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Author SHA1 Message Date
Eugene Zhulenev
01654d97fa Prevent potential division by zero in TensorExecutor 2019-05-17 14:02:25 -07:00
Eugene Zhulenev
96a276803c Always evaluate Tensor expressions with broadcasting via tiled evaluation code path 2019-05-16 16:15:45 -07:00
Rasmus Munk Larsen
ab0a30e429 Make Eigen build with cuda 10 and clang. 2019-05-15 13:32:15 -07:00
Rasmus Larsen
c8d8d5c0fc Merged in rmlarsen/eigen_threadpool (pull request PR-640) 
Fix deadlocks in thread pool.

Approved-by: Eugene Zhulenev <ezhulenev@google.com>
 2019-05-13 20:04:35 +00:00
Christoph Hertzberg
4ccd1ece92 bug #1707: Fix deprecation warnings, or disable warnings when testing deprecated functions 2019-05-10 14:57:05 +02:00
Rasmus Munk Larsen
e5ac8cbd7a A) fix deadlocks in thread pool caused by EventCount 
This fixed 2 deadlocks caused by sloppiness in the EventCount logic.
Both most likely were introduced by cl/236729920 which includes the new EventCount algorithm:
01da8caf00

bug #1 (Prewait):
Prewait must not consume existing signals.
Consider the following scenario.
There are 2 thread pool threads (1 and 2) and 1 external thread (3). RunQueue is empty.
Thread 1 checks the queue, calls Prewait, checks RunQueue again and now is going to call CommitWait.
Thread 2 checks the queue and now is going to call Prewait.
Thread 3 submits 2 tasks, EventCount signals is set to 1 because only 1 waiter is registered the second signal is discarded).
Now thread 2 resumes and calls Prewait and takes away the signal.
Thread 1 resumes and calls CommitWait, there are no pending signals anymore, so it blocks.
As the result we have 2 tasks, but only 1 thread is running.

bug #2 (CancelWait):
CancelWait must not take away a signal if it's not sure that the signal was meant for this thread.
When one thread blocks and another submits a new task concurrently, the EventCount protocol guarantees only the following properties (similar to the Dekker's algorithm):
(a) the registered waiter notices presence of the new task and does not block
(b) the signaler notices presence of the waiters and wakes it
(c) both the waiter notices presence of the new task and signaler notices presence of the waiter
[it's only that both of them do not notice each other must not be possible, because it would lead to a deadlock]
CancelWait is called for cases (a) and (c). For case (c) it is OK to take the notification signal away, but it's not OK for (a) because nobody queued a signals for us and we take away a signal meant for somebody else.
Consider:
Thread 1 calls Prewait, checks RunQueue, it's empty, now it's going to call CommitWait.
Thread 3 submits 2 tasks, EventCount signals is set to 1 because only 1 waiter is registered the second signal is discarded).
Thread 2 calls Prewait, checks RunQueue, discovers the tasks, calls CancelWait and consumes the pending signal (meant for thread 1).
Now Thread 1 resumes and calls CommitWait, since there are no signals it blocks.
As the result we have 2 tasks, but only 1 thread is running.

Both deadlocks are only a problem if the tasks require parallelism. Most computational tasks do not require parallelism, i.e. a single thread will run task 1, finish it and then dequeue and run task 2.

This fix undoes some of the sloppiness in the EventCount that was meant to reduce CPU consumption by idle threads, because we now have more threads running in these corner cases. But we still don't have pthread_yield's and maybe the strictness introduced by this change will actually help to reduce tail latency because we will have threads running when we actually need them running.



B) fix deadlock in thread pool caused by RunQueue

This fixed a deadlock caused by sloppiness in the RunQueue logic.
Most likely this was introduced with the non-blocking thread pool.
The deadlock only affects workloads that require parallelism.
Most computational tasks don't require parallelism.

PopBack must not fail spuriously. If it does, it can effectively lead to single thread consuming several wake up signals.
Consider 2 worker threads are blocked.
External thread submits a task. One of the threads is woken.
It tries to steal the task, but fails due to a spurious failure in PopBack (external thread submits another task and holds the lock).
The thread executes blocking protocol again (it won't block because NonEmptyQueueIndex is precise and the thread will discover pending work, but it has called PrepareWait).
Now external thread submits another task and signals EventCount again.
The signal is consumed by the first thread again. But now we have 2 tasks pending but only 1 worker thread running.

It may be possible to fix this in a different way: make EventCount::CancelWait forward wakeup signal to a blocked thread rather then consuming it. But this looks more complex and I am not 100% that it will fix the bug.
It's also possible to have 2 versions of PopBack: one will do try_to_lock and another won't. Then worker threads could first opportunistically check all queues with try_to_lock, and only use the blocking version before blocking. But let's first fix the bug with the simpler change.
 2019-05-08 10:16:46 -07:00
Christoph Hertzberg
e6667a7060 Fix stupid shadow-warnings (with old clang versions) 2019-05-07 18:32:19 +02:00
Christoph Hertzberg
e54dc24d62 Restore C++03 compatibility 2019-05-07 18:30:44 +02:00
Rasmus Larsen
ac50afaffa Merged in ezhulenev/eigen-01 (pull request PR-633) 
Check if gpu_assert was overridden in TensorGpuHipCudaDefines
 2019-04-29 16:29:35 +00:00
Eugene Zhulenev
01d7e6ee9b Check if gpu_assert was overridden in TensorGpuHipCudaDefines 2019-04-25 11:19:17 -07:00
Eugene Zhulenev
8ead5bb3d8 Fix doxygen warnings to enable statis code analysis 2019-04-24 12:42:28 -07:00
Rasmus Munk Larsen
144ca33321 Remove deprecation annotation from typedef Eigen::Index Index, as it would generate too many build warnings. 2019-04-24 08:50:07 -07:00
Eugene Zhulenev
a7b7f3ca8a Add missing EIGEN_DEPRECATED annotations to deprecated functions and fix few other doxygen warnings 2019-04-23 17:23:19 -07:00
Anuj Rawat
8c7a6feb8e Adding lowlevel APIs for optimized RHS packet load in TensorFlow 
SpatialConvolution

Low-level APIs are added in order to optimized packet load in gemm_pack_rhs
in TensorFlow SpatialConvolution. The optimization is for scenario when a
packet is split across 2 adjacent columns. In this case we read it as two
'partial' packets and then merge these into 1. Currently this only works for
Packet16f (AVX512) and Packet8f (AVX2). We plan to add this for other
packet types (such as Packet8d) also.

This optimization shows significant speedup in SpatialConvolution with
certain parameters. Some examples are below.

Benchmark parameters are specified as:
Batch size, Input dim, Depth, Num of filters, Filter dim

Speedup numbers are specified for number of threads 1, 2, 4, 8, 16.

