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707 Commits

Author SHA1 Message Date
Benoit Steiner
fd9401f260 Refined the cost of the striding operation. 2016-04-25 09:16:08 -07:00
Benoit Steiner
4bbc97be5e Provide access to the base threadpool classes 2016-04-21 17:59:33 -07:00
Benoit Steiner
33adce5c3a Added the ability to switch to the new thread pool with a #define 2016-04-21 11:59:58 -07:00
Benoit Steiner
f670613e4b Fixed several compilation warnings 2016-04-21 11:03:02 -07:00
Benoit Steiner
2dde1b1028 Don't crash when attempting to reduce empty tensors. 2016-04-20 18:08:20 -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
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
50968a0a3e Use DenseIndex in the MeanReducer to avoid overflows when processing very large tensors. 2016-04-19 11:53:58 -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
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
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
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
c7167fee0e Added support for fp16 to the sigmoid function 2016-04-14 10:08:33 -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
Benoit Steiner
7d5b17087f Added missing EIGEN_DEVICE_FUNC to the tensor conversion code. 2016-04-07 20:01:19 -07:00
Benoit Steiner
48308ed801 Added support for isinf, isnan, and isfinite checks to the tensor api 2016-04-07 09:48:36 -07:00
Benoit Steiner
7be1eaad1e Fixed typos in the implementation of the zeta and polygamma ops. 2016-04-06 14:15:37 -07:00
Till Hoffmann
80eba21ad0 Merge upstream. 2016-04-01 18:18:49 +01:00
Till Hoffmann
ffd770ce94 Fixed CUDA signature. 2016-04-01 17:58:24 +01:00
tillahoffmann
49960adbdd Merged eigen/eigen into default 2016-04-01 14:36:15 +01:00
Till Hoffmann
57239f4a81 Added polygamma function. 2016-04-01 14:35:21 +01:00
Till Hoffmann
dd5d390daf Added zeta function. 2016-04-01 13:32:29 +01:00
Benoit Steiner
3da495e6b9 Relaxed the condition used to gate the fft code. 2016-03-31 18:11:51 -07:00
Benoit Steiner
0f5cc504fe Properly gate the fft code 2016-03-31 12:59:39 -07:00
Benoit Steiner
af4ef540bf Fixed a off-by-one bug in a debug assertion 2016-03-30 18:37:19 -07:00
Benoit Steiner
791e5cfb69 Added NumTraits for type2index. 2016-03-30 18:36:36 -07:00
Benoit Steiner
483aaad10a Fixed compilation warning 2016-03-30 17:08:13 -07:00
Benoit Steiner
1b40abbf99 Added missing assignment operator to the TensorUInt128 class, and made misc small improvements 2016-03-30 13:17:03 -07:00
Benoit Steiner
aa45ad2aac Fixed the formatting of the README. 2016-03-29 15:06:13 -07:00
Benoit Steiner
56df5ef1d7 Attempt to fix the formatting of the README 2016-03-29 15:03:38 -07:00
Benoit Steiner
c38295f0a0 Added support for fmod 2016-03-28 15:53:02 -07:00
Benoit Steiner
6772f653c3 Made it possible to customize the threadpool 2016-03-28 10:01:04 -07:00
Benoit Steiner
1bc81f7889 Fixed compilation warnings on arm 2016-03-28 09:21:04 -07:00
Benoit Steiner
78f83d6f6a Prevent potential overflow. 2016-03-28 09:18:04 -07:00
Benoit Steiner
74f91ed06c Improved support for integer modulo 2016-03-25 17:21:56 -07:00
Benoit Steiner
41434a8a85 Avoid unnecessary conversions 2016-03-23 16:52:38 -07:00
Benoit Steiner
92693b50eb Fixed compilation warning 2016-03-23 16:40:36 -07:00
Benoit Steiner
