devtools/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2026-04-10 11:34:33 +08:00
Code Issues Packages Projects Releases Wiki Activity
10,996 Commits 15 Branches 93 Tags
ee4715ff488d5cf685820ad06374cbe7d509ac1a
Commit Graph

47 Commits

Author SHA1 Message Date
David Tellenbach
ee4715ff48 Fix test basic stuff 
- Guard fundamental types that are not available pre C++11
- Separate subsequent angle brackets >> by spaces
- Allow casting of Eigen::half and Eigen::bfloat16 to complex types
 2020-07-09 17:24:00 +00:00
Antonio Sanchez
9cb8771e9c Fix tensor casts for large packets and casts to/from std::complex 
The original tensor casts were only defined for
`SrcCoeffRatio`:`TgtCoeffRatio` 1:1, 1:2, 2:1, 4:1. Here we add the
missing 1:N and 8:1.

We also add casting `Eigen::half` to/from `std::complex<T>`, which
was missing to make it consistent with `Eigen:bfloat16`, and
generalize the overload to work for any complex type.

Tests were added to `basicstuff`, `packetmath`, and
`cxx11_tensor_casts` to test all cast configurations.
 2020-06-30 18:53:55 +00:00
Teng Lu
386d809bde Support BFloat16 in Eigen 2020-06-20 19:16:24 +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
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
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
Rasmus Munk Larsen
ea51a9eace Add missing EIGEN_DEVICE_FUNC attribute to template specializations for pexp to fix GPU build. 2019-11-27 10:17:09 -08:00
Gael Guennebaud
e5778b87b9 Fix duplicate symbol linking error. 2019-11-20 17:23:19 +01:00
Rasmus Munk Larsen
fab4e3a753 Address comments on Chebyshev evaluation code: 
1. Use pmadd when possible.
2. Add casts to avoid c++03 warnings.
 2019-10-02 12:48:17 -07:00
Rasmus Munk Larsen
bd0fac456f Prevent infinite loop in the nvcc compiler while unrolling the recurrent templates for Chebyshev polynomial evaluation. 2019-10-01 13:15:30 -07:00
Srinivas Vasudevan
facdec5aa7 Add packetized versions of i0e and i1e special functions. 
- 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.
 2019-09-11 18:34:02 -07:00
Deven Desai
cdb377d0cb Fix for the HIP build+test errors introduced by the ndtri support. 
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!)
 2019-09-06 16:03:49 +00:00
Gael Guennebaud
17226100c5 Fix a circular dependency regarding pshift* functions and GenericPacketMathFunctions. 
Another solution would have been to make pshift* fully generic template functions with
partial specialization which is always a mess in c++03.
 2019-09-06 09:26:04 +02:00
Srinivas Vasudevan
e38dd48a27 PR 681: Add ndtri function, the inverse of the normal distribution function. 2019-08-12 19:26:29 -04:00
Rasmus Munk Larsen
1187bb65ad Add more tests for corner cases of log1p and expm1. Add handling of infinite arguments to log1p such that log1p(inf) = inf. 2019-08-28 12:20:21 -07:00
Rasmus Munk Larsen
9aba527405 Revert changes to std_falback::log1p that broke handling of arguments less than -1. Fix packet op accordingly. 2019-08-27 15:35:29 -07:00
Rasmus Munk Larsen
b021cdea6d Clean up float16 a.k.a. Eigen::half support in Eigen. Move the definition of half to Core/arch/Default and move arch-specific packet ops to their respective sub-directories. 2019-08-27 11:30:31 -07:00
Rasmus Munk Larsen
a3298b22ec Implement vectorized versions of log1p and expm1 in Eigen using Kahan's 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
 2019-08-12 13:53:28 -07:00
Gael Guennebaud
f11364290e ICC does not support -fno-unsafe-math-optimizations 2019-03-22 09:26:24 +01:00
Gael Guennebaud
1c09ee8541 bug #1674: workaround clang fast-math aggressive optimizations 2019-02-22 15:48:53 +01:00
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
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
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
Gael Guennebaud
3f14e0d19e fix warning 2019-01-09 15:45:21 +01:00
Gael Guennebaud
