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6165 Commits

Author SHA1 Message Date
Rasmus Munk Larsen
4aae8ac693 Fix typo in TypeCasting.h 2020-04-14 02:55:51 +00:00
Rasmus Munk Larsen
1d674003b2 Fix big in vectorized casting of 
{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.
 2020-04-14 02:11:06 +00:00
Christoph Hertzberg
d46d726e9d CommaInitializer wrongfully asserted for 0-sized blocks 
commainitialier unit-test never actually called `test_block_recursion`, which also was not correctly implemented and would have caused too deep template recursion.
 2020-04-13 16:41:20 +02:00
Antonio Sanchez
c854e189e6 Fixed commainitializer test. 
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.
 2020-04-10 13:53:26 -07:00
Rasmus Munk Larsen
f0577a2bfd Speed up matrix multiplication for small to medium size matrices by using 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)
 2020-04-07 22:09:51 +00:00
Antonio Sanchez
9dda5eb7d2 Missing struct definition in NumTraits 2020-04-07 09:01:11 -07:00
Akshay Naresh Modi
bcc0e9e15c Add numeric_limits min and max for bool 
This will allow (among other things) computation of argmax and argmin of bool tensors
 2020-04-06 23:38:57 +00:00
Bernardo Bahia Monteiro
54a0a9c9dd
Bugfix: conjugate_gradient did not compile with lazy-evaluated RealScalar 
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
 2020-03-29 19:44:12 -04:00
Rasmus Munk Larsen
393dbd8ee9 Fix bug in 52d54278be 2020-03-27 16:42:18 +00:00
Joel Holdsworth
6d2dbfc453 NEON: Fixed MSVC types definitions 2020-03-26 20:19:58 +00:00
Joel Holdsworth
52d54278be Additional NEON packet-math operations 2020-03-26 20:18:19 +00:00
Everton Constantino
deb93ed1bf Adhere to recommended load/store intrinsics for pp64le 2020-03-23 15:18:15 -03:00
Everton Constantino
5afdaa473a Fixing float32's pround halfway criteria to match STL's criteria. 2020-03-21 22:30:54 -05:00
Alessio M
96cd1ff718 Fixed: 
- 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
 2020-03-21 05:11:21 +00:00
dlazenby
cc954777f2 Update VectorwiseOp.h to allow Plugins similar to MatrixBase.h or ArrayBase.h 2020-03-20 19:30:01 +00:00
Masaki Murooka
55ecd58a3c Bug https://gitlab.com/libeigen/eigen/-/issues/1415: add missing EIGEN_DEVICE_FUNC to diagonal_product_evaluator_base. 2020-03-20 13:37:37 +09:00
Rasmus Munk Larsen
4da2c6b197 Remove reference to non-existent unary_op_base class. 2020-03-19 18:23:06 +00:00
Rasmus Munk Larsen
eda90baf35 Add missing arguments to numext::absdiff(). 2020-03-19 18:16:55 +00:00
Joel Holdsworth
d5c665742b Add absolute_difference coefficient-wise binary Array function 2020-03-19 17:45:20 +00:00
Everton Constantino
6ff5a14091 Reenabling packetmath unsigned tests, adding dummy pabs for relevant unsigned 
types.
