- gcc 4.8.4 (ARMv7)

* G-API-NG/Streaming: Introduced a Streaming API

Now a GComputation can be compiled in a special "streaming" way
and then "played" on a video stream.

Currently only VideoCapture is supported as an input source.

* G-API-NG/Streaming: added threading & real streaming

* G-API-NG/Streaming: Added tests & docs on Copy kernel

- Added very simple pipeline tests, not all data types are covered yet
  (in fact, only GMat is tested now);
- Started testing non-OCV backends in the streaming mode;
- Added required fixes to Fluid backend, likely it works OK now;
- Added required fixes to OCL backend, and now it is likely broken
- Also added a UMat-based (OCL) version of Copy kernel

* G-API-NG/Streaming: Added own concurrent queue class

- Used only if TBB is not available

* G-API-NG/Streaming: Fixing various issues

- Added missing header to CMakeLists.txt
- Fixed various CI issues and warnings

* G-API-NG/Streaming: Fixed a compile-time GScalar queue deadlock

- GStreamingExecutor blindly created island's input queues for
  compile-time (value-initialized) GScalars which didn't have any
  producers, making island actor threads wait there forever

* G-API-NG/Streaming: Dropped own version of Copy kernel

One was added into master already

* G-API-NG/Streaming: Addressed GArray<T> review comments

- Added tests on mov()
- Removed unnecessary changes in garray.hpp

* G-API-NG/Streaming: Added Doxygen comments to new public APIs

Also fixed some other comments in the code

* G-API-NG/Streaming: Removed debug info, added some comments & renamed vars

* G-API-NG/Streaming: Fixed own-vs-cv abstraction leak

- Now every island is triggered with own:: (instead of cv::)
  data objects as inputs;
- Changes in Fluid backend required to support cv::Mat/Scalar were
  reverted;

* G-API-NG/Streaming: use holds_alternative<> instead of index/index_of test

- Also fixed regression test comments
- Also added metadata check comments for GStreamingCompiled

* G-API-NG/Streaming: Made start()/stop() more robust

- Fixed various possible deadlocks
- Unified the shutdown code
- Added more tests covering different corner cases on start/stop

* G-API-NG/Streaming: Finally fixed Windows crashes

In fact the problem hasn't been Windows-only.
Island thread popped data from queues without preserving the Cmd
objects and without taking the ownership over data acquired so when
islands started to process the data, this data may be already freed.

Linux version worked only by occasion.

* G-API-NG/Streaming: Fixed (I hope so) Windows warnings

* G-API-NG/Streaming: fixed typos in internal comments

- Also added some more explanation on Streaming/OpenCL status

* G-API-NG/Streaming: Added more unit tests on streaming

- Various start()/stop()/setSource() call flow combinations

* G-API-NG/Streaming: Added tests on own concurrent bounded queue

* G-API-NG/Streaming: Added more tests on various data types, + more

- Vector/Scalar passed as input;
- Vector/Scalar passed in-between islands;
- Some more assertions;
- Also fixed a deadlock problem when inputs are mixed (1 constant, 1 stream)

* G-API-NG/Streaming: Added tests on output data types handling

- Vector
- Scalar

* G-API-NG/Streaming: Fixed test issues with IE + Windows warnings

* G-API-NG/Streaming: Decoupled G-API from videoio

- Now the core G-API doesn't use a cv::VideoCapture directly,
  it comes in via an abstract interface;
- Polished a little bit the setSource()/start()/stop() semantics,
  now setSource() is mandatory before ANY call to start().

* G-API-NG/Streaming: Fix STANDALONE build (errors brought by render)

G-API: Implement OpenCV render backend

* Implement render opencv backend

* Fix comment to review

* Add comment

* Add wrappers for kernels

* Fix comments to review

* Fix comment to review

- unnecessary extra semicolon after member function definition removed

OpenCV 4.1.2

OpenCV 3.4.8

* Disable posix_memalign by default

* core: fix memalign parameter handling

* Cuda + OpenGL on ARM

There might be multiple ways of getting OpenCV compile on Tegra (NVIDIA Jetson) platform, but mainly they modify CUDA(8,9,10...) source code, this one fixes it for all installations. 
( https://devtalk.nvidia.com/default/topic/1007290/jetson-tx2/building-opencv-with-opengl-support-/post/5141945/#5141945 et al.).
This way is exactly the same as the one proposed but the code change happens in OpenCV.

* Updated,
The link provided mentions: cuda8 + 9, I have cuda 10 + 10.1 (and can confirm it is still defined this way).
NVIDIA is probably using some other "secret" backend with Jetson.

- _mm256_bslli_epi128() works in GCC 4.9.3+ only
- Android NDK r10 doesn't support this instruction

* Add a few more tests on `any`

Added tests:
- get_ref_to_val_from_any
- update_val_via_ref

* Style fix

Reads and writes to volatile bool are not guaranteed to be atomic.

This ensures uniform behavior on any C++11 compliant compiler

* core: rework and optimize SIMD implementation of dotProd

  - add new universal intrinsics v_dotprod[int32], v_dotprod_expand[u&int8, u&int16, int32], v_cvt_f64(int64)
  - add a boolean param for all v_dotprod&_expand intrinsics that change the behavior of addition order between
    pairs in some platforms in order to reach the maximum optimization when the sum among all lanes is what only matters
  - fix clang build on ppc64le
  - support wide universal intrinsics for dotProd_32s
  - remove raw SIMD and activate universal intrinsics for dotProd_8
  - implement SIMD optimization for dotProd_s16&u16
  - extend performance test data types of dotprod
  - fix GCC VSX workaround of vec_mule and vec_mulo (in little-endian it must be swapped)
  - optimize v_mul_expand(int32) on VSX

* core: remove boolean param from v_dotprod&_expand and implement v_dotprod_fast&v_dotprod_expand_fast

  this changes made depend on "terfendail" review

```
#define NPP_VER_MAJOR 10
#define NPP_VER_MINOR 2
#define NPP_VER_PATCH 0
#define NPP_VER_BUILD 243

#define NPP_VERSION (NPP_VER_MAJOR * 1000 +     \
                     NPP_VER_MINOR *  100 +     \
                     NPP_VER_PATCH)