AVX512:

Parameters                  | Speedup (Num of threads: 1, 2, 4, 8, 16)
----------------------------|------------------------------------------
128,   24x24,  3, 64,   5x5 |2.18X, 2.13X, 1.73X, 1.64X, 1.66X
128,   24x24,  1, 64,   8x8 |2.00X, 1.98X, 1.93X, 1.91X, 1.91X
 32,   24x24,  3, 64,   5x5 |2.26X, 2.14X, 2.17X, 2.22X, 2.33X
128,   24x24,  3, 64,   3x3 |1.51X, 1.45X, 1.45X, 1.67X, 1.57X
 32,   14x14, 24, 64,   5x5 |1.21X, 1.19X, 1.16X, 1.70X, 1.17X
128, 128x128,  3, 96, 11x11 |2.17X, 2.18X, 2.19X, 2.20X, 2.18X

AVX2:

Parameters                  | Speedup (Num of threads: 1, 2, 4, 8, 16)
----------------------------|------------------------------------------
128,   24x24,  3, 64,   5x5 | 1.66X, 1.65X, 1.61X, 1.56X, 1.49X
 32,   24x24,  3, 64,   5x5 | 1.71X, 1.63X, 1.77X, 1.58X, 1.68X
128,   24x24,  1, 64,   5x5 | 1.44X, 1.40X, 1.38X, 1.37X, 1.33X
128,   24x24,  3, 64,   3x3 | 1.68X, 1.63X, 1.58X, 1.56X, 1.62X
128, 128x128,  3, 96, 11x11 | 1.36X, 1.36X, 1.37X, 1.37X, 1.37X

In the higher level benchmark cifar10, we observe a runtime improvement
of around 6% for AVX512 on Intel Skylake server (8 cores).

On lower level PackRhs micro-benchmarks specified in TensorFlow
tensorflow/core/kernels/eigen_spatial_convolutions_test.cc, we observe
the following runtime numbers:

AVX512:

Parameters                                                     | Runtime without patch (ns) | Runtime with patch (ns) | Speedup
---------------------------------------------------------------|----------------------------|-------------------------|---------
BM_RHS_NAME(PackRhs, 128, 24, 24, 3, 64, 5, 5, 1, 1, 256, 56)  |  41350                     | 15073                   | 2.74X
BM_RHS_NAME(PackRhs, 32, 64, 64, 32, 64, 5, 5, 1, 1, 256, 56)  |   7277                     |  7341                   | 0.99X
BM_RHS_NAME(PackRhs, 32, 64, 64, 32, 64, 5, 5, 2, 2, 256, 56)  |   8675                     |  8681                   | 1.00X
BM_RHS_NAME(PackRhs, 32, 64, 64, 30, 64, 5, 5, 1, 1, 256, 56)  |  24155                     | 16079                   | 1.50X
BM_RHS_NAME(PackRhs, 32, 64, 64, 30, 64, 5, 5, 2, 2, 256, 56)  |  25052                     | 17152                   | 1.46X
BM_RHS_NAME(PackRhs, 32, 256, 256, 4, 16, 8, 8, 1, 1, 256, 56) |  18269                     | 18345                   | 1.00X
BM_RHS_NAME(PackRhs, 32, 256, 256, 4, 16, 8, 8, 2, 4, 256, 56) |  19468                     | 19872                   | 0.98X
BM_RHS_NAME(PackRhs, 32, 64, 64, 4, 16, 3, 3, 1, 1, 36, 432)   | 156060                     | 42432                   | 3.68X
BM_RHS_NAME(PackRhs, 32, 64, 64, 4, 16, 3, 3, 2, 2, 36, 432)   | 132701                     | 36944                   | 3.59X

AVX2:

Parameters                                                     | Runtime without patch (ns) | Runtime with patch (ns) | Speedup
---------------------------------------------------------------|----------------------------|-------------------------|---------
BM_RHS_NAME(PackRhs, 128, 24, 24, 3, 64, 5, 5, 1, 1, 256, 56)  | 26233                      | 12393                   | 2.12X
BM_RHS_NAME(PackRhs, 32, 64, 64, 32, 64, 5, 5, 1, 1, 256, 56)  |  6091                      |  6062                   | 1.00X
BM_RHS_NAME(PackRhs, 32, 64, 64, 32, 64, 5, 5, 2, 2, 256, 56)  |  7427                      |  7408                   | 1.00X
BM_RHS_NAME(PackRhs, 32, 64, 64, 30, 64, 5, 5, 1, 1, 256, 56)  | 23453                      | 20826                   | 1.13X
BM_RHS_NAME(PackRhs, 32, 64, 64, 30, 64, 5, 5, 2, 2, 256, 56)  | 23167                      | 22091                   | 1.09X
BM_RHS_NAME(PackRhs, 32, 256, 256, 4, 16, 8, 8, 1, 1, 256, 56) | 23422                      | 23682                   | 0.99X
BM_RHS_NAME(PackRhs, 32, 256, 256, 4, 16, 8, 8, 2, 4, 256, 56) | 23165                      | 23663                   | 0.98X
BM_RHS_NAME(PackRhs, 32, 64, 64, 4, 16, 3, 3, 1, 1, 36, 432)   | 72689                      | 44969                   | 1.62X
BM_RHS_NAME(PackRhs, 32, 64, 64, 4, 16, 3, 3, 2, 2, 36, 432)   | 61732                      | 39779                   | 1.55X

All benchmarks on Intel Skylake server with 8 cores.
 2019-04-20 06:46:43 +00:00
Rasmus Munk Larsen
039ee52125 Tweak cost model for tensor contraction when parallelizing over the inner dimension. 
https://bitbucket.org/snippets/rmlarsen/MexxLo
 2019-04-12 13:35:10 -07:00
Jonathon Koyle
9a3f06d836 Update TheadPoolDevice example to include ThreadPool creation and passing pointer into constructor. 2019-04-10 10:02:33 -06:00
Deven Desai
66a885b61e adding EIGEN_DEVICE_FUNC to the recently added TensorContractionKernel constructor. Not having the EIGEN_DEVICE_FUNC attribute on it was leading to compiler errors when compiling Eigen in the ROCm/HIP path 2019-04-08 13:45:08 +00:00
Eugene Zhulenev
629ddebd15 Add missing semicolon 2019-04-02 15:04:26 -07:00
Eugene Zhulenev
4e2f6de1a8 Add support for custom packed Lhs/Rhs blocks in tensor contractions 2019-04-01 11:47:31 -07:00
Deven Desai
2dbea5510f Merged eigen/eigen into default 2019-03-19 16:52:38 -04:00
David Tellenbach
bd9c2ae3fd Fix include guard comments 2019-03-15 15:29:17 +01:00
Eugene Zhulenev
001f10e3c9 Fix segfaults with cuda compilation 2019-03-11 09:43:33 -07:00
Eugene Zhulenev
899c16fa2c Fix a bug in TensorGenerator for 1d tensors 2019-03-11 09:42:01 -07:00
Eugene Zhulenev
0f8bfff23d Fix a data race in NonBlockingThreadPool 2019-03-11 09:38:44 -07:00
Gael Guennebaud
2df4f00246 Change license from LGPL to MPL2 with agreement from David Harmon. 2019-03-07 18:17:10 +01:00
Rasmus Munk Larsen
3c3f639fe2 Merge. 2019-03-06 11:54:30 -08:00
Rasmus Munk Larsen
f4ec8edea8 Add macro EIGEN_AVOID_THREAD_LOCAL to make it possible to manually disable the use of thread_local. 2019-03-06 11:52:04 -08:00
Rasmus Munk Larsen
41cdc370d0 Fix placement of "#if defined(EIGEN_GPUCC)" guard region. 
Found with -Wundefined-func-template.

Author: tkoeppe@google.com
 2019-03-06 11:42:22 -08:00
Rasmus Munk Larsen
cc407c9d4d Fix placement of "#if defined(EIGEN_GPUCC)" guard region. 
Found with -Wundefined-func-template.