393bc3b16b Added comment 2016-03-23 16:22:15 -07:00
Benoit Steiner
3d1e857327 Fixed compilation error 2016-03-22 15:48:28 -07:00
Benoit Steiner
de7d92c259 Pulled latest updates from trunk 2016-03-22 15:24:49 -07:00
Benoit Steiner
002cf0d1c9 Use a single Barrier instead of a collection of Notifications to reduce the thread synchronization overhead 2016-03-22 15:24:23 -07:00
Benoit Steiner
bc2b802751 Fixed a couple of typos 2016-03-22 14:27:34 -07:00
Benoit Steiner
6a31b7be3e Avoid using std::vector whenever possible 2016-03-22 14:02:50 -07:00
Benoit Steiner
65a7113a36 Use an enum instead of a static const int to prevent possible link error 2016-03-22 09:33:54 -07:00
Benoit Steiner
f9ad25e4d8 Fixed contractions of 16 bit floats 2016-03-22 09:30:23 -07:00
Benoit Steiner
8ef3181f15 Worked around a constness related issue 2016-03-21 11:24:05 -07:00
Benoit Steiner
7a07d6aa2b Small cleanup 2016-03-21 11:12:17 -07:00
Benoit Steiner
e91f255301 Marked variables that's only used in debug mode as such 2016-03-21 10:02:00 -07:00
Benoit Steiner
db5c14de42 Explicitly cast the default value into the proper scalar type. 2016-03-21 09:52:58 -07:00
Benoit Steiner
8e03333f06 Renamed some class members to make the code more readable. 2016-03-18 15:21:04 -07:00
Benoit Steiner
6c08943d9f Fixed a bug in the padding of extracted image patches. 2016-03-18 15:19:10 -07:00
Benoit Steiner
9a7ece9caf Worked around constness issue 2016-03-18 10:38:29 -07:00
Benoit Steiner
edc679f6c6 Fixed compilation warning 2016-03-18 07:12:34 -07:00
Benoit Steiner
70eb70f5f8 Avoid mutable class members when possible 2016-03-17 21:47:18 -07:00
Benoit Steiner
95b8961a9b Allocate the mersenne twister used by the random number generators on the heap instead of on the stack since they tend to keep a lot of state (i.e. about 5k) around. 2016-03-17 15:23:51 -07:00
Benoit Steiner
f7329619da Fix bug in tensor contraction. The code assumes that contraction axis indices for the LHS (after possibly swapping to ColMajor!) is increasing. Explicitly sort the contraction axis pairs to make it so. 2016-03-17 15:08:02 -07:00
Christoph Hertzberg
46aa9772fc Merged in ebrevdo/eigen (pull request PR-169) 
Bugfixes to cuda tests, igamma & igammac implemented, & tests for digamma, igamma, igammac on CPU & GPU.
 2016-03-16 21:59:08 +01:00
Benoit Steiner
b72ffcb05e Made the comparison of Eigen::array GPU friendly 2016-03-11 16:37:59 -08:00
Benoit Steiner
25f69cb932 Added a comparison operator for Eigen::array 
Alias Eigen::array to std::array when compiling with Visual Studio 2015
 2016-03-11 15:20:37 -08:00
Benoit Steiner
86d45a3c83 Worked around visual studio compilation warnings. 2016-03-09 21:29:39 -08:00
Benoit Steiner
8fd4241377 Fixed a typo. 2016-03-10 02:28:46 +00:00
Benoit Steiner
a685a6beed Made the list reductions less ambiguous. 2016-03-09 17:41:52 -08:00
Benoit Steiner
3149b5b148 Avoid implicit cast 2016-03-09 17:35:17 -08:00
Benoit Steiner
f05fb449b8 Avoid unnecessary conversion from 32bit int to 64bit unsigned int 2016-03-09 15:27:45 -08:00
Benoit Steiner
1d566417d2 Enable the random number generators when compiling with visual studio 2016-03-09 10:55:11 -08:00
Benoit Steiner
b084133dbf Fixed the integer division code on windows 2016-03-09 07:06:36 -08:00
Benoit Steiner
