* use universal intrinsic instead of raw intrinsic
* add 2 channels de-interleave on x86 platform
* add v_int32x4 version of v_muladd
* add accumulate version of v_dotprod based on the commit from seiko2plus on bf1852d
* remove some verify check in performance test
* avoid the out of boundary access and keep the performance
* Make <array> #ifdef true for MSVC
I think MSVC had `std::array` for quite a while (possibly going back as far as VS 2012, but it's definitely there in 2015 and 2017. So I think `_MSC_VER` `1900` is a safe bet. Probably `1800` and maybe even `1700` could work as well but I can't test that locally.
* fix test
* Update BufferReader documentation with some example code
* Add warning to BufferPool doc regarding deallocation of StackAllocator
* Added a sample code that satisfies LIFO rule for StackAllocator
OpenCV pthreads-based implementation changes:
- rework worker threads pool, allow to execute job by the main thread too
- rework synchronization scheme (wait for job completion, threads 'pong' answer is not required)
- allow "active wait" (spin) by worker threads and by the main thread
- use _mm_pause() during active wait (support for Hyper-Threading technology)
- use sched_yield() to avoid preemption of still working other workers
- don't use getTickCount()
- optional builtin thread pool profiler (disabled by compilation flag)
UMatData locks are not mapped on real locks (they are mapped to some "pre-initialized" pool).
Concurrent execution of these statements may lead to deadlock:
- a.copyTo(b) from thread 1
- c.copyTo(d) from thread 2
where:
- 'a' and 'd' are mapped to single lock "A".
- 'b' and 'c' are mapped to single lock "B".
Workaround is to process locks with strict order.
The opencv infrastructure mostly has the basics for supporting avx512 math functions,
but it wasn't hooked up (likely due to lack of users)
In order to compile the DNN functions for AVX512, a few things need to be hooked up
and this patch does that
Signed-off-by: Arjan van de Ven <arjan@linux.intel.com>