Author: tkoeppe@google.com
 2019-03-06 11:40:06 -08:00
Eugene Zhulenev
1bc2a0a57c Add missing return to NonBlockingThreadPool::LocalSteal 2019-03-06 10:49:49 -08:00
Eugene Zhulenev
4e4dcd9026 Remove redundant steal loop 2019-03-06 10:39:07 -08:00
Eugene Zhulenev
25abaa2e41 Check that inner block dimension is continuous 2019-03-05 17:34:35 -08:00
Eugene Zhulenev
5d9a6686ed Block evaluation for TensorGeneratorOp 2019-03-05 16:35:21 -08:00
Eugene Zhulenev
a407e022e6 Tune tensor contraction threadpool heuristics 2019-03-05 14:19:59 -08:00
Eugene Zhulenev
56c6373f82 Add an extra check for the RunQueue size estimate 2019-03-05 11:51:26 -08:00
Eugene Zhulenev
b1a8627493 Do not create Tensor<const T> in cxx11_tensor_forced_eval test 2019-03-05 11:19:25 -08:00
Eugene Zhulenev
efb5080d31 Do not initialize invalid fast_strides in TensorGeneratorOp 2019-03-04 16:58:49 -08:00
Eugene Zhulenev
b95941e5c2 Add tiled evaluation for TensorForcedEvalOp 2019-03-04 16:02:22 -08:00
Eugene Zhulenev
694084ecbd Use fast divisors in TensorGeneratorOp 2019-03-04 11:10:21 -08:00
Rasmus Munk Larsen
cf4a1c81fa Fix specialization for conjugate on non-complex types in TensorBase.h. 2019-03-01 14:21:09 -08:00
Rasmus Munk Larsen
6560692c67 Improve EventCount used by the non-blocking threadpool. 
The current algorithm requires threads to commit/cancel waiting in order
they called Prewait. Spinning caused by that serialization can consume
lots of CPU time on some workloads. Restructure the algorithm to not
require that serialization and remove spin waits from Commit/CancelWait.
Note: this reduces max number of threads from 2^16 to 2^14 to leave
more space for ABA counter (which is now 22 bits).
Implementation details are explained in comments.
 2019-02-22 13:56:26 -08:00
Gael Guennebaud
9ac1634fdf Fix conversion warnings 2019-02-19 21:59:53 +01:00
Rasmus Munk Larsen
071629a440 Fix incorrect value of NumDimensions in TensorContraction traits. 
Reported here: #1671
 2019-02-19 10:49:54 -08:00
Rasmus Larsen
efeabee445 Merged in ezhulenev/eigen-01 (pull request PR-590) 
Do not generate no-op cast() and conjugate() expressions
 2019-02-14 21:16:12 +00:00
Eugene Zhulenev
7b837559a7 Fix signed-unsigned return in RuqQueue 2019-02-14 10:40:21 -08:00
Eugene Zhulenev
f0d42d2265 Fix signed-unsigned comparison warning in RunQueue 2019-02-14 10:27:28 -08:00
Eugene Zhulenev
106ba7bb1a Do not generate no-op cast() and conjugate() expressions 2019-02-14 09:51:51 -08:00
Eugene Zhulenev
8c2f30c790 Speedup Tensor ThreadPool RunQueu::Empty() 2019-02-13 10:20:53 -08:00
Eugene Zhulenev
21eb97d3e0 Add PacketConv implementation for non-vectorizable src expressions 2019-02-08 15:47:25 -08:00
Eugene Zhulenev
1e36166ed1 Optimize TensorConversion evaluator: do not convert same type 2019-02-08 15:13:24 -08:00
Steven Peters
953ca5ba2f Spline.h: fix spelling "spang" -> "span" 2019-02-08 06:23:24 +00:00
Eugene Zhulenev
59998117bb Don't do parallel_pack if we can use thread_local memory in tensor contractions 2019-02-07 09:21:25 -08:00
Eugene Zhulenev
8491127082 Do not reduce parallelism too much in contractions with small number of threads 2019-02-04 12:59:33 -08:00
Eugene Zhulenev
eb21bab769 Parallelize tensor contraction only by sharding dimension and use 'thread-local' memory for packing 2019-02-04 10:43:16 -08:00
Gael Guennebaud
d586686924 Workaround lack of support for arbitrary packet-type in Tensor by manually loading half/quarter packets in tensor contraction mapper. 2019-01-30 16:48:01 +01:00
Christoph Hertzberg
a7779a9b42 Hide some annoying unused variable warnings in g++8.1 2019-01-29 16:48:21 +01:00
Christoph Hertzberg
c9825b967e Renaming even more I identifiers 2019-01-26 13:22:13 +01:00
Christoph Hertzberg
934b8a1304 Avoid I as an identifier, since it may clash with the C-header complex.h 2019-01-25 14:54:39 +01:00
Rasmus Munk Larsen
ee550a2ac3 Fix flaky test for tensor fft. 2019-01-16 14:03:12 -08:00
Eugene Zhulenev
1e6d15b55b Fix shorten-64-to-32 warning in TensorContractionThreadPool 2019-01-11 11:41:53 -08:00
Eugene Zhulenev
0abe03764c Fix shorten-64-to-32 warning in TensorContractionThreadPool 2019-01-10 10:27:55 -08:00
Gael Guennebaud
d812f411c3 bug #1654: fix compilation with cuda and no c++11 2019-01-09 18:00:05 +01:00
Eugene Zhulenev
e70ffef967 Optimize evalShardedByInnerDim 2019-01-08 16:26:31 -08:00
Rasmus Munk Larsen
dd6d65898a Fix shorten-64-to-32 warning. Use regular memcpy if num_threads==0. 2018-12-12 14:45:31 -08:00
Gael Guennebaud
cf697272e1 Remove debug code. 2018-12-09 23:05:46 +01:00
Gael Guennebaud
450dc97c6b Various fixes in polynomial solver and its unit tests: 
- cleanup noise in imaginary part of real roots
 - take into account the magnitude of the derivative to check roots.
 - use <= instead of < at appropriate places
 2018-12-09 22:54:39 +01:00
Rasmus Munk Larsen
8a02883d58 Merged in markdryan/eigen/avx512-contraction-2 (pull request PR-554) 
Fix tensor contraction on AVX512 builds

Approved-by: Rasmus Munk Larsen <rmlarsen@google.com>
 2018-12-05 18:19:32 +00:00
Mark D Ryan
36f8f6d0be Fix evalShardedByInnerDim for AVX512 builds 
evalShardedByInnerDim ensures that the values it passes for start_k and
end_k to evalGemmPartialWithoutOutputKernel are multiples of 8 as the kernel
does not work correctly when the values of k are not multiples of the
packet_size.  While this precaution works for AVX builds, it is insufficient
for AVX512 builds where the maximum packet size is 16.  The result is slightly
incorrect float32 contractions on AVX512 builds.