6d30683113 Fixed static assertion 2016-03-08 21:02:51 -08:00
Eugene Brevdo
5e7de771e3 Properly fix merge issues. 2016-03-08 17:35:05 -08:00
Benoit Steiner
46177c8d64 Replace std::vector with our own implementation, as using the stl when compiling with nvcc and avx enabled leads to many issues. 2016-03-08 16:37:27 -08:00
Benoit Steiner
6d6413f768 Simplified the full reduction code 2016-03-08 16:02:00 -08:00
Benoit Steiner
5a427a94a9 Fixed the tensor generator code 2016-03-08 13:28:06 -08:00
Benoit Steiner
a81b88bef7 Fixed the tensor concatenation code 2016-03-08 12:30:19 -08:00
Benoit Steiner
551ff11d0d Fixed the tensor layout swapping code 2016-03-08 12:28:10 -08:00
Benoit Steiner
8768c063f5 Fixed the tensor chipping code. 2016-03-08 12:26:49 -08:00
Benoit Steiner
e09eb835db Decoupled the packet type definition from the definition of the tensor ops. All the vectorization is now defined in the tensor evaluators. This will make it possible to relialably support devices with different packet types in the same compilation unit. 2016-03-08 12:07:33 -08:00
Benoit Steiner
3b614a2358 Use NumTraits::highest() and NumTraits::lowest() instead of the std::numeric_limits to make the tensor min and max functors more CUDA friendly. 2016-03-07 17:53:28 -08:00
Benoit Steiner
769685e74e Added the ability to pad a tensor using a non-zero value 2016-03-07 14:45:37 -08:00
Benoit Steiner
7f87cc3a3b Fix a couple of typos in the code. 2016-03-07 14:31:27 -08:00
Eugene Brevdo
5707004d6b Fix Eigen's building of sharded tests that use CUDA & more igamma/igammac bugfixes. 
0. Prior to this PR, not a single sharded CUDA test was actually being *run*.
Fixed that.

GPU tests are still failing for igamma/igammac.

1. Add calls for igamma/igammac to TensorBase
2. Fix up CUDA-specific calls of igamma/igammac
3. Add unit tests for digamma, igamma, igammac in CUDA.
 2016-03-07 14:08:56 -08:00
Benoit Steiner
9a54c3e32b Don't warn that msvc 2015 isn't c++11 compliant just because it doesn't claim to be. 2016-03-06 09:38:56 -08:00
Benoit Steiner
23aed8f2e4 Use EIGEN_PI instead of redefining our own constant PI 2016-03-05 08:04:45 -08:00
Benoit Steiner
ec35068edc Don't rely on the M_PI constant since not all compilers provide it. 2016-03-04 16:42:38 -08:00
Benoit Steiner
60d9df11c1 Fixed the computation of leading zeros when compiling with msvc. 2016-03-04 16:27:02 -08:00
Benoit Steiner
c561eeb7bf Don't use implicit type conversions in initializer lists since not all compilers support them. 2016-03-04 14:12:45 -08:00
Benoit Steiner
2c50fc878e Fixed a typo 2016-03-04 14:09:38 -08:00
Benoit Steiner
5cf4558c0a Added support for rounding, flooring, and ceiling to the tensor api 2016-03-03 12:36:55 -08:00
Benoit Steiner
68ac5c1738 Improved the performance of large outer reductions on cuda 2016-02-29 18:11:58 -08:00
Benoit Steiner
b2075cb7a2 Made the signature of the inner and outer reducers consistent 2016-02-29 10:53:38 -08:00
Benoit Steiner
3284842045 Optimized the performance of narrow reductions on CUDA devices 2016-02-29 10:48:16 -08:00
Benoit Steiner
609b3337a7 Print some information to stderr when a CUDA kernel fails 2016-02-27 20:42:57 +00:00
Benoit Steiner
ac2e6e0d03 Properly vectorized the random number generators 2016-02-26 13:52:24 -08:00
Benoit Steiner
