Benoit Steiner
d0ee2267d6
Relaxed the resizing checks so that they don't fail with gcc >= 5.3
2016-10-13 10:59:46 -07:00
Robert Lukierski
a94791b69a
Fixes for min and abs after Benoit's comments, switched to numext.
2016-10-13 15:00:22 +01:00
Avi Ginsburg
ac63d6891c
Patch to allow VS2015 & CUDA 8.0 to compile with Eigen included. I'm not sure
...
whether to limit the check to this compiler combination
(` || (EIGEN_COMP_MSVC == 1900 && __CUDACC_VER__) `)
or to leave it as it is. I also don't know if this will have any affect on
including Eigen in device code (I'm not in my current project).
2016-10-13 08:47:32 +00:00
Benoit Steiner
7e4a6754b2
Merged eigen/eigen into default
2016-10-12 22:42:33 -07:00
Benoit Steiner
38b6048e14
Deleted redundant implementation of predux
2016-10-12 14:37:56 -07:00
Gael Guennebaud
e74612b9a0
Remove double ;;
2016-10-12 22:49:47 +02:00
Benoit Steiner
78d2926508
Merged eigen/eigen into default
2016-10-12 13:46:29 -07:00
Benoit Steiner
2e2f48e30e
Take advantage of AVX512 instructions whenever possible to speedup the processing of 16 bit floats.
2016-10-12 13:45:39 -07:00
Gael Guennebaud
f939c351cb
Fix SPQR for rectangular matrices
2016-10-12 22:39:33 +02:00
Gael Guennebaud
091d373ee9
Fix outer-stride.
2016-10-12 21:47:52 +02:00
Robert Lukierski
471075f7ad
Fixes min() warnings.
2016-10-12 18:59:05 +01:00
Gael Guennebaud
5c366fe1d7
Merged in rmlarsen/eigen (pull request PR-230)
...
Fix a bug in psqrt for SSE and AVX when EIGEN_FAST_MATH=1
2016-10-12 16:30:51 +00:00
Robert Lukierski
86711497c4
Adding EIGEN_DEVICE_FUNC in the Geometry module.
...
Additional CUDA necessary fixes in the Core (mostly usage of
EIGEN_USING_STD_MATH).
2016-10-12 16:35:17 +01:00
Rasmus Munk Larsen
47150af1c8
Fix copy-paste error: Must use _mm256_cmp_ps for AVX.
2016-10-12 08:34:39 -07:00
Gael Guennebaud
89e315152c
bug #1325 : fix compilation on NEON with clang
2016-10-12 16:55:47 +02:00
Benoit Steiner
7f0599b6eb
Manually define int16_t and uint16_t when compiling with Visual Studio
2016-10-08 22:56:32 -07:00
Benoit Steiner
5727e4d89c
Reenabled the use of variadic templates on tegra x1 provides that the latest version (i.e. JetPack 2.3) is used.
2016-10-08 22:19:03 +00:00
Benoit Steiner
5266ff8966
Cleaned up a regression test
2016-10-08 19:12:44 +00:00
Benoit Steiner
5c68051cd7
Merge the content of the ComputeCpp branch into the default branch
2016-10-07 11:04:16 -07:00
Gael Guennebaud
4860727ac2
Remove static qualifier of free-functions (inline is enough and this helps ICC to find the right overload)
2016-10-07 09:21:12 +02:00
Benoit Steiner
507b661106
Renamed predux_half into predux_downto4
2016-10-06 17:57:04 -07:00
Benoit Steiner
a498ff7df6
Fixed incorrect comment
2016-10-06 15:27:27 -07:00
Benoit Steiner
8ba3c41fcf
Revergted unecessary change
2016-10-06 15:12:15 -07:00
Benoit Steiner
a7473d6d5a
Fixed compilation error with gcc >= 5.3
2016-10-06 14:33:22 -07:00
Benoit Steiner
5e64cea896
Silenced a compilation warning
2016-10-06 14:24:17 -07:00
Benoit Steiner
33fba3f08d
Merged in rryan/eigen/tensorfunctors (pull request PR-233)
...
Fully support complex types in SumReducer and MeanReducer when building for CUDA by using scalar_sum_op and scalar_product_op instead of operator+ and operator*.
2016-10-06 12:29:19 -07:00
RJ Ryan
bfc264abe8
Add a test that GPU complex product reductions match CPU reductions.
2016-10-06 11:10:14 -07:00
RJ Ryan
e2e9cdd169
Fully support complex types in SumReducer and MeanReducer when building for CUDA by using scalar_sum_op and scalar_product_op instead of operator+ and operator*.
2016-10-06 10:49:48 -07:00
Benoit Steiner
d485d12c51
Added missing AVX intrinsics for fp16: in particular, implemented predux which is required by the matrix-vector code.
2016-10-06 10:41:03 -07:00
Rasmus Munk Larsen
48c635e223
Add a simple cost model to prevent Eigen's parallel GEMM from using too many threads when the inner dimension is small.
...
Timing for square matrices is unchanged, but both CPU and Wall time are significantly improved for skinny matrices. The benchmarks below are for multiplying NxK * KxN matrices with test names of the form BM_OuterishProd/N/K.
