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Author SHA1 Message Date
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
Gael Guennebaud
45e65fbb77 bug #1695: fix a numerical robustness issue. Computing the secular equation at the middle range without a shift might give a wrong sign. 2019-03-27 20:16:58 +01:00
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
Rasmus Munk Larsen
6a34003141 Remove EIGEN_MPL2_ONLY guard in IncompleteCholesky that is no longer needed after the AMD reordering code was relicensed to MPL2. 2019-03-13 11:52:41 -07:00
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
Rasmus Larsen
4d808e834a Merged in rmlarsen/eigen_threadpool (pull request PR-606) 
Remove EIGEN_MPL2_ONLY guards around code re-licensed from LGPL to MPL2 in 2ca1e73239


Approved-by: Sameer Agarwal <sameeragarwal@google.com>
 2019-03-06 17:59:03 +00:00
Gael Guennebaud
bfbf7da047 bug #1689 fix used-but-marked-unused warning 2019-03-05 23:46:24 +01:00
Rasmus Munk Larsen
0318fc7f44 Remove EIGEN_MPL2_ONLY guards around code re-licensed from LGPL to MPL2 in 2ca1e73239 2019-03-05 10:24:54 -08:00
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
22144e949d bug #1629: fix compilation of PardisoSupport (regression introduced in changeset a7842daef2 
)
 2019-03-02 22:44:47 +01:00
Rasmus Larsen
2ca1e73239 Merged in rmlarsen/eigen (pull request PR-597) 
Change licensing of OrderingMethods/Amd.h and SparseCholesky/SimplicialCholesky_impl.h from LGPL to MPL2.

Approved-by: Gael Guennebaud <g.gael@free.fr>
 2019-02-25 17:02:16 +00:00
Gael Guennebaud
e409dbba14 Enable SSE vectorization of Quaternion and cross3() with AVX 2019-02-23 10:45:40 +01:00
Gael Guennebaud
0b25a5c431 fix alignment in ploadquad 2019-02-22 21:39:36 +01:00
Rasmus Munk Larsen
1dc1677d52 Change licensing of OrderingMethods/Amd.h and SparseCholesky/SimplicialCholesky_impl.h from LGPL to MPL2. Google LLC executed a license agreement with the author of the code from which these files are derived to allow the Eigen project to distribute the code and derived works under MPL2. 2019-02-22 12:33:57 -08:00
Gael Guennebaud
cca6c207f4 AVX512: implement faster ploadquad<Packet16f> thus speeding up GEMM 2019-02-21 17:18:28 +01:00
Gael Guennebaud
1c09ee8541 bug #1674: workaround clang fast-math aggressive optimizations 2019-02-22 15:48:53 +01:00
Gael Guennebaud
7e3084bb6f Fix compilation on ARM. 2019-02-22 14:56:12 +01:00
Gael Guennebaud
42c23f14ac Speed up col/row-wise reverse for fixed size matrices by propagating compile-time sizes. 2019-02-21 22:44:40 +01:00
Rasmus Munk Larsen
4d7f317102 Add a few missing packet ops: cmp_eq for NEON. pfloor for GPU. 2019-02-21 13:32:13 -08:00
Gael Guennebaud
2a39659d79 Add fully generic Vector<Type,Size> and RowVector<Type,Size> type aliases. 2019-02-20 15:23:23 +01:00
Gael Guennebaud
302377110a Update documentation of Matrix and Array type aliases. 2019-02-20 15:18:48 +01:00
Gael Guennebaud
44b54fa4a3 Protect c++11 type alias with Eigen's macro, and add respective unit test. 2019-02-20 14:43:05 +01:00
Gael Guennebaud
7195f008ce Merged in ra_bauke/eigen (pull request PR-180) 
alias template for matrix and array classes, see also bug #864