caa54d888f Made the TensorIndexList usable on GPU without having to use the -relaxed-constexpr compilation flag 2016-02-26 12:38:18 -08:00
Benoit Steiner
c36c09169e Fixed a typo in the reduction code that could prevent large full reductionsx from running properly on old cuda devices. 2016-02-24 17:07:25 -08:00
Benoit Steiner
7a01cb8e4b Marked the And and Or reducers as stateless. 2016-02-24 16:43:01 -08:00
Benoit Steiner
1d9256f7db Updated the padding code to work with half floats 2016-02-23 05:51:22 +00:00
Benoit Steiner
72d2cf642e Deleted the coordinate based evaluation of tensor expressions, since it's hardly ever used and started to cause some issues with some versions of xcode. 2016-02-22 15:29:41 -08:00
Benoit Steiner
257b640463 Fixed compilation warning generated by clang 2016-02-21 22:43:37 -08:00
Benoit Steiner
96a24b05cc Optimized casting of tensors in the case where the casting happens to be a no-op 2016-02-21 11:16:15 -08:00
Benoit Steiner
203490017f Prevent unecessary Index to int conversions 2016-02-21 08:49:36 -08:00
Rasmus Munk Larsen
8eb127022b Get rid of duplicate code. 2016-02-19 16:33:30 -08:00
Rasmus Munk Larsen
d5e2ec7447 Speed up tensor FFT by up ~25-50%. 
Benchmark                          Base (ns)  New (ns) Improvement
------------------------------------------------------------------
BM_tensor_fft_single_1D_cpu/8            132       134     -1.5%
BM_tensor_fft_single_1D_cpu/9           1162      1229     -5.8%
BM_tensor_fft_single_1D_cpu/16           199       195     +2.0%
BM_tensor_fft_single_1D_cpu/17          2587      2267    +12.4%
BM_tensor_fft_single_1D_cpu/32           373       341     +8.6%
BM_tensor_fft_single_1D_cpu/33          5922      4879    +17.6%
BM_tensor_fft_single_1D_cpu/64           797       675    +15.3%
BM_tensor_fft_single_1D_cpu/65         13580     10481    +22.8%
BM_tensor_fft_single_1D_cpu/128         1753      1375    +21.6%
BM_tensor_fft_single_1D_cpu/129        31426     22789    +27.5%
BM_tensor_fft_single_1D_cpu/256         4005      3008    +24.9%
BM_tensor_fft_single_1D_cpu/257        70910     49549    +30.1%
BM_tensor_fft_single_1D_cpu/512         8989      6524    +27.4%
BM_tensor_fft_single_1D_cpu/513       165402    107751    +34.9%
BM_tensor_fft_single_1D_cpu/999       198293    115909    +41.5%
BM_tensor_fft_single_1D_cpu/1ki        21289     14143    +33.6%
BM_tensor_fft_single_1D_cpu/1k        361980    233355    +35.5%
BM_tensor_fft_double_1D_cpu/8            138       131     +5.1%
BM_tensor_fft_double_1D_cpu/9           1253      1133     +9.6%
BM_tensor_fft_double_1D_cpu/16           218       200     +8.3%
BM_tensor_fft_double_1D_cpu/17          2770      2392    +13.6%
BM_tensor_fft_double_1D_cpu/32           406       368     +9.4%
BM_tensor_fft_double_1D_cpu/33          6418      5153    +19.7%
BM_tensor_fft_double_1D_cpu/64           856       728    +15.0%
BM_tensor_fft_double_1D_cpu/65         14666     11148    +24.0%
BM_tensor_fft_double_1D_cpu/128         1913      1502    +21.5%
BM_tensor_fft_double_1D_cpu/129        36414     24072    +33.9%
BM_tensor_fft_double_1D_cpu/256         4226      3216    +23.9%
BM_tensor_fft_double_1D_cpu/257        86638     52059    +39.9%
BM_tensor_fft_double_1D_cpu/512         9397      6939    +26.2%
