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
b2100b83ad
Made sure to include the <random> header file when compiling with visual studio
2016-03-09 16:03:16 -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
05bbca079a
Turn on some of the cxx11 features when compiling with visual studio 2015
2016-03-05 10:52:08 -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
5cd00068c0
include <iostream> in the tensor header since we now use it to better report cuda initialization errors
2016-02-22 13:59:03 -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
Benoit Steiner
1b82969559
Add alignment requirement for local buffer used by the slicing op.
2015-12-18 14:36:35 -08:00
Benoit Steiner
75a7fa1919
Doubled the speed of full reductions on GPUs.
2015-12-18 14:07:31 -08:00
Benoit Steiner
8dd17cbe80
Fixed a clang compilation warning triggered by the use of arrays of size 0.
2015-12-17 14:00:33 -08:00
Benoit Steiner
4aac55f684
Silenced some compilation warnings triggered by nvcc
2015-12-17 13:39:01 -08:00
Benoit Steiner
40e6250fc3
Made it possible to run tensor chipping operations on CUDA devices
2015-12-17 13:29:08 -08:00
Benoit Steiner
2ca55a3ae4
Fixed some compilation error triggered by the tensor code with msvc 2008
2015-12-16 20:45:58 -08:00
Benoit Steiner
17352e2792
Made the entire TensorFixedSize api callable from a CUDA kernel.
2015-12-14 15:20:31 -08:00
Benoit Steiner
75e19fc7ca
Marked the tensor constructors as EIGEN_DEVICE_FUNC: This makes it possible to call them from a CUDA kernel.
2015-12-14 15:12:55 -08:00
Gael Guennebaud
ca39b1546e
Merged in ebrevdo/eigen (pull request PR-148)
...
Add special functions to eigen: lgamma, erf, erfc.
2015-12-11 11:52:09 +01:00
Benoit Steiner
6af52a1227
Fixed a typo in the constructor of tensors of rank 5.
2015-12-10 23:31:12 -08:00
Benoit Steiner
8e00ea9a92
Fixed the coefficient accessors use for the 2d and 3d case when compiling without cxx11 support.
2015-12-10 22:45:10 -08:00
Eugene Brevdo
fa4f933c0f
Add special functions to Eigen: lgamma, erf, erfc.
...
Includes CUDA support and unit tests.
2015-12-07 15:24:49 -08:00
Benoit Steiner
7dfe75f445
Fixed compilation warnings
2015-12-07 08:12:30 -08:00
Benoit Steiner
f4ca8ad917
Use signed integers instead of unsigned ones more consistently in the codebase.
2015-12-04 18:14:16 -08:00
Benoit Steiner
490d26e4c1
Use integers instead of std::size_t to encode the number of dimensions in the Tensor class since most of the code currently already use integers.
2015-12-04 10:15:11 -08:00
Benoit Steiner
d20efc974d
Made it possible to use the sigmoid functor within a CUDA kernel.
2015-12-04 09:38:15 -08:00
Benoit Steiner
029052d276
Deleted redundant code
2015-12-03 17:08:47 -08:00