Approved-by: Heiko Bauke <heiko.bauke@mail.de>
 2019-02-20 13:22:39 +00:00
Gael Guennebaud
edd413c184 bug #1409: make EIGEN_MAKE_ALIGNED_OPERATOR_NEW* macros empty in c++17 mode: 
- this helps clang 5 and 6 to support alignas in STL's containers.
 - this makes the public API of our (and users) classes cleaner
 2019-02-20 13:52:11 +01:00
Gael Guennebaud
482c5fb321 bug #899: remove "rank-revealing" qualifier for SparseQR and warn that it is not always rank-revealing. 2019-02-19 22:52:15 +01:00
Christoph Hertzberg
a1646fc960 Commas at the end of enumerator lists are not allowed in C++03 2019-02-19 14:32:25 +01:00
Gael Guennebaud
ab78cabd39 Add C++17 detection macro, and make sure throw(xpr) is not used if the compiler is in c++17 mode. 2019-02-19 14:04:35 +01:00
Gael Guennebaud
115da6a1ea Fix conversion warnings 2019-02-19 14:00:15 +01:00
Gael Guennebaud
7580112c31 Fix harmless Scalar vs RealScalar cast. 2019-02-18 22:12:28 +01:00
Gael Guennebaud
796db94e6e bug #1194: implement slightly faster and SIMD friendly 4x4 determinant. 2019-02-18 16:21:27 +01:00
Gael Guennebaud
31b6e080a9 Fix regression: .conjugate() was popped out but not re-introduced. 2019-02-18 14:45:55 +01:00
Gael Guennebaud
c69d0d08d0 Set cost of conjugate to 0 (in practice it boils down to a no-op). 
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)
 2019-02-18 14:43:07 +01:00
Gael Guennebaud
512b74aaa1 GEMM: catch all scalar-multiple variants when falling-back to a coeff-based 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).
 2019-02-18 11:47:54 +01:00
Christoph Hertzberg
ec032ac03b Guard C++11-style default constructor. Also, this is only needed for MSVC 2019-02-16 09:44:05 +01:00
Gael Guennebaud
83309068b4 bug #1680: improve MSVC inlining by declaring many triavial constructors and accessors as STRONG_INLINE. 2019-02-15 16:35:35 +01:00
Gael Guennebaud
0505248f25 bug #1680: make all "block" methods strong-inline and device-functions (some were missing EIGEN_DEVICE_FUNC) 2019-02-15 16:33:56 +01:00
Gael Guennebaud
559320745e bug #1678: Fix lack of __FMA__ macro on MSVC with AVX512 2019-02-15 10:30:28 +01:00
Gael Guennebaud
d85ae650bf bug #1678: workaround MSVC compilation issues with AVX512 2019-02-15 10:24:17 +01:00
Gael Guennebaud
f2970819a2 bug #1679: avoid possible division by 0 in complex-schur 2019-02-15 09:39:25 +01:00
Rasmus Munk Larsen
65e23ca7e9 Revert b55b5c7280 
.
 2019-02-14 13:46:13 -08:00
Gael Guennebaud
bdcb5f3304 Let's properly use Score instead of std::abs, and remove deprecated FIXME ( a /= b does a/b and not a * (1/b) as it was a long time ago...) 2019-02-11 22:56:19 +01:00
Gael Guennebaud
2edfc6807d Fix compilation of empty products of the form: Mx0 * 0xN 2019-02-11 18:24:07 +01:00
Gael Guennebaud
eb46f34a8c Speed up 2x2 LU by a factor 2, and other small fixed sizes by about 10%. 
Not sure that's so critical, but this does not complexify the code base much.
 2019-02-11 17:59:35 +01:00
Gael Guennebaud
ab6e6edc32 Speedup PartialPivLU for small matrices by passing compile-time sizes when available. 
This change set also makes a better use of Map<>+OuterStride and Ref<> yielding surprising speed up for small dynamic sizes as well.
The table below reports times in micro seconds for 10 random matrices:
           | ------ float --------- | ------- double ------- |
     size  | before   after  ratio  |  before   after  ratio |
fixed	  1	 | 0.34     0.11   2.93   |  0.35     0.11   3.06  |
fixed	  2	 | 0.81     0.24   3.38   |  0.91     0.25   3.60  |
fixed	  3	 | 1.49     0.49   3.04   |  1.68     0.55   3.01  |
fixed	  4	 | 2.31     0.70   3.28   |  2.45     1.08   2.27  |
fixed	  5	 | 3.49     1.11   3.13   |  3.84     2.24   1.71  |
fixed	  6	 | 4.76     1.64   2.88   |  4.87     2.84   1.71  |
dyn     1	 | 0.50     0.40   1.23   |  0.51     0.40   1.26  |
dyn     2	 | 1.08     0.85   1.27   |  1.04     0.69   1.49  |
dyn     3	 | 1.76     1.26   1.40   |  1.84     1.14   1.60  |
dyn     4	 | 2.57     1.75   1.46   |  2.67     1.66   1.60  |
dyn     5	 | 3.80     2.64   1.43   |  4.00     2.48   1.61  |
dyn     6	 | 5.06     3.43   1.47   |  5.15     3.21   1.60  |
 2019-02-11 13:58:24 +01:00
Gael Guennebaud
013cc3a6b3 Make GEMM fallback to GEMV for runtime vectors. 
This is a more general and simpler version of changeset 4c0fa6ce0f
 2019-02-07 16:24:09 +01:00
Gael Guennebaud
fa2fcb4895 Backed out changeset 4c0fa6ce0f 2019-02-07 16:07:08 +01:00
Gael Guennebaud
b3c4344a68 bug #1676: workaround GCC's bug in c++17 mode. 2019-02-07 15:21:35 +01:00
Eugene Zhulenev
6d0f6265a9 Remove duplicated comment line 2019-02-04 10:30:25 -08:00
Eugene Zhulenev
690b2c45b1 Fix GeneralBlockPanelKernel Android compilation 2019-02-04 10:29:15 -08:00
Gael Guennebaud
871e2e5339 bug #1674: disable GCC's unsafe-math-optimizations in sin/cos vectorization (results are completely wrong otherwise) 2019-02-03 08:54:47 +01:00
Rasmus Larsen
e7b481ea74 Merged in rmlarsen/eigen (pull request PR-578) 
Speed up Eigen matrix*vector and vector*matrix multiplication.