BM_tensor_fft_double_1D_cpu/513       203208    114090    +43.9%
BM_tensor_fft_double_1D_cpu/999       237841    125583    +47.2%
BM_tensor_fft_double_1D_cpu/1ki        20921     15392    +26.4%
BM_tensor_fft_double_1D_cpu/1k        455183    250763    +44.9%
BM_tensor_fft_single_2D_cpu/8           1051      1005     +4.4%
BM_tensor_fft_single_2D_cpu/9          16784     14837    +11.6%
BM_tensor_fft_single_2D_cpu/16          4074      3772     +7.4%
BM_tensor_fft_single_2D_cpu/17         75802     63884    +15.7%
BM_tensor_fft_single_2D_cpu/32         20580     16931    +17.7%
BM_tensor_fft_single_2D_cpu/33        345798    278579    +19.4%
BM_tensor_fft_single_2D_cpu/64         97548     81237    +16.7%
BM_tensor_fft_single_2D_cpu/65       1592701   1227048    +23.0%
BM_tensor_fft_single_2D_cpu/128       472318    384303    +18.6%
BM_tensor_fft_single_2D_cpu/129      7038351   5445308    +22.6%
BM_tensor_fft_single_2D_cpu/256      2309474   1850969    +19.9%
BM_tensor_fft_single_2D_cpu/257     31849182  23797538    +25.3%
BM_tensor_fft_single_2D_cpu/512     10395194   8077499    +22.3%
BM_tensor_fft_single_2D_cpu/513     144053843  104242541    +27.6%
BM_tensor_fft_single_2D_cpu/999     279885833  208389718    +25.5%
BM_tensor_fft_single_2D_cpu/1ki     45967677  36070985    +21.5%
BM_tensor_fft_single_2D_cpu/1k      619727095  456489500    +26.3%
BM_tensor_fft_double_2D_cpu/8           1110      1016     +8.5%
BM_tensor_fft_double_2D_cpu/9          17957     15768    +12.2%
BM_tensor_fft_double_2D_cpu/16          4558      4000    +12.2%
BM_tensor_fft_double_2D_cpu/17         79237     66901    +15.6%
BM_tensor_fft_double_2D_cpu/32         21494     17699    +17.7%
BM_tensor_fft_double_2D_cpu/33        357962    290357    +18.9%
BM_tensor_fft_double_2D_cpu/64        105179     87435    +16.9%
BM_tensor_fft_double_2D_cpu/65       1617143   1288006    +20.4%
BM_tensor_fft_double_2D_cpu/128       512848    419397    +18.2%
BM_tensor_fft_double_2D_cpu/129      7271322   5636884    +22.5%
BM_tensor_fft_double_2D_cpu/256      2415529   1922032    +20.4%
BM_tensor_fft_double_2D_cpu/257     32517952  24462177    +24.8%
BM_tensor_fft_double_2D_cpu/512     10724898   8287617    +22.7%
BM_tensor_fft_double_2D_cpu/513     146007419  108603266    +25.6%
BM_tensor_fft_double_2D_cpu/999     296351330  221885776    +25.1%
BM_tensor_fft_double_2D_cpu/1ki     59334166  48357539    +18.5%
BM_tensor_fft_double_2D_cpu/1k      666660132  483840349    +27.4%
 2016-02-19 16:29:23 -08:00
Benoit Steiner
46fc23f91c Print an error message to stderr when the initialization of the CUDA runtime fails. This helps debugging setup issues. 2016-02-19 13:44:22 -08:00
Benoit Steiner
670db7988d Updated the contraction code to make it compatible with half floats. 2016-02-19 13:03:26 -08:00
Benoit Steiner
180156ba1a Added support for tensor reductions on half floats 2016-02-19 10:05:59 -08:00
Benoit Steiner
f268db1c4b Added the ability to query the minor version of a cuda device 2016-02-19 16:31:04 +00:00
Benoit Steiner
f3352e0fb0 Don't make the array constructors explicit 2016-02-19 15:58:57 +00:00
Benoit Steiner
cd042dbbfd Fixed a bug in the tensor type converter 2016-02-19 15:03:26 +00:00
Benoit Steiner
de345eff2e Added a method to conjugate the content of a tensor or the result of a tensor expression. 2016-02-11 16:34:07 -08:00
