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abc815798b
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1843 Commits

Author SHA1 Message Date
Benoit Steiner
abc815798b Added a new operation to enable more powerful tensorindexing. 2016-05-27 12:22:25 -07:00
Benoit Steiner
5707537592 Fixed option '--relaxed-constexpr' has been deprecated and replaced by option '--expt-relaxed-constexpr' warning generated by nvcc 7.5 2016-05-27 10:47:53 -07:00
Gael Guennebaud
22a035db95 Fix compilation when defaulting to row-major 2016-05-27 10:31:11 +02:00
Benoit Steiner
1ae2567861 Fixed some compilation warnings 2016-05-26 15:57:19 -07:00
Benoit Steiner
1a47844529 Preserve the ability to vectorize the evaluation of an expression even when it involves a cast that isn't vectorized (e.g fp16 to float) 2016-05-26 14:37:09 -07:00
Benoit Steiner
36369ab63c Resolved merge conflicts 2016-05-26 13:39:39 -07:00
Benoit Steiner
28fcb5ca2a Merged latest reduction improvements 2016-05-26 12:19:33 -07:00
Benoit Steiner
c1c7f06c35 Improved the performance of inner reductions. 2016-05-26 11:53:59 -07:00
Benoit Steiner
22d02c9855 Improved the coverage of the fp16 reduction tests 2016-05-26 11:12:16 -07:00
Benoit Steiner
8288b0aec2 Code cleanup. 2016-05-26 09:00:04 -07:00
Benoit Steiner
2d7ed54ba2 Made the static storage class qualifier come first. 2016-05-25 22:16:15 -07:00
Benoit Steiner
e1fca8866e Deleted unnecessary explicit qualifiers. 2016-05-25 22:15:26 -07:00
Benoit Steiner
9b0aaf5113 Don't mark inline functions as static since it confuses the ICC compiler 2016-05-25 22:10:11 -07:00
Benoit Steiner
037a463fd5 Marked unused variables as such 2016-05-25 22:07:48 -07:00
Benoit Steiner
3ac4045272 Made the IndexPair code compile in non cxx11 mode 2016-05-25 15:15:12 -07:00
Benoit Steiner
66556d0e05 Made the index pair list code more portable accross various compilers 2016-05-25 14:34:27 -07:00
Benoit Steiner
034aa3b2c0 Improved the performance of tensor padding 2016-05-25 11:43:08 -07:00
Benoit Steiner
58026905ae Added support for statically known lists of pairs of indices 2016-05-25 11:04:14 -07:00
Benoit Steiner
0835667329 There is no need to make the fp16 full reduction kernel a static function. 2016-05-24 23:11:56 -07:00
Benoit Steiner
b5d6b52a4d Fixed compilation warning 2016-05-24 23:10:57 -07:00
Benoit Steiner
a09cbf9905 Merged in rmlarsen/eigen (pull request PR-188) 
Minor cleanups: 1. Get rid of a few unused variables. 2. Get rid of last uses of EIGEN_USE_COST_MODEL.
 2016-05-23 12:55:12 -07:00
Christoph Hertzberg
718521d5cf Silenced several double-promotion warnings 2016-05-22 18:17:04 +02:00
Christoph Hertzberg
b5a7603822 fixed macro name 2016-05-22 16:49:29 +02:00
Christoph Hertzberg
25a03c02d6 Fix some sign-compare warnings 2016-05-22 16:42:27 +02:00
Gael Guennebaud
ccaace03c9 Make EIGEN_HAS_CONSTEXPR user configurable 2016-05-20 15:10:08 +02:00
Gael Guennebaud
c3410804cd Make EIGEN_HAS_VARIADIC_TEMPLATES user configurable 2016-05-20 15:05:38 +02:00
Gael Guennebaud
48bf5ec216 Make EIGEN_HAS_RVALUE_REFERENCES user configurable 2016-05-20 14:54:20 +02:00
Gael Guennebaud
f43ae88892 Rename EIGEN_HAVE_RVALUE_REFERENCES to EIGEN_HAS_RVALUE_REFERENCES 2016-05-20 14:48:51 +02:00
Gael Guennebaud
2f656ce447 Remove std:: to enable custom scalar types. 2016-05-19 23:13:47 +02:00
Rasmus Larsen
b1e080c752 Merged eigen/eigen into default 2016-05-18 15:21:50 -07:00
Rasmus Munk Larsen
5624219b6b Merge. 2016-05-18 15:16:06 -07:00
Rasmus Munk Larsen
7df811cfe5 Minor cleanups: 1. Get rid of unused variables. 2. Get rid of last uses of EIGEN_USE_COST_MODEL. 2016-05-18 15:09:48 -07:00
Benoit Steiner
bb3ff8e9d9 Advertize the packet api of the tensor reducers iff the corresponding packet primitives are available. 2016-05-18 14:52:49 -07:00