Approved-by: Eugene Zhulenev <ezhulenev@google.com>
 2019-02-02 01:53:44 +00:00
Sameer Agarwal
b55b5c7280 Speed up row-major matrix-vector product on ARM 
The row-major matrix-vector multiplication code uses a threshold to
check if processing 8 rows at a time would thrash the cache.

This change introduces two modifications to this logic.

1. A smaller threshold for ARM and ARM64 devices.

The value of this threshold was determined empirically using a Pixel2
phone, by benchmarking a large number of matrix-vector products in the
range [1..4096]x[1..4096] and measuring performance separately on
small and little cores with frequency pinning.

On big (out-of-order) cores, this change has little to no impact. But
on the small (in-order) cores, the matrix-vector products are up to
700% faster. Especially on large matrices.

The motivation for this change was some internal code at Google which
was using hand-written NEON for implementing similar functionality,
processing the matrix one row at a time, which exhibited substantially
better performance than Eigen.

With the current change, Eigen handily beats that code.

2. Make the logic for choosing number of simultaneous rows apply
unifiormly to 8, 4 and 2 rows instead of just 8 rows.

Since the default threshold for non-ARM devices is essentially
unchanged (32000 -> 32 * 1024), this change has no impact on non-ARM
performance. This was verified by running the same set of benchmarks
on a Xeon desktop.
 2019-02-01 15:23:53 -08:00
Rasmus Munk Larsen
4c0fa6ce0f Speed up Eigen matrix*vector and vector*matrix multiplication. 
This change speeds up Eigen matrix * vector and vector * matrix multiplication for dynamic matrices when it is known at runtime that one of the factors is a vector.

The benchmarks below test

c.noalias()= n_by_n_matrix * n_by_1_matrix;
c.noalias()= 1_by_n_matrix * n_by_n_matrix;
respectively.