e6b217b8dd bug #1652: implements a much more accurate version of vectorized sin/cos. This new version achieve same speed for SSE/AVX, and is slightly faster with FMA. Guarantees are as follows: 
- no FMA: 1ULP up to 3pi, 2ULP up to sin(25966) and cos(18838), fallback to std::sin/cos for larger inputs
  - FMA: 1ULP up to sin(117435.992) and cos(71476.0625), fallback to std::sin/cos for larger inputs
 2019-01-09 15:25:17 +01:00
Gael Guennebaud
0f6f75bd8a Implement a faster fix for sin/cos of large entries that also correctly handle INF input. 2018-12-23 17:26:21 +01:00
Gael Guennebaud
38d704def8 Make sure that psin/pcos return number in [-1,1] for large inputs (though sin/cos on large entries is quite useless because it's inaccurate) 2018-12-23 16:13:24 +01:00
Gael Guennebaud
5713fb7feb Fix plog(+INF): it returned ~87 instead of +INF 2018-12-23 15:40:52 +01:00
Gael Guennebaud
efa4c9c40f bug #1615: slightly increase the default unrolling limit to compensate for changeset 101ea26f5e 
.
This solves a performance regression with clang and 3x3 matrix products.
 2018-12-13 10:42:39 +01:00
Gael Guennebaud
b477d60bc6 Extend the generic psin_float code to handle cosine and make SSE and AVX use it (-> this adds pcos for AVX) 2018-11-30 11:26:30 +01:00
Gael Guennebaud
b131a4db24 bug #1631: fix compilation with ARM NEON and clang, and cleanup the weird pshiftright_and_cast and pcast_and_shiftleft functions. 2018-11-27 23:45:00 +01:00
Gael Guennebaud
a1a5fbbd21 Update pshiftleft to pass the shift as a true compile-time integer. 2018-11-27 22:57:30 +01:00
Gael Guennebaud
fa7fd61eda Unify SSE/AVX psin functions. 
It is based on the SSE version which is much more accurate, though very slightly slower.
This changeset also includes the following required changes:
 - add packet-float to packet-int type traits
 - add packet float<->int reinterpret casts
 - add faster pselect for AVX based on blendv
 2018-11-27 22:41:51 +01:00
Gael Guennebaud
502f92fa10 Unify SSE and AVX pexp for double. 2018-11-26 23:12:44 +01:00
Gael Guennebaud
cf8b85d5c5 Unify SSE and AVX implementation of pexp 2018-11-26 16:36:19 +01:00
Gael Guennebaud
2c44c40114 First step toward a unification of packet log implementation, currently only SSE and AVX are unified. 
To this end, I added the following functions: pzero, pcmp_*, pfrexp, pset1frombits functions.
 2018-11-26 14:21:24 +01:00
Gael Guennebaud
b240080e64 bug #1436: fix compilation of Jacobi rotations with ARM NEON, some specializations of internal::conj_helper were missing. 2017-06-15 10:16:30 +02:00
Gael Guennebaud
35a8e94577 bug #1167: simplify installation of header files using cmake's install(DIRECTORY ...) command. 2016-08-29 10:59:37 +02:00
Benoit Jacob
69124cfca2 Automatic relicensing to MPL2 using Keirs script. Manual fixup follows. 2012-07-13 14:42:47 -04:00
Jitse Niesen
e2d46eac42 Remove all references to EIGEN_TUNE_CPU_CACHE_SIZE. 
This macro is no longer used as of revision 0212eec23f
.
 2011-02-04 22:33:53 +01:00
Benoit Jacob
3a30a2bc3e forgot to remove a #endif 2010-08-13 14:03:38 -04:00
Benoit Jacob
b80d9dd42e fix determination of number of registers on sse: 
__i386__ was not defined by MSVC 2010.
fixed as (2*sizeof(void*)).
also move that to SSE/ and let the default for unknown arch's be just 8.
 2010-08-13 13:55:28 -04:00
Gael Guennebaud
28e64b0da3 email change 2010-06-24 23:21:58 +02:00
Gael Guennebaud
88cd6885be Add a proof concept API to configure the blocking parameters at runtime. 
After validation of the final API I'll update the other products to use it.
 2010-06-07 16:35:25 +02:00
Gael Guennebaud
9a3b00c040 add missing cmake directives for arch/Default 2010-03-08 22:15:35 +01:00
Gael Guennebaud
ea8cad5151 make the number of registers easier to configure per architectures 2010-03-04 18:58:12 +01:00
Gael Guennebaud
7dd81aad74 factorize default performance related settings to a single file 
included after the architecture specific files such that they
can be adapted by each platform.
 2010-03-03 18:47:58 +01:00