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1712 Commits

Author SHA1 Message Date
Benoit Steiner
32ffce04fc Use EIGEN_THREAD_YIELD instead of std::this_thread::yield to make the code more portable. 2016-04-21 08:47:28 -07:00
Benoit Steiner
2dde1b1028 Don't crash when attempting to reduce empty tensors. 2016-04-20 18:08:20 -07:00
Benoit Steiner
a792cd357d Added more tests 2016-04-20 17:33:58 -07:00
Benoit Steiner
c7c2054bb5 Started to implement a portable way to yield. 2016-04-19 17:59:58 -07:00
Benoit Steiner
2b72163028 Implemented a more portable version of thread local variables 2016-04-19 15:56:02 -07:00
Benoit Steiner
04f954956d Fixed a few typos 2016-04-19 15:27:09 -07:00
Benoit Steiner
5b1106c56b Fixed a compilation error with nvcc 7. 2016-04-19 14:57:57 -07:00
Benoit Steiner
7129d998db Simplified the code that launches cuda kernels. 2016-04-19 14:55:21 -07:00
Benoit Steiner
b9ea40c30d Don't take the address of a kernel on CUDA devices that don't support this feature. 2016-04-19 14:35:11 -07:00
Benoit Steiner
884c075058 Use numext::ceil instead of std::ceil 2016-04-19 14:33:30 -07:00
Benoit Steiner
a278414d1b Avoid an unnecessary copy of the evaluator. 2016-04-19 13:54:28 -07:00
Benoit Steiner
f953c60705 Fixed 2 recent regression tests 2016-04-19 12:57:39 -07:00
Benoit Steiner
50968a0a3e Use DenseIndex in the MeanReducer to avoid overflows when processing very large tensors. 2016-04-19 11:53:58 -07:00
Benoit Steiner
84543c8be2 Worked around the lack of a rand_r function on windows systems 2016-04-17 19:29:27 -07:00
Benoit Steiner
5fbcfe5eb4 Worked around the lack of a rand_r function on windows systems 2016-04-17 18:42:31 -07:00
Benoit Steiner
c8e8f93d6c Move the evalGemm method into the TensorContractionEvaluatorBase class to make it accessible from both the single and multithreaded contraction evaluators. 2016-04-15 16:48:10 -07:00
Benoit Steiner
7cff898e0a Deleted unnecessary variable 2016-04-15 15:46:14 -07:00
Benoit Steiner
6c43c49e4a Fixed a few compilation warnings 2016-04-15 15:34:34 -07:00
Benoit Steiner
eb669f989f Merged in rmlarsen/eigen (pull request PR-178) 
Eigen Tensor cost model part 2: Thread scheduling for standard evaluators and reductions.
 2016-04-15 14:53:15 -07:00
Rasmus Munk Larsen
3718bf654b Get rid of void* casting when calling EvalRange::run. 2016-04-15 12:51:33 -07:00
Benoit Steiner
40c9923a8a Fixed compilation errors with msvc 2016-04-15 11:27:52 -07:00
Benoit Steiner
a62e924656 Added ability to access the cache sizes from the tensor devices 2016-04-14 21:25:06 -07:00
Benoit Steiner
18e6f67426 Added support for exclusive or 2016-04-14 20:37:46 -07:00
Rasmus Munk Larsen
07ac4f7e02 Eigen Tensor cost model part 2: Thread scheduling for standard evaluators and reductions. The cost model is turned off by default. 2016-04-14 18:28:23 -07:00
Benoit Steiner
9624a1ea3d Added missing definition of PacketSize in the gpu evaluator of convolution 2016-04-14 17:16:58 -07:00
Benoit Steiner
6fbedf5a4e Merged in rmlarsen/eigen (pull request PR-177) 
Eigen Tensor cost model part 1.
 2016-04-14 17:13:19 -07:00
Benoit Steiner
bebb89acfa Enabled the new threadpool tests 2016-04-14 16:44:10 -07:00
Benoit Steiner
9c064b5a97 Cleanup 2016-04-14 16:41:31 -07:00
Benoit Steiner
1372156c41 Prepared the migration to the new non blocking thread pool 2016-04-14 16:16:42 -07:00
Rasmus Munk Larsen
aeb5494a0b Improvements to cost model. 2016-04-14 15:52:58 -07:00
Benoit Steiner
a8e8837ba7 Added tests for the non blocking thread pool 2016-04-14 15:23:49 -07:00
Benoit Steiner
78a51abc12 Added a more scalable non blocking thread pool 2016-04-14 15:23:10 -07:00
Rasmus Munk Larsen
d2e95492e7 Merge upstream updates. 2016-04-14 13:59:50 -07:00
Rasmus Munk Larsen
235e83aba6 Eigen cost model part 1. This implements a basic recursive framework to estimate the cost of evaluating tensor expressions. 2016-04-14 13:57:35 -07:00
Benoit Steiner
5912ad877c Silenced a compilation warning 2016-04-14 11:40:14 -07:00
Benoit Steiner
2b6e3de02f Added tests to validate flooring and ceiling of fp16 2016-04-14 11:39:18 -07:00
Benoit Steiner
6f23e945f6 Added simple test for numext::sqrt and numext::pow on fp16 2016-04-14 10:32:52 -07:00
Benoit Steiner
72510c80e1 Added basic test for trigonometric functions on fp16 2016-04-14 10:27:24 -07:00
Benoit Steiner
c7167fee0e Added support for fp16 to the sigmoid function 2016-04-14 10:08:33 -07:00
Benoit Steiner
f6003f0873 Made the test msvc friendly 2016-04-14 09:47:26 -07:00
Gael Guennebaud
7d1391d049 Turn a converge check to a warning 2016-04-13 22:50:54 +02:00
Benoit Steiner
e9b12cc1f7 Fixed compilation warnings generated by clang 2016-04-12 20:53:18 -07:00
Benoit Steiner
e3a184785c Fixed the zeta test 2016-04-12 11:12:36 -07:00
Benoit Steiner
3b76df64fc Defer the decision to vectorize tensor CUDA code to the meta kernel. This makes it possible to decide to vectorize or not depending on the capability of the target cuda architecture. In particular, this enables us to vectorize the processing of fp16 when running on device of capability >= 5.3 2016-04-12 10:58:51 -07:00
Gael Guennebaud
af2161cdb4 bug #1197: fix/relax some LM unit tests 2016-04-09 11:14:02 +02:00
Gael Guennebaud
a05a683d83 bug #1160: fix and relax some lm unit tests by turning faillures to warnings 2016-04-09 10:49:19 +02:00
Benoit Steiner
995f202cea Disabled the use of half2 on cuda devices of compute capability < 5.3 2016-04-08 14:43:36 -07:00
Benoit Steiner
0d2a532fc3 Created the new EIGEN_TEST_CUDA_CLANG option to compile the CUDA tests using clang instead of nvcc 2016-04-08 13:16:08 -07:00
Benoit Steiner
2d072b38c1 Don't test the division by 0 on float16 when compiling with msvc since msvc detects and errors out on divisions by 0. 2016-04-08 12:50:25 -07:00
Benoit Steiner
d962fe6a99 Renamed float16 into cxx11_float16 since the test relies on c++11 features 2016-04-07 20:28:32 -07:00