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5016 Commits

Author SHA1 Message Date
Gael Guennebaud
3ecb343dc3 Fix regression in X = (X*X.transpose())/s with X rectangular by deferring resizing of the destination after the creation of the evaluator of the source expression. 2016-10-26 22:50:41 +02:00
Gael Guennebaud
97feea9d39 add a generic EIGEN_HAS_CXX11 2016-10-26 15:53:13 +02:00
Gael Guennebaud
ca6a2a5248 Fix warning with ICC 2016-10-26 14:13:05 +02:00
Gael Guennebaud
b15a5dc3f4 Fix ICC warnings 2016-10-25 22:20:24 +02:00
Gael Guennebaud
aad72f3c6d Add missing inline keywords 2016-10-25 20:20:09 +02:00
Benoit Steiner
3e194a6a73 Fixed a typo 2016-10-25 08:42:15 -07:00
Gael Guennebaud
58146be99b bug #1004: one more rewrite of LinSpaced for floating point numbers to guarantee both interpolation and monotonicity. 
This version simply does low+i*step plus a branch to return high if i==size-1.
Vectorization is accomplished with a branch and the help of pinsertlast.
Some quick benchmark revealed that the overhead is really marginal, even when filling small vectors.
 2016-10-25 16:53:09 +02:00
Gael Guennebaud
13fc18d3a2 Add a pinsertlast function replacing the last entry of a packet by a scalar. 
(useful to vectorize LinSpaced)
 2016-10-25 16:48:49 +02:00
Gael Guennebaud
2634f9386c bug #1333: fix bad usage of const_cast_derived. Better use .data() for that purpose. 2016-10-24 22:22:35 +02:00
Gael Guennebaud
9e8f07d7b5 Cleanup ArrayWrapper and MatrixWrapper by removing redundant accessors. 2016-10-24 22:16:48 +02:00
Gael Guennebaud
b027d7a8cf bug #1004: remove the inaccurate "sequential" path for LinSpaced, mark respective function as deprecated, and enforce strict interpolation of the higher range using a correction term. 
Now, even with floating point precision, both the 'low' and 'high' bounds are exactly reproduced at i=0 and i=size-1 respectively.
 2016-10-24 20:27:21 +02:00
Benoit Steiner
b11aab5fcc Merged in benoitsteiner/opencl (pull request PR-238) 
Added support for OpenCL to the Tensor Module
 2016-10-24 15:30:45 +00:00
Gael Guennebaud
53c77061f0 bug #698: rewrite LinSpaced for integer scalar types to avoid overflow and guarantee an even spacing when possible. 
Otherwise, the "high" bound is implicitly lowered to the largest value allowing for an even distribution.
This changeset also disable vectorization for this integer path.
 2016-10-24 15:50:27 +02:00
Gael Guennebaud
40f62974b7 bug #1328: workaround a compilation issue with gcc 4.2 2016-10-20 19:19:37 +02:00
Benoit Steiner
cf20b30d65 Merge latest updates from trunk 2016-10-20 09:42:05 -07:00
Benoit Steiner
d3943cd50c Fixed a few typos in the ternary tensor expressions types 2016-10-19 12:56:12 -07:00
Mehdi Goli
8fb162fc85 Fixing the typo regarding missing #if needed for proper handling of exceptions in Eigen/Core. 2016-10-16 12:52:34 +01:00
Luke Iwanski
2e188dd4d4 Merged ComputeCpp to default. 2016-10-14 16:47:40 +01:00
Mehdi Goli
15380f9a87 Applyiing Benoit's comment to return the missing line back in Eigen/Core 2016-10-14 16:39:41 +01:00
Gael Guennebaud
692b30ca95 Fix previous merge. 2016-10-14 17:16:28 +02:00
Gael Guennebaud
050c681bdd Merged in rmlarsen/eigen2 (pull request PR-232) 
Improve performance of parallelized matrix multiply for rectangular matrices
 2016-10-14 14:51:09 +00:00
Luke Iwanski
e742da8b28 Merged ComputeCpp into default. 2016-10-14 13:36:51 +01:00
Mehdi Goli
524fa4c46f Reducing the code by generalising sycl backend functions/structs. 2016-10-14 12:09:55 +01:00
Benoit Steiner
737e4152c3 Merged in lukier/eigen (pull request PR-234) 
Enabling CUDA in Geometry
 2016-10-13 18:09:28 +00:00
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
Gael Guennebaud
e74612b9a0 Remove double ;; 2016-10-12 22:49:47 +02:00
Gael Guennebaud
f939c351cb Fix SPQR for rectangular matrices 2016-10-12 22:39:33 +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
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
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
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
Gael Guennebaud
80b5133789 Fix compilation of qr.inverse() for column and full pivoting variants. 2016-10-06 09:55:50 +02:00
Benoit Steiner
ae1385c7e4 Pull the latest updates from trunk 2016-10-05 14:54:36 -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
Benoit Steiner
881b90e984 Use explicit type casting to generate packets of zeros. 2016-10-04 08:23:38 -07:00
Benoit Steiner
409e887d78 Added support for constand std::complex numbers on GPU 2016-10-03 11:06:24 -07:00
Gael Guennebaud
9d6d0dff8f bug #1317: fix performance regression with some Block expressions and clang by helping it to remove dead code. 
The trick is to get rid of the nested expression in the evaluator by copying only the required information (here, the strides).
 2016-10-01 15:37:00 +02:00
Gael Guennebaud
8b84801f7f bug #1310: workaround a compilation regression from 3.2 regarding triangular * homogeneous 2016-09-30 22:49:59 +02:00
Gael Guennebaud
67b4f45836 Fix angle range 2016-09-30 12:46:33 +02:00