Gael Guennebaud
548a487800 bug #1229: bypass usage of Derived::Options which is available for plain matrix types only. Better use column-major storage anyway. 2016-05-18 16:44:05 +02:00
Gael Guennebaud
43790e009b Pass argument by const ref instead of by value in pow(AutoDiffScalar...) 2016-05-18 16:28:02 +02:00
Gael Guennebaud
1fbfab27a9 bug #1223: fix compilation of AutoDiffScalar's min/max operators, and add regression unit test. 2016-05-18 16:26:26 +02:00
Gael Guennebaud
448d9d943c bug #1222: fix compilation in AutoDiffScalar and add respective unit test 2016-05-18 16:00:11 +02:00
Rasmus Munk Larsen
f519fca72b Reduce overhead for small tensors and cheap ops by short-circuiting the const computation and block size calculation in parallelFor. 2016-05-17 16:06:00 -07:00
Benoit Steiner
86ae94462e #if defined(EIGEN_USE_NONBLOCKING_THREAD_POOL) is now #if !defined(EIGEN_USE_SIMPLE_THREAD_POOL): the non blocking thread pool is the default since it's more scalable, and one needs to request the old thread pool explicitly. 2016-05-17 14:06:15 -07:00
Benoit Steiner
997c335970 Fixed compilation error 2016-05-17 12:54:18 -07:00
Benoit Steiner
ebf6ada5ee Fixed compilation error in the tensor thread pool 2016-05-17 12:33:46 -07:00
Rasmus Munk Larsen
0bb61b04ca Merge upstream. 2016-05-17 10:26:10 -07:00
Rasmus Munk Larsen
0dbd68145f Roll back changes to core. Move include of TensorFunctors.h up to satisfy dependence in TensorCostModel.h. 2016-05-17 10:25:19 -07:00
Rasmus Larsen
00228f2506 Merged eigen/eigen into default 2016-05-17 09:49:31 -07:00
Benoit Steiner
e7e64c3277 Enable the use of the packet api to evaluate tensor broadcasts. This speed things up quite a bit: 
Before"
M_broadcasting/10        500000       3690    27.10 MFlops/s
BM_broadcasting/80        500000       4014  1594.24 MFlops/s
BM_broadcasting/640       100000      14770 27731.35 MFlops/s
BM_broadcasting/4K          5000     632711 39512.48 MFlops/s
After:
BM_broadcasting/10        500000       4287    23.33 MFlops/s
BM_broadcasting/80        500000       4455  1436.41 MFlops/s
BM_broadcasting/640       200000      10195 40173.01 MFlops/s
BM_broadcasting/4K          5000     423746 58997.57 MFlops/s
 2016-05-17 09:24:35 -07:00
Benoit Steiner
5fa27574dd Allow vectorized padding on GPU. This helps speed things up a little 
Before:
BM_padding/10            5000000        460   217.03 MFlops/s
BM_padding/80            5000000        460 13899.40 MFlops/s
BM_padding/640           5000000        461 888421.17 MFlops/s
BM_padding/4K            5000000        460 54316322.55 MFlops/s
After:
BM_padding/10            5000000        454   220.20 MFlops/s
BM_padding/80            5000000        455 14039.86 MFlops/s
BM_padding/640           5000000        452 904968.83 MFlops/s
BM_padding/4K            5000000        411 60750049.21 MFlops/s
 2016-05-17 09:17:26 -07:00
Benoit Steiner
a910bcee43 Merged latest updates from trunk 2016-05-17 09:14:22 -07:00
Benoit Steiner
8d06c02ffd Allow vectorized padding on GPU. This helps speed things up a little. 
Before:
BM_padding/10            5000000        460   217.03 MFlops/s
BM_padding/80            5000000        460 13899.40 MFlops/s
BM_padding/640           5000000        461 888421.17 MFlops/s
BM_padding/4K            5000000        460 54316322.55 MFlops/s
After:
BM_padding/10            5000000        454   220.20 MFlops/s
BM_padding/80            5000000        455 14039.86 MFlops/s
BM_padding/640           5000000        452 904968.83 MFlops/s
BM_padding/4K            5000000        411 60750049.21 MFlops/s
 2016-05-17 09:13:27 -07:00
Benoit Steiner
86da77cb9b Pulled latest updates from trunk. 2016-05-17 07:21:48 -07:00
Benoit Steiner
92fc6add43 Don't rely on c++11 extension when we don't have to. 2016-05-17 07:21:22 -07:00