Benchmark measurements:

SSE:
Run on *** (72 X 2992 MHz CPUs); 2019-01-28T17:51:44.452697457-08:00
CPU: Intel Skylake Xeon with HyperThreading (36 cores) dL1:32KB dL2:1024KB dL3:24MB
Benchmark                          Base (ns)  New (ns) Improvement
------------------------------------------------------------------
BM_MatVec/64                            1096       312    +71.5%
BM_MatVec/128                           4581      1464    +68.0%
BM_MatVec/256                          18534      5710    +69.2%
BM_MatVec/512                         118083     24162    +79.5%
BM_MatVec/1k                          704106    173346    +75.4%
BM_MatVec/2k                         3080828    742728    +75.9%
BM_MatVec/4k                        25421512   4530117    +82.2%
BM_VecMat/32                             352       130    +63.1%
BM_VecMat/64                            1213       425    +65.0%
BM_VecMat/128                           4640      1564    +66.3%
BM_VecMat/256                          17902      5884    +67.1%
BM_VecMat/512                          70466     24000    +65.9%
BM_VecMat/1k                          340150    161263    +52.6%
BM_VecMat/2k                         1420590    645576    +54.6%
BM_VecMat/4k                         8083859   4364327    +46.0%

AVX2:
Run on *** (72 X 2993 MHz CPUs); 2019-01-28T17:45:11.508545307-08:00
CPU: Intel Skylake Xeon with HyperThreading (36 cores) dL1:32KB dL2:1024KB dL3:24MB
Benchmark                          Base (ns)  New (ns) Improvement
------------------------------------------------------------------
BM_MatVec/64                             619       120    +80.6%
BM_MatVec/128                           9693       752    +92.2%
BM_MatVec/256                          38356      2773    +92.8%
BM_MatVec/512                          69006     12803    +81.4%
BM_MatVec/1k                          443810    160378    +63.9%
BM_MatVec/2k                         2633553    646594    +75.4%
BM_MatVec/4k                        16211095   4327148    +73.3%
BM_VecMat/64                             925       227    +75.5%
BM_VecMat/128                           3438       830    +75.9%
BM_VecMat/256                          13427      2936    +78.1%
BM_VecMat/512                          53944     12473    +76.9%
BM_VecMat/1k                          302264    157076    +48.0%
BM_VecMat/2k                         1396811    675778    +51.6%
BM_VecMat/4k                         8962246   4459010    +50.2%