This commit fixes the problem by ensuring that k is always a multiple of
the packet_size if the packet_size is > 8.
 2018-12-05 12:29:03 +01:00
Christoph Hertzberg
0ec8afde57 Fixed most conversion warnings in MatrixFunctions module 2018-11-20 16:23:28 +01:00
Deven Desai
e7e6809e6b ROCm/HIP specfic fixes + updates 
1. Eigen/src/Core/arch/GPU/Half.h

   Updating the HIPCC implementation half so that it can declared as a __shared__ variable


2. Eigen/src/Core/util/Macros.h, Eigen/src/Core/util/Memory.h

   introducing a EIGEN_USE_STD(func) macro that calls
   - std::func be default
   - ::func when eigen is being compiled with HIPCC

   This change was requested in the previous HIP PR
   (https://bitbucket.org/eigen/eigen/pull-requests/518/pr-with-hip-specific-fixes-for-the-eigen/diff)


3. unsupported/Eigen/CXX11/src/Tensor/TensorDeviceThreadPool.h

   Removing EIGEN_DEVICE_FUNC attribute from pure virtual methods as it is not supported by HIPCC


4. unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h

   Disabling the template specializations of InnerMostDimReducer as they run into HIPCC link errors
 2018-11-19 18:13:59 +00:00
Rasmus Munk Larsen
72928a2c8a Merged in rmlarsen/eigen2 (pull request PR-543) 
Add parallel memcpy to TensorThreadPoolDevice in Eigen, but limit the number of threads to 4, beyond which we just seem to be wasting CPU cycles as the threads contend for memory bandwidth.

Approved-by: Eugene Zhulenev <ezhulenev@google.com>
 2018-11-13 17:10:30 +00:00
Rasmus Munk Larsen
cda479d626 Remove accidental changes. 2018-11-12 18:34:04 -08:00
Rasmus Munk Larsen
719d9aee65 Add parallel memcpy to TensorThreadPoolDevice in Eigen, but limit the number of threads to 4, beyond which we just seem to be wasting CPU cycles as the threads contend for memory bandwidth. 2018-11-12 17:46:02 -08:00
Rasmus Munk Larsen
93f9988a7e A few small fixes to a) prevent throwing in ctors and dtors of the threading code, and b) supporting matrix exponential on platforms with 113 bits of mantissa for long doubles. 2018-11-09 14:15:32 -08:00
Rasmus Munk Larsen
07fcdd1438 Merged in ezhulenev/eigen-02 (pull request PR-534) 
Fix cxx11_tensor_{block_access, reduction} tests
 2018-10-25 18:34:35 +00:00
Eugene Zhulenev
8a977c1f46 Fix cxx11_tensor_{block_access, reduction} tests 2018-10-25 11:31:29 -07:00
Christoph Hertzberg
449ff74672 Fix most Doxygen warnings. Also add links to stable documentation from unsupported modules (by using the corresponding Doxytags file). 
Manually grafted from d107a371c6
 2018-10-19 21:10:28 +02:00
Christoph Hertzberg
40fa6f98bf bug #1606: Explicitly set the standard before find_package(StandardMathLibrary). Also replace EIGEN_COMPILER_SUPPORT_CXX11 in favor of EIGEN_COMPILER_SUPPORT_CPP11. 
Grafted manually from a4afa90d16
 2018-10-19 17:20:51 +02:00
Rasmus Munk Larsen
dda68f56ec Fix GPU build due to gpu_assert not always being defined. 2018-10-18 16:29:29 -07:00
Eugene Zhulenev
9e96e91936 Move from rvalue arguments in ThreadPool enqueue* methods 2018-10-16 16:48:32 -07:00
Eugene Zhulenev
217d839816 Reduce thread scheduling overhead in parallelFor 2018-10-16 14:53:06 -07:00
Rasmus Munk Larsen
d52763bb4f Merged in ezhulenev/eigen-02 (pull request PR-528) 
[TensorBlockIO] Check if it's allowed to squeeze inner dimensions

Approved-by: Rasmus Munk Larsen <rmlarsen@google.com>
 2018-10-16 15:39:40 +00:00
Eugene Zhulenev
900c7c61bb Check if it's allowed to squueze inner dimensions in TensorBlockIO 2018-10-15 16:52:33 -07:00
Gael Guennebaud
f0fb95135d Iterative solvers: unify and fix handling of multiple rhs. 
m_info was not properly computed and the logic was repeated in several places.
 2018-10-15 23:47:46 +02:00
Gael Guennebaud
2747b98cfc DGMRES: fix null rhs, fix restart, fix m_isDeflInitialized for multiple solve 2018-10-15 23:46:00 +02:00
Gael Guennebaud
d835a0bf53 relax number of iterations checks to avoid false negatives 2018-10-15 10:23:32 +02:00
Gael Guennebaud
8214cf1896 Make sparse_basic includable from sparse_extra, but disable it since sparse_basic(DynamicSparseMatrix) does not compile at all anyways 2018-10-11 10:27:23 +02:00
Christoph Hertzberg
3f2c8b7ff0 Fix a lot of Doxygen warnings in Tensor module 2018-10-09 20:22:47 +02:00
Gael Guennebaud
93a6192e98 fix mpreal for mpfr<4.0.0 2018-10-09 09:15:22 +02:00
Rasmus Munk Larsen
d16634c4d4 Fix out-of bounds access in TensorArgMax.h. 2018-10-08 16:41:36 -07:00
Rasmus Munk Larsen
1a737e1d6a Fix contraction test. 2018-10-08 16:37:07 -07:00
Gael Guennebaud
2eda9783de typo 2018-10-08 21:37:46 +02:00
Gael Guennebaud
6cc9b2c831 fix warning in mpreal.h 2018-10-08 18:25:37 +02:00
Gael Guennebaud
e29bfe8479 Update included mpreal header to 3.6.5 and fix deprecated warnings. 2018-10-08 17:09:23 +02:00
Gael Guennebaud
64b1a15318 Workaround stupid warning 2018-10-08 12:01:18 +02:00
Christoph Hertzberg
c5f1d0a72a Fix shadow warning 2018-10-02 19:01:08 +02:00
Christoph Hertzberg
b92c71235d Move struct outside of method for C++03 compatibility. 2018-10-02 18:59:10 +02:00
Christoph Hertzberg
051f9c1aff Make code compile in C++03 mode again 2018-10-02 18:36:30 +02:00
Christoph Hertzberg
b786ce8c72 Fix conversion warning ... again 2018-10-02 18:35:25 +02:00
Christoph Hertzberg
564ca71e39 Merged in deven-amd/eigen/HIP_fixes (pull request PR-518) 
PR with HIP specific fixes (for the eigen nightly regression failures in HIP mode)
 2018-10-01 16:51:04 +00:00
Deven Desai
94898488a6 This commit contains the following (HIP specific) updates: 
- unsupported/Eigen/CXX11/src/Tensor/TensorReductionGpu.h
  Changing "pass-by-reference" argument to be "pass-by-value" instead
  (in a  __global__ function decl).
  "pass-by-reference" arguments to __global__ functions are unwise,
  and will be explicitly flagged as errors by the newer versions of HIP.

- Eigen/src/Core/util/Memory.h
- unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
  Changes introduced in recent commits breaks the HIP compile.
  Adding EIGEN_DEVICE_FUNC attribute to some functions and
  calling ::malloc/free instead of the corresponding std:: versions
  to get the HIP compile working again

- unsupported/Eigen/CXX11/src/Tensor/TensorReduction.h
  Change introduced a recent commit breaks the HIP compile
  (link stage errors out due to failure to inline a function).
  Disabling the recently introduced code (only for HIP compile), to get
  the eigen nightly testing going again.
  Will submit another PR once we have te proper fix.