Benoit Steiner
9a21b38ccc Worked around a few clang compilation warnings 2016-02-10 08:02:04 -08:00
Benoit Steiner
72ab7879f7 Fixed clang comilation warnings 2016-02-10 06:48:28 -08:00
Benoit Steiner
e88535634d Fixed some clang compilation warnings 2016-02-09 23:32:41 -08:00
Benoit Steiner
d69946183d Updated the TensorIntDivisor code to work properly on LLP64 systems 2016-02-08 21:03:59 -08:00
Benoit Steiner
4d4211c04e Avoid unecessary type conversions 2016-02-05 18:19:41 -08:00
Benoit Steiner
f535378995 Added support for vectorized type casting of int to char. 2016-02-03 18:58:29 -08:00
Benoit Steiner
4ab63a3f6f Fixed the initialization of the dummy member of the array class to make it compatible with pairs of element. 2016-02-03 17:23:07 -08:00
Benoit Steiner
1cbb79cdfd Made sure the dummy element of size 0 array is always intialized to silence some compiler warnings 2016-02-03 15:58:26 -08:00
Benoit Steiner
dc413dbe8a Merged in ville-k/eigen/explicit_long_constructors (pull request PR-158) 
Add constructor for long types.
 2016-02-02 20:58:06 -08:00
Ville Kallioniemi
783018d8f6 Use EIGEN_STATIC_ASSERT for backward compatibility. 2016-02-02 16:45:12 -07:00
Benoit Steiner
99cde88341 Don't try to use direct offsets when computing a tensor product, since the required stride isn't available. 2016-02-02 11:06:53 -08:00
Ville Kallioniemi
aedea349aa Replace separate low word constructors with a single templated constructor. 2016-02-01 20:25:02 -07:00
Ville Kallioniemi
f0fdefa96f Rebase to latest. 2016-02-01 19:32:31 -07:00
Benoit Steiner
6b5dff875e Made it possible to limit the number of blocks that will be used to evaluate a tensor expression on a CUDA device. This makesit possible to set aside streaming multiprocessors for other computations. 2016-02-01 12:46:32 -08:00
Benoit Steiner
e80ed948e1 Fixed a number of compilation warnings generated by the cuda tests 2016-01-31 20:09:41 -08:00
Benoit Steiner
6720b38fbf Fixed a few compilation warnings 2016-01-31 16:48:50 -08:00
Benoit Steiner
963f2d2a8f Marked several methods EIGEN_DEVICE_FUNC 2016-01-28 23:37:48 -08:00
Benoit Steiner
c5d25bf1d0 Fixed a couple of compilation warnings. 2016-01-28 23:15:45 -08:00
Gael Guennebaud
ddf64babde merge 2016-01-28 13:21:48 +01:00
Benoit Steiner
4bf9eaf77a Deleted an invalid assertion that prevented the assignment of empty tensors. 2016-01-27 17:09:30 -08:00
Benoit Steiner
291069e885 Fixed some compilation problems with nvcc + clang 2016-01-27 15:37:03 -08:00
Ville Kallioniemi
02db1228ed Add constructor for long types. 2016-01-26 23:41:01 -07:00
Benoit Steiner
e3a15a03a4 Don't explicitely evaluate the subexpression from TensorForcedEval::evalSubExprIfNeeded, as it will be done when executing the EvalTo subexpression 2016-01-24 23:04:50 -08:00
Benoit Steiner
bd207ce11e Added missing EIGEN_DEVICE_FUNC qualifier 2016-01-24 20:36:05 -08:00
Benoit Steiner
cb4e53ff7f Merged in ville-k/eigen/tensorflow_fix (pull request PR-153) 
Add ctor for long
 2016-01-22 19:11:31 -08:00
Benoit Steiner
3aeeca32af Leverage the new blocking code in the tensor contraction code. 2016-01-22 16:36:30 -08:00
Benoit Steiner
4beb447e27 Created a mechanism to enable contraction mappers to determine the best blocking strategy. 2016-01-22 14:37:26 -08:00