AVX512:
Run on *** (72 X 2993 MHz CPUs); 2019-01-28T17:35:17.239329863-08:00
CPU: Intel Skylake Xeon with HyperThreading (36 cores) dL1:32KB dL2:1024KB dL3:24MB
Benchmark                          Base (ns)  New (ns) Improvement
------------------------------------------------------------------
BM_MatVec/64                             401       111    +72.3%
BM_MatVec/128                           1846       513    +72.2%
BM_MatVec/256                          36739      1927    +94.8%
BM_MatVec/512                          54490      9227    +83.1%
BM_MatVec/1k                          487374    161457    +66.9%
BM_MatVec/2k                         2016270    643824    +68.1%
BM_MatVec/4k                        13204300   4077412    +69.1%
BM_VecMat/32                             324       106    +67.3%
BM_VecMat/64                            1034       246    +76.2%
BM_VecMat/128                           3576       802    +77.6%
BM_VecMat/256                          13411      2561    +80.9%
BM_VecMat/512                          58686     10037    +82.9%
BM_VecMat/1k                          320862    163750    +49.0%
BM_VecMat/2k                         1406719    651397    +53.7%
BM_VecMat/4k                         7785179   4124677    +47.0%
Currently watchingStop watching
 2019-01-31 14:24:08 -08:00
Gael Guennebaud
7ef879f6bf GEBP: improves pipelining in the 1pX4 path with FMA. 
Prior to this change, a product with a LHS having 8 rows was faster with AVX-only than with AVX+FMA.
With AVX+FMA I measured a speed up of about x1.25 in such cases.
 2019-01-30 23:45:12 +01:00
Gael Guennebaud
de77bf5d6c Fix compilation with ARM64. 2019-01-30 16:48:20 +01:00
Gael Guennebaud
eb4c6bb22d Fix conflicts and merge 2019-01-30 15:57:08 +01:00
Gael Guennebaud
df12fae8b8 According to https://gcc.gnu.org/bugzilla/show_bug.cgi?id=89101, the previous GCC issue is fixed in GCC trunk (will be gcc 9). 2019-01-30 11:52:28 +01:00
Gael Guennebaud
3775926bba ARM64 & GEBP: add specialization for double +30% speed up 2019-01-30 11:49:06 +01:00
Gael Guennebaud
be5b0f664a ARM64 & GEBP: Make use of vfmaq_laneq_f32 and workaround GCC's issue in generating good ASM 2019-01-30 11:48:25 +01:00
Gael Guennebaud
8a06c699d0 bug #1669: fix PartialPivLU/inverse with zero-sized matrices. 2019-01-29 10:27:13 +01:00
Gael Guennebaud
a2a07e62b9 Fix compilation with c++03 (local class cannot be template arguments), and make SparseMatrix::assignDiagonal truly protected. 2019-01-29 10:10:07 +01:00
Gael Guennebaud
f489f44519 bug #1574: implement "sparse_matrix =,+=,-= diagonal_matrix" with smart insertion strategies of missing diagonal coeffs. 2019-01-28 17:29:50 +01:00
Gael Guennebaud
803fa79767 Move evaluator<SparseCompressedBase>::find(i,j) to a more general and reusable SparseCompressedBase::lower_bound(i,j) functiion 2019-01-28 17:24:44 +01:00
Christoph Hertzberg
5a52e35f9a Renaming some more I identifiers 2019-01-26 13:18:21 +01:00
Rasmus Munk Larsen
71429883ee Fix compilation error in NEON GEBP specializaition of madd. 2019-01-25 17:00:21 -08:00
Gael Guennebaud
ec8a387972 cleanup 2019-01-24 10:24:45 +01:00
David Tellenbach
237b03b372 PR 574: use variadic template instead of initializer_list to implement fixed-size vector ctor from coefficients. 2019-01-23 00:07:19 +01:00
Gael Guennebaud
80f81f9c4b Cleanup SFINAE in Array/Matrix(initializer_list) ctors and minor doc editing. 2019-01-22 17:08:47 +01:00
David Tellenbach
db152b9ee6 PR 572: Add initializer list constructors to Matrix and Array (include unit 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
 2019-01-21 16:25:57 +01:00
nluehr
92774f0275 Replace host_define.h with cuda_runtime_api.h 2019-01-18 16:10:09 -06:00
Christoph Hertzberg
da0a41b9ce Mask unused-parameter warnings, when building with NDEBUG 2019-01-18 10:41:14 +01:00
Rasmus Munk Larsen
2eccbaf3f7 Add missing logical packet ops for GPU and NEON. 2019-01-17 17:45:08 -08:00
Gael Guennebaud
ee3662abc5 Remove some useless const_cast 2019-01-17 18:27:49 +01:00