- Eigen/src/Core/util/ConfigureVectorization.h
  Enabling GPU VECTOR support when HIP compiler is in use
  (for both the host and device compile phases)
 2018-10-01 14:28:37 +00:00
Rasmus Munk Larsen
2088c0897f Merged eigen/eigen into default 2018-09-28 16:00:46 -07:00
Rasmus Munk Larsen
31629bb964 Get rid of unused variable warning. 2018-09-28 16:00:09 -07:00
Eugene Zhulenev
bb13d5d917 Fix bug in copy optimization in Tensor slicing. 2018-09-28 14:34:42 -07:00
Rasmus Munk Larsen
104e8fa074 Fix a few warnings and rename a variable to not shadow "last". 2018-09-28 12:00:08 -07:00
Rasmus Munk Larsen
7c1b47840a Merged in ezhulenev/eigen-01 (pull request PR-514) 
Add tests for evalShardedByInnerDim contraction + fix bugs
 2018-09-28 18:37:54 +00:00
Eugene Zhulenev
524c81f3fa Add tests for evalShardedByInnerDim contraction + fix bugs 2018-09-28 11:24:08 -07:00
Christoph Hertzberg
86ba50be39 Fix integer conversion warnings 2018-09-28 19:33:39 +02:00
Eugene Zhulenev
e95696acb3 Optimize TensorBlockCopyOp 2018-09-27 14:49:26 -07:00
Eugene Zhulenev
9f33e71e9d Revert code lost in merge 2018-09-27 12:08:17 -07:00
Eugene Zhulenev
a7a3e9f2b6 Merge with eigen/eigen default 2018-09-27 12:05:06 -07:00
Eugene Zhulenev
9f4988959f Remove explicit mkldnn support and redundant TensorContractionKernelBlocking 2018-09-27 11:49:19 -07:00
Eugene Zhulenev
b314376f9c Test mkldnn pack for doubles 2018-09-26 18:22:24 -07:00
Eugene Zhulenev
22ed98a331 Conditionally add mkldnn test 2018-09-26 17:57:37 -07:00
Rasmus Munk Larsen
d956204ab2 Remove "false &&" left over from test. 2018-09-26 17:03:30 -07:00
Rasmus Munk Larsen
3815aeed7a Parallelize tensor contraction over the inner dimension in cases where where one or both of the outer dimensions (m and n) are small but k is large. This speeds up individual matmul microbenchmarks by up to 85%. 
Naming below is BM_Matmul_M_K_N_THREADS, measured on a 2-socket Intel Broadwell-based server.