 2020-03-19 17:31:49 +00:00
Joel Holdsworth
232f904082 Add shift_left<N> and shift_right<N> coefficient-wise unary Array functions 2020-03-19 17:24:06 +00:00
Joel Holdsworth
54aa8fa186 Implement integer square-root for NEON 2020-03-19 17:05:13 +00:00
Allan Leal
37ccb86916 Update NullaryFunctors.h 2020-03-16 11:59:02 +00:00
Deven Desai
7158ed4e0e Fixing HIP breakage caused by the recent commit that introduces Packet4h2 as the Eigen::Half packet type 2020-03-12 01:06:24 +00:00
Joel Holdsworth
d53ae40f7b NEON: Added int64_t and uint64_t packet math 2020-03-10 22:46:19 +00:00
Joel Holdsworth
4b9ecf2924 NEON: Added int8_t and uint8_t packet math 2020-03-10 22:46:19 +00:00
Joel Holdsworth
ceaabd4e16 NEON: Added int16_t and uint16_t packet math 2020-03-10 22:46:19 +00:00
Joel Holdsworth
d5d3cf9339 NEON: Added uint32_t packet math 2020-03-10 22:46:19 +00:00
Joel Holdsworth
eacf97f727 NEON: Implemented half-size vectors 2020-03-10 22:46:19 +00:00
Joel Holdsworth
5f411b729e NEON: Set packet_traits<double> flags 2020-03-10 22:46:19 +00:00
Sami Kama
b733b8b680 remove duplicate pset1 for half and add some comments about why we need expose pmul/add/div/min/max on host 2020-03-10 20:28:43 +00:00
Rasmus Munk Larsen
52a2fbbb00 Revert "avoid selecting half-packets when unnecessary" 
This reverts commit 5ca10480b0
 2020-02-25 01:07:43 +00:00
Rasmus Munk Larsen
235bcfe08d Revert "Pick full packet unconditionally when EIGEN_UNALIGNED_VECTORIZE" 
This reverts commit 44df2109c8
 2020-02-25 01:07:28 +00:00
Rasmus Munk Larsen
d7a42eade6 Revert "do not pick full-packet if it'd result in more operations" 
This reverts commit e9cc0cd353
 2020-02-25 01:07:15 +00:00
Tobias Bosch
f0ce88cff7 Include <sstream> explicitly, and don't rely on the implicit include via <complex>. 
This implicit dependency does no longer exist in a recent llbm release (sha 78be61871704).
 2020-02-24 23:09:36 +00:00
Francesco Mazzoli
e9cc0cd353 do not pick full-packet if it'd result in more operations 
See comment and
<https://gitlab.com/libeigen/eigen/merge_requests/46#note_270622952>.
 2020-02-07 18:16:16 +01:00
Francesco Mazzoli
44df2109c8 Pick full packet unconditionally when EIGEN_UNALIGNED_VECTORIZE 
See comment for details.
 2020-02-07 18:16:16 +01:00
Francesco Mazzoli
5ca10480b0 avoid selecting half-packets when unnecessary 
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);
 2020-02-07 18:16:16 +01:00
Rasmus Munk Larsen
6601abce86 Remove rogue include in TypeCasting.h. Meta.h is already included by the top-level header in Eigen/Core. 2020-01-14 21:03:53 +00:00
Everton Constantino
5a8b97b401 Switching unpacket_traits<Packet4i> to vectorizable=true. 2020-01-13 16:08:20 -03:00
Everton Constantino
42838c28b8 Adding correct cache sizes for PPC architecture. 2020-01-13 16:58:14 +00:00
Rasmus Munk Larsen
e1ecfc162d call Explicitly ::rint and ::rintf for targets without c++11. Without this, the Windows build breaks when trying to compile numext::rint<double>. 2020-01-10 21:14:08 +00:00
Joel Holdsworth
da5a7afed0 Improvements to the tidiness and completeness of the NEON implementation 2020-01-10 18:31:15 +00:00
Anuj Rawat
452371cead Fix for gcc build error when using Eigen headers with AVX512 2020-01-10 18:05:42 +00:00
mehdi-goli
601f89dfd0 Adding RInt vector support for SYCL. 2020-01-10 18:00:36 +00:00
Rasmus Munk Larsen
9254974115 Don't add EIGEN_DEVICE_FUNC to random() since ::rand is not available in Cuda. 2020-01-09 21:23:09 +00:00
Rasmus Munk Larsen
a3ec89b5bd Add missing EIGEN_DEVICE_FUNC annotations in MathFunctions.h. 2020-01-09 21:06:34 +00:00
Rasmus Munk Larsen
e6fcee995b Don't use the rational approximation to the logistic function on GPUs as it appears to be slightly slower. 2020-01-09 00:04:26 +00:00
Rasmus Munk Larsen
4217a9f090 The upper limits for where to use the rational approximation to the logistic 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()). 2020-01-08 22:21:37 +00:00
Ilya Tokar
19876ced76 Bug #1785: Introduce numext::rint. 
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).
 2020-01-07 21:22:44 +00:00