Gael Guennebaud
6a44ccb58b Backout changeset 690bc950f7 2016-01-22 15:03:53 +01:00
Ville Kallioniemi
9b6c72958a Update to latest default branch 2016-01-21 23:08:54 -07:00
Benoit Steiner
c33479324c Fixed a constness bug 2016-01-21 17:08:11 -08:00
Jan Prach
690bc950f7 fix clang warnings 
"braces around scalar initializer"
 2016-01-20 19:35:59 -08:00
Benoit Steiner
7ce932edd3 Small cleanup and small fix to the contraction of row major tensors 2016-01-20 18:12:08 -08:00
Benoit Steiner
47076bf00e Reduce the register pressure exerted by the tensor mappers whenever possible. This improves the performance of the contraction of a matrix with a vector by about 35%. 2016-01-20 14:51:48 -08:00
Ville Kallioniemi
2832175a68 Use explicitly 32 bit integer types in constructors. 2016-01-19 20:12:17 -07:00
Benoit Steiner
df79c00901 Improved the formatting of the code 2016-01-19 17:24:08 -08:00
Benoit Steiner
6d472d8375 Moved the contraction mapping code to its own file to make the code more manageable. 2016-01-19 17:22:05 -08:00
Benoit Steiner
b3b722905f Improved code indentation 2016-01-19 17:09:47 -08:00
Benoit Steiner
5b7713dd33 Record whether the underlying tensor storage can be accessed directly during the evaluation of an expression. 2016-01-19 17:05:10 -08:00
Ville Kallioniemi
63fb66f53a Add ctor for long 2016-01-17 21:25:36 -07:00
Benoit Steiner
34057cff23 Fixed a race condition that could affect some reductions on CUDA devices. 2016-01-15 15:11:56 -08:00
Benoit Steiner
0461f0153e Made it possible to compare tensor dimensions inside a CUDA kernel. 2016-01-15 11:22:16 -08:00
Benoit Steiner
aed4cb1269 Use warp shuffles instead of shared memory access to speedup the inner reduction kernel. 2016-01-14 21:45:14 -08:00
Benoit Steiner
8fe2532e70 Fixed a boundary condition bug in the outer reduction kernel 2016-01-14 09:29:48 -08:00
Benoit Steiner
9f013a9d86 Properly record the rank of reduced tensors in the tensor traits. 2016-01-13 14:24:37 -08:00
Benoit Steiner
79b69b7444 Trigger the optimized matrix vector path more conservatively. 2016-01-12 15:21:09 -08:00
Benoit Steiner
d920d57f38 Improved the performance of the contraction of a 2d tensor with a 1d tensor by a factor of 3 or more. This helps speedup LSTM neural networks. 2016-01-12 11:32:27 -08:00
Benoit Steiner
bd7d901da9 Reverted a previous change that tripped nvcc when compiling in debug mode. 2016-01-11 17:49:44 -08:00
Benoit Steiner
c5e6900400 Silenced a few compilation warnings. 2016-01-11 17:06:39 -08:00
Benoit Steiner
f894736d61 Updated the tensor traits: the alignment is not part of the Flags enum anymore 2016-01-11 16:42:18 -08:00
Benoit Steiner
4f7714d72c Enabled the use of fixed dimensions from within a cuda kernel. 2016-01-11 16:01:00 -08:00
Benoit Steiner
01c55d37e6 Deleted unused variable. 2016-01-11 15:53:19 -08:00
Benoit Steiner
0504c56ea7 Silenced a nvcc compilation warning 2016-01-11 15:49:21 -08:00
Benoit Steiner
b523771a24 Silenced several compilation warnings triggered by nvcc. 2016-01-11 14:25:43 -08:00
Benoit Steiner
2c3b13eded Merged in jeremy_barnes/eigen/shader-model-3.0 (pull request PR-152) 
Alternative way of forcing instantiation of device kernels without causing warnings or requiring device to device kernel invocations.