Benchmark                          Base (ns)  New (ns) Improvement
------------------------------------------------------------------
BM_Matmul_1_80_13522_1                  387457    396013     -2.2%
BM_Matmul_1_80_13522_2                  406487    230789    +43.2%
BM_Matmul_1_80_13522_4                  395821    123211    +68.9%
BM_Matmul_1_80_13522_6                  391625     97002    +75.2%
BM_Matmul_1_80_13522_8                  408986    113828    +72.2%
BM_Matmul_1_80_13522_16                 399988     67600    +83.1%
BM_Matmul_1_80_13522_22                 411546     60044    +85.4%
BM_Matmul_1_80_13522_32                 393528     57312    +85.4%
BM_Matmul_1_80_13522_44                 390047     63525    +83.7%
BM_Matmul_1_80_13522_88                 387876     63592    +83.6%
BM_Matmul_1_1500_500_1                  245359    248119     -1.1%
BM_Matmul_1_1500_500_2                  401833    143271    +64.3%
BM_Matmul_1_1500_500_4                  210519    100231    +52.4%
BM_Matmul_1_1500_500_6                  251582     86575    +65.6%
BM_Matmul_1_1500_500_8                  211499     80444    +62.0%
BM_Matmul_3_250_512_1                    70297     68551     +2.5%
BM_Matmul_3_250_512_2                    70141     52450    +25.2%
BM_Matmul_3_250_512_4                    67872     58204    +14.2%
BM_Matmul_3_250_512_6                    71378     63340    +11.3%
BM_Matmul_3_250_512_8                    69595     41652    +40.2%
BM_Matmul_3_250_512_16                   72055     42549    +40.9%
BM_Matmul_3_250_512_22                   70158     54023    +23.0%
BM_Matmul_3_250_512_32                   71541     56042    +21.7%
BM_Matmul_3_250_512_44                   71843     57019    +20.6%
BM_Matmul_3_250_512_88                   69951     54045    +22.7%
BM_Matmul_3_1500_512_1                  369328    374284     -1.4%
BM_Matmul_3_1500_512_2                  428656    223603    +47.8%
BM_Matmul_3_1500_512_4                  205599    139508    +32.1%
BM_Matmul_3_1500_512_6                  214278    139071    +35.1%
BM_Matmul_3_1500_512_8                  184149    142338    +22.7%
BM_Matmul_3_1500_512_16                 156462    156983     -0.3%
BM_Matmul_3_1500_512_22                 163905    158259     +3.4%
BM_Matmul_3_1500_512_32                 155314    157662     -1.5%
BM_Matmul_3_1500_512_44                 235434    158657    +32.6%
BM_Matmul_3_1500_512_88                 156779    160275     -2.2%
BM_Matmul_1500_4_512_1                  363358    349528     +3.8%
BM_Matmul_1500_4_512_2                  303134    263319    +13.1%
BM_Matmul_1500_4_512_4                  176208    130086    +26.2%
BM_Matmul_1500_4_512_6                  148026    115449    +22.0%
BM_Matmul_1500_4_512_8                  131656     98421    +25.2%
BM_Matmul_1500_4_512_16                 134011     82861    +38.2%
BM_Matmul_1500_4_512_22                 134950     85685    +36.5%
BM_Matmul_1500_4_512_32                 133165     90081    +32.4%
BM_Matmul_1500_4_512_44                 133203     90644    +32.0%
BM_Matmul_1500_4_512_88                 134106    100566    +25.0%
BM_Matmul_4_1500_512_1                  439243    435058     +1.0%
BM_Matmul_4_1500_512_2                  451830    257032    +43.1%
BM_Matmul_4_1500_512_4                  276434    164513    +40.5%
BM_Matmul_4_1500_512_6                  182542    144827    +20.7%
BM_Matmul_4_1500_512_8                  179411    166256     +7.3%
BM_Matmul_4_1500_512_16                 158101    155560     +1.6%
BM_Matmul_4_1500_512_22                 152435    155448     -1.9%
BM_Matmul_4_1500_512_32                 155150    149538     +3.6%
BM_Matmul_4_1500_512_44                 193842    149777    +22.7%
BM_Matmul_4_1500_512_88                 149544    154468     -3.3%
 2018-09-26 16:47:13 -07:00
Eugene Zhulenev
71cd3fbd6a Support multiple contraction kernel types in TensorContractionThreadPool 2018-09-26 11:08:47 -07:00
Christoph Hertzberg
0a3356f4ec Don't deactivate BVH test for clang (probably, this was failing for very old versions of clang) 2018-09-25 20:26:16 +02:00
Christoph Hertzberg
2c083ace3e Provide EIGEN_OVERRIDE and EIGEN_FINAL macros to mark virtual function overrides 2018-09-24 18:01:17 +02:00
Gael Guennebaud
c696dbcaa6 Fiw shadowing of last and all 2018-09-21 23:02:33 +02:00
Gael Guennebaud
4291f167ee Add missing plugins to DynamicSparseMatrix -- fix sparse_extra_3 2018-09-21 14:53:43 +02:00
Eugene Zhulenev
719e438a20 Collapsed revision 
* Split cxx11_tensor_executor test
* Register test parts with EIGEN_SUFFIXES
* Fix EIGEN_SUFFIXES in cxx11_tensor_executor test
 2018-09-20 15:19:12 -07:00
Rasmus Munk Larsen
8e2be7777e Merged eigen/eigen into default 2018-09-20 11:41:15 -07:00
Rasmus Munk Larsen
5d2e759329 Initialize BlockIteratorState in a C++03 compatible way. 2018-09-20 11:40:43 -07:00
Gael Guennebaud
e04faca930 merge 2018-09-20 18:33:54 +02:00
Gael Guennebaud
d37188b9c1 Fix MPrealSupport 2018-09-20 18:30:10 +02:00
Gael Guennebaud
3c6dc93f99 Fix GPU support. 2018-09-20 18:29:21 +02:00
Gael Guennebaud
9419f506d0 Fix regression introduced by the previous fix for AVX512. 
It brokes the complex-complex case on SSE.
 2018-09-20 17:32:34 +02:00
Christoph Hertzberg
a0166ab651 Workaround for spurious "array subscript is above array bounds" warnings with g++4.x 2018-09-20 17:08:43 +02:00
Christoph Hertzberg
c50250cb24 Avoid warning "suggest braces around initialization of subobject". 
This test is not run in C++03 mode, so no compatibility is lost.
 2018-09-20 17:03:42 +02:00
Gael Guennebaud
71496b0e25 Fix gebp kernel for real+complex in case only reals are vectorized (e.g., AVX512). 
This commit also removes "half-packet" from data-mappers: it was not used and conceptually broken anyways.
 2018-09-20 17:01:24 +02:00
Rasmus Munk Larsen
44d8274383 Cast to longer type. 2018-09-19 13:31:42 -07:00
Rasmus Munk Larsen
d638b62dda Silence compiler warning. 2018-09-19 13:27:55 -07:00
Rasmus Munk Larsen
db9c9df59a Silence more compiler warnings. 2018-09-19 11:50:27 -07:00
Rasmus Munk Larsen
febd09dcc0 Silence compiler warnings in ThreadPoolInterface.h. 2018-09-19 11:11:04 -07:00
luz.paz"
f67b19a884 [PATCH 1/2] Misc. typos 
From 68d431b4c14ad60a778ee93c1f59ecc4b931950e Mon Sep 17 00:00:00 2001
Found via `codespell -q 3 -I ../eigen-word-whitelist.txt` where the whitelists consists of:
```
als
ans
cas
dum
lastr
lowd
nd
overfl
pres
preverse
substraction
te
uint
whch
```
---
 CMakeLists.txt                                | 26 +++++++++----------
 Eigen/src/Core/GenericPacketMath.h            |  2 +-
 Eigen/src/SparseLU/SparseLU.h                 |  2 +-
 bench/bench_norm.cpp                          |  2 +-
 doc/HiPerformance.dox                         |  2 +-
 doc/QuickStartGuide.dox                       |  2 +-
 .../Eigen/CXX11/src/Tensor/TensorChipping.h   |  6 ++---
 .../Eigen/CXX11/src/Tensor/TensorDeviceGpu.h  |  2 +-
 .../src/Tensor/TensorForwardDeclarations.h    |  4 +--
 .../src/Tensor/TensorGpuHipCudaDefines.h      |  2 +-
 .../Eigen/CXX11/src/Tensor/TensorReduction.h  |  2 +-
 .../CXX11/src/Tensor/TensorReductionGpu.h     |  2 +-
 .../test/cxx11_tensor_concatenation.cpp       |  2 +-
 unsupported/test/cxx11_tensor_executor.cpp    |  2 +-
 14 files changed, 29 insertions(+), 29 deletions(-)
 2018-09-18 04:15:01 -04:00
Eugene Zhulenev
c4627039ac Support static dimensions (aka IndexList) in Tensor::resize(...) 2018-09-18 14:25:21 -07:00
Eugene Zhulenev
218a7b9840 Enable DSizes type promotion with c++03 compilers 2018-09-18 10:57:00 -07:00
Ravi Kiran
1f0c941c3d Collapsed revision 
* Merged eigen/eigen into default
 2018-09-17 18:29:12 -07:00
Rasmus Munk Larsen
03a88c57e1 Merged in ezhulenev/eigen-02 (pull request PR-498) 
Add DSizes index type promotion
 2018-09-17 21:58:38 +00:00
Rasmus Munk Larsen
5ca0e4a245 Merged in ezhulenev/eigen-01 (pull request PR-497) 
Fix warnings in IndexList array_prod
 2018-09-17 20:15:06 +00:00
Eugene Zhulenev
a5cd4e9ad1 Replace deprecated Eigen::DenseIndex with Eigen::Index in TensorIndexList 2018-09-17 10:58:07 -07:00
Gael Guennebaud
b311bfb752 bug #1596: fix inclusion of Eigen's header within unsupported modules. 2018-09-17 09:54:29 +02:00
Gael Guennebaud
72f19c827a typo 2018-09-16 22:10:34 +02:00
Eugene Zhulenev
66f056776f Add DSizes index type promotion 2018-09-15 15:17:38 -07:00
Eugene Zhulenev
f313126dab Fix warnings in IndexList array_prod 2018-09-15 13:47:54 -07:00
Christoph Hertzberg
42705ba574 Fix weird error for building with g++-4.7 in C++03 mode. 2018-09-15 12:43:41 +02:00
Rasmus Munk Larsen
c2383f95af Merged in ezhulenev/eigen/fix_dsizes (pull request PR-494) 
Fix DSizes IndexList constructor
 2018-09-15 02:36:19 +00:00
Rasmus Munk Larsen
30290cdd56 Merged in ezhulenev/eigen/moar_eigen_fixes_3 (pull request PR-493) 
Const cast scalar pointer in TensorSlicingOp evaluator

Approved-by: Sameer Agarwal <sameeragarwal@google.com>
 2018-09-15 02:35:07 +00:00
Eugene Zhulenev
f7d0053cf0 Fix DSizes IndexList constructor 2018-09-14 19:19:13 -07:00
Rasmus Munk Larsen
601e289d27 Merged in ezhulenev/eigen/moar_eigen_fixes_1 (pull request PR-492) 
Explicitly construct tensor block dimensions from evaluator dimensions
 2018-09-15 01:36:21 +00:00
Eugene Zhulenev
71070a1e84 Const cast scalar pointer in TensorSlicingOp evaluator 2018-09-14 17:17:50 -07:00
Eugene Zhulenev
4863375723 Explicitly construct tensor block dimensions from evaluator dimensions 2018-09-14 16:55:05 -07:00
Rasmus Munk Larsen
14e35855e1 Merged in chtz/eigen-maxsizevector (pull request PR-490) 
Let MaxSizeVector respect alignment of objects

