Benoit Steiner
|
deea866bbd
|
Added tests to cover the new rounding, flooring and ceiling tensor operations.
|
2016-03-03 12:38:02 -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
|
dac58d7c35
|
Added a test to validate the conversion of half floats into floats on Kepler GPUs.
Restricted the testing of the random number generation code to GPU architecture greater than or equal to 3.5.
|
2016-03-03 10:37:25 -08:00 |
|
Benoit Steiner
|
1032441c6f
|
Enable partial support for half floats on Kepler GPUs.
|
2016-03-03 10:34:20 -08:00 |
|
Benoit Steiner
|
1da10a7358
|
Enable the conversion between floats and half floats on older GPUs that support it.
|
2016-03-03 10:33:20 -08:00 |
|
Benoit Steiner
|
2de8cc9122
|
Merged in ebrevdo/eigen (pull request PR-167)
Add infinity() support to numext::numeric_limits, use it in lgamma.
I tested the code on my gtx-titan-black gpu, and it appears to work as expected.
|
2016-03-03 09:42:12 -08:00 |
|
Eugene Brevdo
|
ab3dc0b0fe
|
Small bugfix to numeric_limits for CUDA.
|
2016-03-02 21:48:46 -08:00 |
|
Eugene Brevdo
|
6afea46838
|
Add infinity() support to numext::numeric_limits, use it in lgamma.
This makes the infinity access a __device__ function, removing
nvcc warnings.
|
2016-03-02 21:35:48 -08:00 |
|
Gael Guennebaud
|
3fccef6f50
|
bug #537: fix compilation with Apples's compiler
|
2016-03-02 13:22:46 +01:00 |
|
Benoit Steiner
|
fedaf19262
|
Pulled latest updates from trunk
|
2016-03-01 06:15:44 -08:00 |
|
Gael Guennebaud
|
dfa80b2060
|
Compilation fix
|
2016-03-01 12:48:56 +01:00 |
|
Gael Guennebaud
|
bee9efc203
|
Compilation fix
|
2016-03-01 12:47:27 +01:00 |
|
Benoit Steiner
|
68ac5c1738
|
Improved the performance of large outer reductions on cuda
|
2016-02-29 18:11:58 -08:00 |
|
Benoit Steiner
|
56a3ada670
|
Added benchmarks for full reduction
|
2016-02-29 14:57:52 -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 |
|
Gael Guennebaud
|
e9bea614ec
|
Fix shortcoming in fixed-value deduction of startRow/startCol
|
2016-02-29 10:31:27 +01:00 |
|
Benoit Steiner
|
609b3337a7
|
Print some information to stderr when a CUDA kernel fails
|
2016-02-27 20:42:57 +00:00 |
|
Benoit Steiner
|
1031b31571
|
Improved the README
|
2016-02-27 20:22:04 +00:00 |
|
Gael Guennebaud
|
8e6faab51e
|
bug #1172: make valuePtr and innderIndexPtr properly return null for empty matrices.
|
2016-02-27 14:55:40 +01:00 |
|
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
|
93485d86bc
|
Added benchmarks for type casting of float16
|
2016-02-26 12:24:58 -08:00 |
|
Benoit Steiner
|
002824e32d
|
Added benchmarks for fp16
|
2016-02-26 12:21:25 -08:00 |
|
Benoit Steiner
|
2cd32cad27
|
Reverted previous commit since it caused more problems than it solved
|
2016-02-26 13:21:44 +00:00 |
|
Benoit Steiner
|
d9d05dd96e
|
Fixed handling of long doubles on aarch64
|
2016-02-26 04:13:58 -08:00 |
|
Benoit Steiner
|
af199b4658
|
Made the CUDA architecture level a build setting.
|
2016-02-25 09:06:18 -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 |
|
Gael Guennebaud
|
91e1375ba9
|
merge
|
2016-02-23 11:09:05 +01:00 |
|
Gael Guennebaud
|
055000a424
|
Fix startRow()/startCol() for dense Block with direct access:
the initial implementation failed for empty rows/columns for which are ambiguous.
|
2016-02-23 11:07:59 +01:00 |
|
Benoit Steiner
|
1d9256f7db
|
Updated the padding code to work with half floats
|
2016-02-23 05:51:22 +00:00 |
|
Benoit Steiner
|
8cb9bfab87
|
Extended the tensor benchmark suite to support types other than floats
|
2016-02-23 05:28:02 +00:00 |
|
Benoit Steiner
|
f442a5a5b3
|
Updated the tensor benchmarking code to work with compilers that don't support cxx11.
|
2016-02-23 04:15:48 +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
|
6270d851e3
|
Declare the half float type as arithmetic.
|
2016-02-22 13:59:33 -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
|
584832cb3c
|
Implemented the ptranspose function on half floats
|
2016-02-21 12:44:53 -08:00 |
|
Benoit Steiner
|
e644f60907
|
Pulled latest updates from trunk
|
2016-02-21 20:24:59 +00:00 |
|
Benoit Steiner
|
95fceb6452
|
Added the ability to compute the absolute value of a half float
|
2016-02-21 20:24:11 +00:00 |
|
Benoit Steiner
|
ed69cbeef0
|
Added some debugging information to the test to figure out why it fails sometimes
|
2016-02-21 11:20:20 -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 |
|
Benoit Steiner
|
9ff269a1d3
|
Moved some of the fp16 operators outside the Eigen namespace to workaround some nvcc limitations.
|
2016-02-20 07:47:23 +00:00 |
|
Benoit Steiner
|
1e6fe6f046
|
Fixed the float16 tensor test.
|
2016-02-20 07:44:17 +00:00 |
|
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 |
|
Gael Guennebaud
|
d90a2dac5e
|
merge
|
2016-02-19 23:01:27 +01:00 |
|
Gael Guennebaud
|
485823b5f5
|
Add COD and BDCSVD in list of benched solvers.
|
2016-02-19 23:00:33 +01:00 |
|