics were added here: https://reviews.llvm.org/D16177 
and are part of LLVM 3.8.0.
 2019-05-20 17:19:20 -07:00
Rasmus Larsen
e92486b8c3 Merged in rmlarsen/eigen (pull request PR-643) 
Make Eigen build with cuda 10 and clang.

Approved-by: Justin Lebar <justin.lebar@gmail.com>
 2019-05-20 17:02:39 +00:00
Gael Guennebaud
cc7ecbb124 Merged in scramsby/eigen (pull request PR-646) 
Eigen: Fix MSVC C++17 language standard detection logic
 2019-05-20 07:19:10 +00:00
Rasmus Larsen
bf9cbed8d0 Merged in glchaves/eigen (pull request PR-635) 
Speed up GEMV on AVX-512 builds, just as done for GEBP previously.

Approved-by: Rasmus Larsen <rmlarsen@google.com>
 2019-05-17 19:40:50 +00:00
Rasmus Munk Larsen
ab0a30e429 Make Eigen build with cuda 10 and clang. 2019-05-15 13:32:15 -07:00
Anuj Rawat
ad372084f5 Removing unused API to fix compile error in TensorFlow due to 
AVX512VL, AVX512BW usage
 2019-05-12 14:43:10 +00:00
Christoph Hertzberg
4ccd1ece92 bug #1707: Fix deprecation warnings, or disable warnings when testing deprecated functions 2019-05-10 14:57:05 +02:00
Rasmus Munk Larsen
d3ef7cf03e Fix build with clang on Windows. 2019-05-09 11:07:04 -07:00
Eugene Zhulenev
45b40d91ca Fix AVX512 & GCC 6.3 compilation 2019-05-07 16:44:55 -07:00
Christoph Hertzberg
cca76c272c Restore C++03 compatibility 2019-05-06 16:18:22 +02:00
Rasmus Munk Larsen
8e33844fc7 Fix traits for scalar_logistic_op. 2019-05-03 15:49:09 -07:00
Scott Ramsby
ff06ef7584 Eigen: Fix MSVC C++17 language standard detection logic 
To detect C++17 support, use _MSVC_LANG macro instead of _MSC_VER. _MSC_VER can indicate whether the current compiler version could support the C++17 language standard, but not whether that standard is actually selected (i.e. via /std:c++17).
See these web pages for more details:
https://devblogs.microsoft.com/cppblog/msvc-now-correctly-reports-__cplusplus/
https://docs.microsoft.com/en-us/cpp/preprocessor/predefined-macros
 2019-05-03 14:14:09 -07:00
Eugene Zhulenev
e9f0eb8a5e Add masked_store_available to unpacket_traits 2019-05-02 14:52:58 -07:00
Eugene Zhulenev
96e30e936a Add masked pstoreu for Packet16h 2019-05-02 14:11:01 -07:00
Eugene Zhulenev
b4010f02f9 Add masked pstoreu to AVX and AVX512 PacketMath 2019-05-02 13:14:18 -07:00
Gael Guennebaud
578407f42f Fix regression in changeset ae33e866c7 2019-05-02 15:45:21 +02:00
Gustavo Lima Chaves
d4dcb71bcb Speed up GEMV on AVX-512 builds, just as done for GEBP previously. 
We take advantage of smaller SIMD registers as well, in that case.