Approved-by: Rasmus Munk Larsen <rmlarsen@google.com>
 2018-09-14 23:29:24 +00:00
Eugene Zhulenev
1b8d70a22b Support reshaping with static shapes and dimensions conversion in tensor broadcasting 2018-09-14 15:25:27 -07:00
Christoph Hertzberg
007f165c69 bug #1598: Let MaxSizeVector respect alignment of objects and add a unit test 
Also revert 8b3d9ed081
 2018-09-14 20:21:56 +02:00
Rasmus Munk Larsen
9b864cdb37 Merged in rmlarsen/eigen3 (pull request PR-480) 
Avoid compilation error in C++11 test when EIGEN_AVOID_STL_ARRAY is set.
 2018-09-14 00:05:09 +00:00
Rasmus Munk Larsen
d0eef5fe6c Don't use bracket syntax in ctor. 2018-09-13 17:04:05 -07:00
Rasmus Munk Larsen
6313dde390 Fix merge error. 2018-09-13 16:42:05 -07:00
Rasmus Munk Larsen
0db590d22d Backed out changeset 01197e4452 2018-09-13 16:20:57 -07:00
Rasmus Munk Larsen
b3f4c067d9 Merge 2018-09-13 16:18:52 -07:00
Rasmus Munk Larsen
2b07018140 Enable vectorized version on GPUs. The underlying bug has been fixed. 2018-09-13 16:12:22 -07:00
Rasmus Munk Larsen
53568e3549 Merged in ezhulenev/eigen/tiled_evalution_support (pull request PR-444) 
Tiled evaluation for Tensor ops