Improvements in Wall time:
Run on [redacted] (12 X 3501 MHz CPUs); 2016-10-05T17:40:02.462497196-07:00
CPU: Intel Haswell with HyperThreading (6 cores) dL1:32KB dL2:256KB dL3:15MB
Benchmark Base (ns) New (ns) Improvement
------------------------------------------------------------------
BM_OuterishProd/64/1 3088 1610 +47.9%
BM_OuterishProd/64/4 3562 2414 +32.2%
BM_OuterishProd/64/32 8861 7815 +11.8%
BM_OuterishProd/128/1 11363 6504 +42.8%
BM_OuterishProd/128/4 11128 9794 +12.0%
BM_OuterishProd/128/64 27691 27396 +1.1%
BM_OuterishProd/256/1 33214 28123 +15.3%
BM_OuterishProd/256/4 34312 36818 -7.3%
BM_OuterishProd/256/128 174866 176398 -0.9%
BM_OuterishProd/512/1 7963684 104224 +98.7%
BM_OuterishProd/512/4 7987913 112867 +98.6%
BM_OuterishProd/512/256 8198378 1306500 +84.1%
BM_OuterishProd/1k/1 7356256 324432 +95.6%
BM_OuterishProd/1k/4 8129616 331621 +95.9%
BM_OuterishProd/1k/512 27265418 7517538 +72.4%
Improvements in CPU time:
Run on [redacted] (12 X 3501 MHz CPUs); 2016-10-05T17:40:02.462497196-07:00
CPU: Intel Haswell with HyperThreading (6 cores) dL1:32KB dL2:256KB dL3:15MB
Benchmark Base (ns) New (ns) Improvement
------------------------------------------------------------------
BM_OuterishProd/64/1 6169 1608 +73.9%
BM_OuterishProd/64/4 7117 2412 +66.1%
BM_OuterishProd/64/32 17702 15616 +11.8%
BM_OuterishProd/128/1 45415 6498 +85.7%
BM_OuterishProd/128/4 44459 9786 +78.0%
BM_OuterishProd/128/64 110657 109489 +1.1%
BM_OuterishProd/256/1 265158 28101 +89.4%
BM_OuterishProd/256/4 274234 183885 +32.9%
BM_OuterishProd/256/128 1397160 1408776 -0.8%
BM_OuterishProd/512/1 78947048 520703 +99.3%
BM_OuterishProd/512/4 86955578 1349742 +98.4%
BM_OuterishProd/512/256 74701613 15584661 +79.1%
BM_OuterishProd/1k/1 78352601 3877911 +95.1%
BM_OuterishProd/1k/4 78521643 3966221 +94.9%
BM_OuterishProd/1k/512 258104736 89480530 +65.3%
2016-10-06 10:33:10 -07:00
Benoit Steiner
9f3276981c
Enabling AVX512 should also enable AVX2.
2016-10-06 10:29:48 -07:00
Gael Guennebaud
80b5133789
Fix compilation of qr.inverse() for column and full pivoting variants.
2016-10-06 09:55:50 +02:00
Benoit Steiner
4131074818
Deleted unecessary CMakeLists.txt file
2016-10-05 18:54:35 -07:00
Benoit Steiner
cb5cd69872
Silenced a compilation warning.
2016-10-05 18:50:53 -07:00
Benoit Steiner
78b569f685
Merged latest updates from trunk
2016-10-05 18:48:55 -07:00
Benoit Steiner
9c2b6c049b
Silenced a few compilation warnings
2016-10-05 18:37:31 -07:00
Benoit Steiner
6f3cd529af
Pulled latest updates from trunk
2016-10-05 18:31:43 -07:00
Benoit Steiner
d7f9679a34
Fixed a couple of compilation warnings
2016-10-05 15:00:32 -07:00
Benoit Steiner
ae1385c7e4
Pull the latest updates from trunk
2016-10-05 14:54:36 -07:00
Benoit Steiner
73b0012945
Fixed compilation warnings
2016-10-05 14:24:24 -07:00
Benoit Steiner
c84084c0c0
Fixed compilation warning
2016-10-05 14:15:41 -07:00
Benoit Steiner
4387433acf
Increased the robustness of the reduction tests on fp16
2016-10-05 10:42:41 -07:00
Benoit Steiner
aad20d700d
Increase the tolerance to numerical noise.
2016-10-05 10:39:24 -07:00
Benoit Steiner
8b69d5d730
::rand() returns a signed integer on win32
2016-10-05 08:55:02 -07:00
Benoit Steiner
ed7a220b04
Fixed a typo that impacts windows builds
2016-10-05 08:51:31 -07:00
Benoit Steiner
ceee1c008b
Silenced compilation warning
2016-10-04 18:47:53 -07:00
Benoit Steiner
698ff69450
Properly characterize the CUDA packet primitives for fp16 as device only
2016-10-04 16:53:30 -07:00
Rasmus Munk Larsen
7f67e6dfdb
Update comment for fast sqrt.
2016-10-04 15:09:11 -07:00
Rasmus Munk Larsen
765615609d
Update comment for fast sqrt.
2016-10-04 15:08:41 -07:00
Rasmus Munk Larsen
3ed67cb0bb
Fix a bug in the implementation of Carmack's fast sqrt algorithm in Eigen (enabled by EIGEN_FAST_MATH), which causes the vectorized parts of the computation to return -0.0 instead of NaN for negative arguments.
...
Benchmark speed in Giga-sqrts/s
Intel(R) Xeon(R) CPU E5-1650 v3 @ 3.50GHz
-----------------------------------------
SSE AVX
Fast=1 2.529G 4.380G
Fast=0 1.944G 1.898G
Fast=1 fixed 2.214G 3.739G
This table illustrates the worst case in terms speed impact: It was measured by repeatedly computing the sqrt of an n=4096 float vector that fits in L1 cache. For large vectors the operation becomes memory bound and the differences between the different versions almost negligible.
2016-10-04 14:22:56 -07:00