Gains up to 3x for select input sizes.
 2019-04-26 14:12:39 -07:00
Andy May
ae33e866c7 Fix compilation with PGI version 19 2019-04-25 21:23:19 +01:00
Gael Guennebaud
665ac22cc6 Merged in ezhulenev/eigen-01 (pull request PR-632) 
Fix doxygen warnings
 2019-04-25 20:02:20 +00:00
Eugene Zhulenev
8ead5bb3d8 Fix doxygen warnings to enable statis code analysis 2019-04-24 12:42:28 -07:00
Eugene Zhulenev
07355d47c6 Get rid of SequentialLinSpacedReturnType deprecation warnings in DenseBase.h 2019-04-24 11:01:35 -07:00
Rasmus Munk Larsen
144ca33321 Remove deprecation annotation from typedef Eigen::Index Index, as it would generate too many build warnings. 2019-04-24 08:50:07 -07:00
Eugene Zhulenev
a7b7f3ca8a Add missing EIGEN_DEPRECATED annotations to deprecated functions and fix few other doxygen warnings 2019-04-23 17:23:19 -07:00
Eugene Zhulenev
68a2a8c445 Use packet ops instead of AVX2 intrinsics 2019-04-23 11:41:02 -07:00
Anuj Rawat
8c7a6feb8e Adding lowlevel APIs for optimized RHS packet load in TensorFlow 
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.
 2019-04-20 06:46:43 +00:00
William D. Irons
8de66719f9 Collapsed revision from PR-619 
* Add support for pcmp_eq in AltiVec/Complex.h
* Fixed implementation of pcmp_eq for double

The new logic is based on the logic from NEON for double.
 2019-03-26 18:14:49 +00:00
Gael Guennebaud
f11364290e ICC does not support -fno-unsafe-math-optimizations 2019-03-22 09:26:24 +01:00
David Tellenbach
3031d57200 PR 621: Fix documentation of EIGEN_COMP_EMSCRIPTEN 2019-03-21 02:21:04 +01:00
Deven Desai
51e399fc15 updates requested in the PR feedback. Also droping coded within #ifdef EIGEN_HAS_OLD_HIP_FP16 2019-03-19 21:45:25 +00:00
Deven Desai
2dbea5510f Merged eigen/eigen into default 2019-03-19 16:52:38 -04:00
Rasmus Larsen
5c93b38c5f Merged in rmlarsen/eigen (pull request PR-618) 
Make clipping outside [-18:18] consistent for vectorized and non-vectorized paths of scalar_logistic_op<float>.

Approved-by: Gael Guennebaud <g.gael@free.fr>
 2019-03-18 15:51:55 +00:00
Gael Guennebaud
cf7e2e277f bug #1692: enable enum as sizes of Matrix and Array 2019-03-17 21:59:30 +01:00
Rasmus Munk Larsen
e42f9aa68a Make clipping outside [-18:18] consistent for vectorized and non-vectorized paths of scalar_logistic_<float>. 2019-03-15 17:15:14 -07:00
Rasmus Munk Larsen
8450a6d519 Clean up half packet traits and add a few more missing packet ops. 2019-03-14 15:18:06 -07:00
David Tellenbach
97f9a46cb9 PR 593: Add variadtic ctor for DiagonalMatrix with unit tests 2019-03-14 10:18:24 +01:00
Gael Guennebaud
d7d2f0680e bug #1684: partially workaround clang's 6/7 bug #40815 2019-03-13 10:40:01 +01:00
Rasmus Munk Larsen
77f7d4a894 Clean up PacketMathHalf.h and add a few missing logical packet ops. 2019-03-11 17:51:16 -07:00
Gael Guennebaud
656d9bc66b Apply SSE's pmin/pmax fix for GCC <= 5 to AVX's pmin/pmax 2019-03-10 21:19:18 +01:00
Gael Guennebaud
bfbf7da047 bug #1689 fix used-but-marked-unused warning 2019-03-05 23:46:24 +01:00
Gael Guennebaud
b0d406d91c Enable construction of Ref<VectorType> from a runtime vector. 2019-03-03 15:25:25 +01:00
Sam Hasinoff
9ba81cf0ff Fully qualify Eigen::internal::aligned_free 
This helps avoids a conflict on certain Windows toolchains
(potentially due to some ADL name resolution bug) in the case
where aligned_free is defined in the global namespace. In any
case, tightening this up is harmless.
 2019-03-02 17:42:16 +00:00
Gael Guennebaud
0b25a5c431 fix alignment in ploadquad 2019-02-22 21:39:36 +01:00
Gael Guennebaud
cca6c207f4 AVX512: implement faster ploadquad<Packet16f> thus speeding up GEMM 2019-02-21 17:18:28 +01:00