Approved-by: Rasmus Munk Larsen <rmlarsen@google.com>
Approved-by: Gael Guennebaud <g.gael@free.fr>
 2018-09-13 22:05:47 +00:00
Eugene Zhulenev
01197e4452 Fix warnings 2018-09-13 15:03:36 -07:00
Gael Guennebaud
7f3b17e403 MSVC 2015 supports c++11 thread-local-storage 2018-09-13 18:15:07 +02:00
Eugene Zhulenev
d138fe341d Fis static_assert in test to conform c++11 standard 2018-09-11 17:23:18 -07:00
Rasmus Munk Larsen
e289f44c56 Don't vectorize the MeanReducer unless pdiv is available. 2018-09-11 14:09:00 -07:00
Eugene Zhulenev
55bb7e7935 Merge with upstream eigen/default 2018-09-11 13:33:06 -07:00
Eugene Zhulenev
81b38a155a Fix compilation of tiled evaluation code with c++03 2018-09-11 13:32:32 -07:00
Rasmus Munk Larsen
46f88fc454 Use numerically stable tree reduction in TensorReduction. 2018-09-11 10:08:10 -07:00
Rasmus Munk Larsen
3d057e0453 Avoid compilation error in C++11 test when EIGEN_AVOID_STL_ARRAY is set. 2018-09-06 12:59:36 -07:00
Alexey Frunze
edeee16a16 Fix build failures in matrix_power and matrix_exponential tests. 
This fixes the static assertion complaining about double being
used in place of long double. This happened on MIPS32, where
double and long double have the same type representation.
This can be simulated on x86 as well if we pass -mlong-double-64
to g++.
 2018-08-31 14:11:10 -07:00
Deven Desai
c64fe9ea1f Updates to fix HIP-clang specific compile errors. 
Compiling the eigen unittests with hip-clang (HIP with clang as the underlying compiler instead of hcc or nvcc), results in compile errors. The changes in this commit fix those compile errors. The main change is to convert a few instances of "__device__" to "EIGEN_DEVICE_FUNC"
 2018-08-30 20:22:16 +00:00
Rasmus Munk Larsen
8b3d9ed081 Use padding instead of alignment attribute, which MaxSizeVector does not respect. This leads to undefined behavior and hard-to-trace bugs. 2018-09-05 11:20:06 -07:00
Christoph Hertzberg
ba2c8efdcf EIGEN_UNUSED is not supported by g++4.7 (and not portable) 2018-09-12 11:49:10 +02:00
Christoph Hertzberg
ff4e835d6b "sparse_product.cpp" must be included before "sparse_basic.cpp", otherwise EIGEN_SPARSE_CREATE_TEMPORARY_PLUGIN has no effect 2018-08-30 20:10:11 +02:00
Christoph Hertzberg
023ed6b9a8 Product of empty array must be 1 and not 0. 2018-08-30 17:14:52 +02:00
Christoph Hertzberg
c2f4e8c08e Fix integer conversion warning 2018-08-30 17:12:53 +02:00
Deven Desai
946c3e2544 adding EIGEN_DEVICE_FUNC attribute to fix some GPU unit tests that are broken in HIP mode 2018-08-27 23:04:08 +00:00
Christoph Hertzberg
20ba2eee6d gcc thinks this may not be initialized 2018-08-28 18:33:24 +02:00
Christoph Hertzberg
73ca600bca Fix numerous shadow-warnings for GCC<=4.8 2018-08-28 18:32:39 +02:00
Christoph Hertzberg
42f3ee4fb8 Old gcc versions have problems with recursive #pragma GCC diagnostic push/pop 
Workaround: Don't include "DisableStupidWarnings.h" before including other main-headers
 2018-08-28 11:44:15 +02:00
Eugene Zhulenev
c144bb355b Merge with upstream eigen/default 2018-08-27 14:34:07 -07:00
Christoph Hertzberg
b1653d1599 Fix some trivial C++11 vs C++03 compatibility warnings 2018-08-25 12:21:00 +02:00
Christoph Hertzberg
42123ff38b Make unit test C++03 compatible 2018-08-25 11:53:28 +02:00
Christoph Hertzberg
117bc5d505 Fix some shadow warnings 2018-08-25 09:06:08 +02:00
Christoph Hertzberg
f155e97adb Previous fix broke compilation for clang 2018-08-25 00:10:46 +02:00
Christoph Hertzberg
209b4972ec Fix conversion warning 2018-08-25 00:02:46 +02:00
Christoph Hertzberg
495f6c3c3a Fix missing-braces warnings 2018-08-24 23:56:13 +02:00
Christoph Hertzberg
5aaedbeced Fixed more sign-compare and type-limits warnings 2018-08-24 23:54:12 +02:00
Christoph Hertzberg
8295f02b36 Hide "maybe uninitialized" warning on gcc 2018-08-24 23:22:20 +02:00
Christoph Hertzberg
f7675b826b Fix several integer conversion and sign-compare warnings 2018-08-24 22:58:55 +02:00
Rasmus Munk Larsen
744e2fe0de Address comments about EIGEN_THREAD_LOCAL. 2018-08-24 10:24:54 -07:00
Rasmus Munk Larsen
8d9bc5cc02 Fix g++ compilation. 2018-08-23 13:06:39 -07:00
Rasmus Munk Larsen
e9f9d70611 Don't rely on __had_feature for g++. 
Don't use __thread.
Only use thread_local for gcc 4.8 or newer.
 2018-08-23 12:59:46 -07:00
Rasmus Munk Larsen
668690978f Pad PerThread when we emulate thread_local to prevent false sharing. 2018-08-23 12:54:33 -07:00
Rasmus Munk Larsen
6cedc5a9b3 rename mu. 2018-08-23 12:11:58 -07:00
Rasmus Munk Larsen
6e0464004a Store std::unique_ptr instead of raw pointers in per_thread_map_. 2018-08-23 12:10:08 -07:00
Rasmus Munk Larsen
e51d9e473a Protect #undef max with #ifdef max. 2018-08-23 11:42:05 -07:00
Rasmus Munk Larsen
d35880ed91 merge 2018-08-23 11:36:49 -07:00
Christoph Hertzberg
a709c8efb4 Replace pointers by values or unique_ptr for better leak-safety 2018-08-23 19:41:59 +02:00
Christoph Hertzberg
39335cf51e Make MaxSizeVector leak-safe 2018-08-23 19:37:56 +02:00
Benoit Steiner
ff8e0ecc2f Updated one more line of code to avoid making the test dependent on cxx11 features. 2018-08-17 15:15:52 -07:00
Benoit Steiner
43d9dd9b28 Removed more dependencies on cxx11. 2018-08-17 08:49:32 -07:00
Christoph Hertzberg
4713465eef Silence double-promotion warning 2018-08-17 16:39:43 +02:00
Christoph Hertzberg
c9b25fbefa Silence unused parameter warning 2018-08-17 16:28:28 +02:00
Christoph Hertzberg
dbdeceabdd Silence double-promotion warning (when converting double to complex<long double>) 2018-08-17 16:26:11 +02:00
Benoit Steiner
19df4d5752 Merged in codeplaysoftware/eigen-upstream-pure/Pointer_type_creation (pull request PR-461) 
Creating a pointer type in TensorCustomOp.h
 2018-08-16 18:28:33 +00:00
Benoit Steiner
f641cf1253 Adding missing at method in Eigen::array 2018-08-16 11:24:37 -07:00
Benoit Steiner
ede580ccda Avoid using the auto keyword to make the tensor block access test more portable 2018-08-16 10:49:47 -07:00
Benoit Steiner
e23c8c294e Use actual types instead of the auto keyword to make the code more portable 2018-08-16 10:41:01 -07:00
Mehdi Goli
80f1a76dec removing the noises. 2018-08-16 13:33:24 +01:00
Mehdi Goli
d0b01ebbf6 Reverting the unitended delete from the code. 2018-08-16 13:21:36 +01:00
Mehdi Goli
161dcbae9b Using PointerType struct and specializing it per device for TensorCustomOp.h 2018-08-16 00:07:02 +01:00
Sameer Agarwal
f197c3f55b Removed an used variable (PacketSize) from TensorExecutor 2018-08-15 11:24:57 -07:00
Benoit Steiner
4181556907 Fixed the tensor contraction code. 2018-08-15 09:34:47 -07:00
Benoit Steiner
b6f96cf7dd Removed dependencies on cxx11 language features from the tensor_block_access test 2018-08-15 08:54:31 -07:00
Benoit Steiner
fbb834144d Fixed more compilation errors 2018-08-15 08:52:58 -07:00
Benoit Steiner
6bb3f1b43e Made the tensor_block_access test compile again 2018-08-14 14:26:59 -07:00
Benoit Steiner
43ec0082a6 Made the kronecker_product test compile again 2018-08-14 14:08:36 -07:00
Benoit Steiner
ab3f481141 Cleaned up the code and make it compile with more compilers 2018-08-14 14:05:46 -07:00
Rasmus Munk Larsen
fa0bcbf230 merge 2018-08-14 12:18:31 -07:00
Rasmus Munk Larsen
15d4f515e2 Use plain_assert in destructors to avoid throwing in CXX11 tests where main.h owerwrites eigen_assert with a throwing version. 2018-08-14 12:17:46 -07:00
Rasmus Munk Larsen
aebdb06424 Fix a few compiler warnings in CXX11 tests. 2018-08-14 12:06:39 -07:00
Rasmus Munk Larsen
2a98bd9c8e Merged eigen/eigen into default 2018-08-14 12:02:09 -07:00
Benoit Steiner
59bba77ead Fixed compilation errors with gcc 4.7 and 4.8 2018-08-14 10:54:48 -07:00
Mehdi Goli
8ba799805b Merge with upstream 2018-08-14 09:43:45 +01:00
Rasmus Munk Larsen
6d6e7b7027 merge 2018-08-13 15:34:50 -07:00
Rasmus Munk Larsen
9bb75d8d31 Add Barrier.h. 2018-08-13 15:34:03 -07:00
Rasmus Munk Larsen
2e1adc0324 Merged eigen/eigen into default 2018-08-13 15:32:00 -07:00
Rasmus Munk Larsen
8278ae6313 Add support for thread local support on platforms that do not support it through emulation using a hash map. 2018-08-13 15:31:23 -07:00
Benoit Steiner
501be70b27 Code cleanup 2018-08-13 15:16:40 -07:00
Benoit Steiner
3d3711f22f Fixed compilation errors. 2018-08-13 15:16:06 -07:00
Gael Guennebaud
3ec60215df Merged in rmlarsen/eigen2 (pull request PR-466) 
Move sigmoid functor to core and rename it to 'logistic'.
 2018-08-13 21:28:20 +00:00
Rasmus Munk Larsen
0f1b2e08a5 Call logistic functor from Tensor::sigmoid. 2018-08-13 11:52:58 -07:00
Benoit Steiner
26239ee580 Use NULL instead of nullptr to avoid adding a cxx11 requirement. 2018-08-13 11:05:51 -07:00
Benoit Steiner
3810ec228f Don't use the auto keyword since it's not always supported properly. 2018-08-13 10:46:09 -07:00
Benoit Steiner
e6d5be811d Fixed syntax of nested templates chevrons to make it compatible with c++97 mode. 2018-08-13 10:29:21 -07:00
Mehdi Goli
1aa86aad14 Merge with upstream. 2018-08-13 15:40:31 +01:00
Eugene Zhulenev
35d90e8960 Fix BlockAccess enum in CwiseUnaryOp evaluator 2018-08-10 17:37:58 -07:00
Eugene Zhulenev
855b68896b Merge with eigen/default 2018-08-10 17:18:42 -07:00
Eugene Zhulenev
f2209d06e4 Add block evaluationto CwiseUnaryOp and add PreferBlockAccess enum to all evaluators 2018-08-10 16:53:36 -07:00
Benoit Steiner
c8ea398675 Avoided language features that are only available in cxx11 mode. 2018-08-10 13:02:41 -07:00
Benoit Steiner
4be4286224 Made the code compile with gcc 5.4. 2018-08-10 11:32:58 -07:00
Eugene Zhulenev
cfaedb38cd Fix bug in a test + compilation errors 2018-08-09 09:44:07 -07:00
Mehdi Goli
ea8fa5e86f Merge with upstream 2018-08-09 14:07:56 +01:00
Mehdi Goli
8c083bfd0e Properly fixing the PointerType for TensorCustomOp.h. As the output type here should be based on CoeffreturnType not the Scalar type. Therefore, Similar to reduction and evalTo function, it should have its own MakePointer class. In this case, for other device the type is defaulted to CoeffReturnType and no changes is required on users' code. However, in SYCL, on the device, we can recunstruct the device Type. 2018-08-09 13:57:43 +01:00
Eugene Zhulenev
1c8b9e10a7 Merged with upstream eigen 2018-08-08 16:57:58 -07:00
Benoit Steiner
131ed1191f Merged in codeplaysoftware/eigen-upstream-pure/Fixing_compiler_warning (pull request PR-462) 
Fixing compiler warning in TensorBlock.h as it was creating a lot of noise at compilation.
 2018-08-08 18:14:15 +00:00
Mehdi Goli
532a0be05c Fixing compiler warning in TensorBlock.h as it was creating a lot of noise at compilation. 2018-08-08 12:12:26 +01:00