Gael Guennebaud
0fe6b7d687 Make nestByValue works again (broken since 3.3) and add unit tests. 2019-01-17 18:27:25 +01:00
Gael Guennebaud
4b7cf7ff82 Extend reshaped unit tests and remove useless const_cast 2019-01-17 17:35:32 +01:00
Gael Guennebaud
b57c9787b1 Cleanup useless const_cast and add missing broadcast assignment tests 2019-01-17 16:55:42 +01:00
Gael Guennebaud
be05d0030d Make FullPivLU use conjugateIf<> 2019-01-17 12:01:00 +01:00
Patrick Peltzer
15e53d5d93 PR 567: makes all dense solvers inherit SoverBase (LU,Cholesky,QR,SVD). 
This changeset also includes:
 * add HouseholderSequence::conjugateIf
 * define int as the StorageIndex type for all dense solvers
 * dedicated unit tests, including assertion checking
 * _check_solve_assertion(): this method can be implemented in derived solver classes to implement custom checks
 * CompleteOrthogonalDecompositions: add applyZOnTheLeftInPlace, fix scalar type in applyZAdjointOnTheLeftInPlace(), add missing assertions
 * Cholesky: add missing assertions
 * FullPivHouseholderQR: Corrected Scalar type in _solve_impl()
 * BDCSVD: Unambiguous return type for ternary operator
 * SVDBase: Corrected Scalar type in _solve_impl()
 2019-01-17 01:17:39 +01:00
Gael Guennebaud
7f32109c11 Add conjugateIf<bool> members to DesneBase, TriangularView, SelfadjointView, and make PartialPivLU use it. 2019-01-17 11:33:43 +01:00
Gael Guennebaud
562985bac4 bug #1646: fix false aliasing detection for A.row(0) = A.col(0); 
This changeset completely disable the detection for vectors for which are current mechanism cannot detect any positive aliasing anyway.
 2019-01-17 00:14:27 +01:00
Rasmus Munk Larsen
7401e2541d Fix compilation error for logical packet ops with older compilers. 2019-01-16 14:43:33 -08:00
Gael Guennebaud
0f028f61cb GEBP: fix swapped kernel mode with AVX512 and complex scalars 2019-01-16 22:26:38 +01:00
Gael Guennebaud
e118ce86fd GEBP: cleanup logic to choose between a 4 packets of 1 packet 2019-01-16 21:47:42 +01:00
Gael Guennebaud
70e133333d bug #1661: fix regression in GEBP and AVX512 2019-01-16 21:22:20 +01:00
Gael Guennebaud
502f717980 bug #1646: disable aliasing detection for empty and 1x1 expression 2019-01-16 14:33:45 +01:00
Gael Guennebaud
0b466b6933 bug #1633: use proper type for madd temporaries, factorize RhsPacketx4. 2019-01-16 13:50:13 +01:00
Renjie Liu
dbfcceabf5 Bug: 1633: refactor gebp kernel and optimize for neon 2019-01-16 12:51:36 +08:00
Gael Guennebaud
2b70b2f570 Make Transform::rotation() an alias to Transform::linear() in the case of an Isometry 2019-01-15 22:50:42 +01:00
Gael Guennebaud
2c2c114995 Silent maybe-uninitialized warnings by gcc 2019-01-15 16:53:15 +01:00
Gael Guennebaud
6ec6bf0b0d Enable visitor on empty matrices (the visitor is left unchanged), and protect min/maxCoeff(Index*,Index*) on empty matrices by an assertion (+ doc & unit tests) 2019-01-15 15:21:14 +01:00
Gael Guennebaud
027e44ed24 bug #1592: makes partial min/max reductions trigger an assertion on inputs with a zero reduction length (+doc and tests) 2019-01-15 15:13:24 +01:00
Gael Guennebaud
f8bc5cb39e Fix detection of vector-at-time: use Rows/Cols instead of MaxRow/MaxCols. 
This fix VectorXd(n).middleCol(0,0).outerSize() which was equal to 1.
 2019-01-15 15:09:49 +01:00
Gael Guennebaud
6cf7afa3d9 Typo 2019-01-15 11:04:37 +01:00
Rasmus Larsen
7b3aab0936 Merged in rmlarsen/eigen (pull request PR-570) 
Add support for inverse hyperbolic functions. Fix cost of division.
 2019-01-14 21:31:33 +00:00
Gael Guennebaud
250dcd1fdb bug #1652: fix position of EIGEN_ALIGN16 attributes in Neon and Altivec 2019-01-14 21:45:56 +01:00
Rasmus Larsen
5a59452aae Merged eigen/eigen into default 2019-01-14 10:23:23 -08:00
Gael Guennebaud
3c9e6d206d AVX512: fix pgather/pscatter for Packet4cd and unaligned pointers 2019-01-14 17:57:28 +01:00
Gael Guennebaud
61b6eb05fe AVX512 (r)sqrt(double) was mistakenly disabled with clang and others 2019-01-14 17:28:47 +01:00
Gael Guennebaud