 2016-01-11 11:43:37 -08:00
Benoit Steiner
2ccb1c8634 Fixed a bug in the dispatch of optimized reduction kernels. 2016-01-11 10:36:37 -08:00
Benoit Steiner
780623261e Re-enabled the optimized reduction CUDA code. 2016-01-11 09:07:14 -08:00
Jeremy Barnes
91678f489a Cleaned up double-defined macro from last commit 2016-01-10 22:44:45 -05:00
Jeremy Barnes
403a7cb6c3 Alternative way of forcing instantiation of device kernels without 
causing warnings or requiring device to device kernel invocations.

This allows Tensorflow to work on SM 3.0 (ie, Amazon EC2) machines.
 2016-01-10 22:39:13 -05:00
Benoit Steiner
e76904af1b Simplified the dispatch code. 2016-01-08 16:50:57 -08:00
Benoit Steiner
d726e864ac Made it possible to use array of size 0 on CUDA devices 2016-01-08 16:38:14 -08:00
Benoit Steiner
3358dfd5dd Reworked the dispatch of optimized cuda reduction kernels to workaround a nvcc bug that prevented the code from compiling in optimized mode in some cases 2016-01-08 16:28:53 -08:00
Benoit Steiner
53749ff415 Prevent nvcc from miscompiling the cuda metakernel. Unfortunately this reintroduces some compulation warnings but it's much better than having to deal with random assertion failures. 2016-01-08 13:53:40 -08:00
Benoit Steiner
6639b7d6e8 Removed a couple of partial specialization that confuse nvcc and result in errors such as this: 
error: more than one partial specialization matches the template argument list of class "Eigen::internal::get<3, Eigen::internal::numeric_list<std::size_t, 1UL, 1UL, 1UL, 1UL>>"
            "Eigen::internal::get<n, Eigen::internal::numeric_list<T, a, as...>>"
            "Eigen::internal::get<n, Eigen::internal::numeric_list<T, as...>>"
 2016-01-07 18:45:19 -08:00
Benoit Steiner
0cb2ca5de2 Fixed a typo. 2016-01-06 18:50:28 -08:00
Benoit Steiner
213459d818 Optimized the performance of broadcasting of scalars. 2016-01-06 18:47:45 -08:00
Benoit Steiner
cfff40b1d4 Improved the performance of reductions on CUDA devices 2016-01-04 17:25:00 -08:00
Benoit Steiner
515dee0baf Added a 'divup' util to compute the floor of the quotient of two integers 2016-01-04 16:29:26 -08:00
Gael Guennebaud
978c379ed7 Add missing ctor from uint 2015-12-30 12:52:38 +01:00
Eugene Brevdo
f7362772e3 Add digamma for CPU + CUDA. Includes tests. 2015-12-24 21:15:38 -08:00
Benoit Steiner
bdcbc66a5c Don't attempt to vectorize mean reductions of integers since we can't use 
SSE or AVX instructions to divide 2 integers.
 2015-12-22 17:51:55 -08:00
Benoit Steiner
a1e08fb2a5 Optimized the configuration of the outer reduction cuda kernel 2015-12-22 16:30:10 -08:00
Benoit Steiner
9c7d96697b Added missing define 2015-12-22 16:11:07 -08:00
Benoit Steiner
e7e6d01810 Made sure the optimized gpu reduction code is actually compiled. 2015-12-22 15:07:33 -08:00
Benoit Steiner
b5d2078c4a Optimized outer reduction on GPUs. 2015-12-22 15:06:17 -08:00
Benoit Steiner
1c3e78319d Added missing const 2015-12-21 15:05:01 -08:00