ccddeaad90 fix warning 2019-01-14 16:51:16 +01:00
Gael Guennebaud
d4881751d3 Doc: add Isometry in the list of supported Mode of Transform<> 2019-01-14 16:38:26 +01:00
Greg Coombe
9d988a1e1a Initialize isometric transforms like affine transforms. 
The isometric transform, like the affine transform, has an implicit last
row of [0, 0, 0, 1]. This was not being properly initialized, as verified
by a new test function.
 2019-01-11 23:14:35 -08:00
Gael Guennebaud
4356a55a61 PR 571: Implements an accurate argument reduction algorithm for huge inputs of sin/cos and call it instead of falling back to std::sin/std::cos. 
This makes both the small and huge argument cases faster because:
- for small inputs this removes the last pselect
- for large inputs only the reduction part follows a scalar path,
the rest use the same SIMD path as the small-argument case.
 2019-01-14 13:54:01 +01:00
Gael Guennebaud
f566724023 Fix StorageIndex FIXME in dense LU solvers 2019-01-13 17:54:30 +01:00
Rasmus Munk Larsen
1c6e6e2c3f Merge. 2019-01-11 17:47:11 -08:00
Rasmus Munk Larsen
28ba1b2c32 Add support for inverse hyperbolic functions. 
Fix cost of division.
 2019-01-11 17:45:37 -08:00
Rasmus Munk Larsen
89c4001d6f Fix warnings in ptrue for complex and half types. 2019-01-11 14:10:57 -08:00
Rasmus Munk Larsen
a49d01edba Fix warnings in ptrue for complex and half types. 2019-01-11 13:18:17 -08:00
Rasmus Munk Larsen
df29511ac0 Fix merge. 2019-01-11 10:36:36 -08:00
Rasmus Munk Larsen
9396ace46b Merge. 2019-01-11 10:28:52 -08:00
Rasmus Larsen
74882471d0 Merged eigen/eigen into default 2019-01-11 10:20:55 -08:00
Gael Guennebaud
9005f0111f Replace compiler's alignas/alignof extension by respective c++11 keywords when available. This also fix a compilation issue with gcc-4.7. 2019-01-11 17:10:54 +01:00
Mark D Ryan
3c9add6598 Remove reinterpret_cast from AVX512 complex implementation 
The reinterpret_casts used in ptranspose(PacketBlock<Packet8cf,4>&)
ptranspose(PacketBlock<Packet8cf,8>&) don't appear to be working
correctly.  They're used to convert the kernel parameters to
PacketBlock<Packet8d,T>& so that the complex number versions of
ptranspose can be written using the existing double implementations.
Unfortunately, they don't seem to work and are responsible for 9 unit
test failures in the AVX512 build of tensorflow master.  This commit
fixes the issue by manually initialising PacketBlock<Packet8d,T>
variables with the contents of the kernel parameter before calling
the double version of ptranspose, and then copying the resulting
values back into the kernel parameter before returning.
 2019-01-11 14:02:09 +01:00
Rasmus Munk Larsen
fcfced13ed Rename pones -> ptrue. Use _CMP_TRUE_UQ where appropriate. 2019-01-09 17:20:33 -08:00
Rasmus Munk Larsen
e15bb785ad Collapsed revision 
* Add packet up "pones". Write pnot(a) as pxor(pones(a), a).
* Collapsed revision
* Simplify a bit.
* Undo useless diffs.
* Fix typo.
 2019-01-09 16:34:23 -08:00
Rasmus Munk Larsen
f6ba6071c5 Fix typo. 2019-01-09 16:34:23 -08:00
Rasmus Munk Larsen
8f04442526 Collapsed revision 
* Collapsed revision
* Add packet up "pones". Write pnot(a) as pxor(pones(a), a).
* Collapsed revision
* Simplify a bit.
* Undo useless diffs.
* Fix typo.
 2019-01-09 16:34:23 -08:00
Rasmus Munk Larsen
e00521b514 Undo useless diffs. 2019-01-09 16:32:53 -08:00
Rasmus Munk Larsen
f2767112c8 Simplify a bit. 2019-01-09 16:29:18 -08:00
Rasmus Munk Larsen
cb955df9a6 Add packet up "pones". Write pnot(a) as pxor(pones(a), a). 2019-01-09 16:17:08 -08:00
Rasmus Larsen
cb3c059fa4 Merged eigen/eigen into default 2019-01-09 15:04:17 -08:00
Gael Guennebaud
d812f411c3 bug #1654: fix compilation with cuda and no c++11 2019-01-09 18:00:05 +01:00
Gael Guennebaud
3492a1ca74 fix plog(+inf) with AVX512 2019-01-09 16:53:37 +01:00
Gael Guennebaud
47810cf5b7 Add dedicated implementations of predux_any for AVX512, NEON, and Altivec/VSE 2019-01-09 16:40:42 +01:00
Gael Guennebaud
3f14e0d19e fix warning 2019-01-09 15:45:21 +01:00