C++, OpenCV and "what" for cross-platform GPU programing [closed]

Question

I want to write a cross-platform code for computer vision issue. This code should be run on PC with GPU (nVidia), iPhone with GPU and Some Android-Based device that may contain GPU and may not. I want to get the max possible utilization of the exist hardware. My programing language is C++ 11 and my computer vision library is OpenCV. What is the best framework, Layer, technique... etc to use in order to write an isolated high-level code that can utilize from the GPU if it is available.

P.S. this could be shown as off-topic as asking for recommendation. But really here I am not asking between many available options. I am just asking about how this usually is done or what is the state of art in this field.

Answer 1

For multiplatform, I'm going to argue for keeping it in C/C++ and use the usual threading libraries.

While in iOS you've got only one vendor and the OpenCV team can devote the efforts to tune as required, on Android there is a mix of CPU/GPU vendors so the Google/Android team went with RenderScript (Why did Google choose RenderScript instead of OpenCL) and doesn't officially support OpenCL. Including an non-RenderScript GPU compute options would have to come from the individual vendors like Intel, Qualcomm, and for completeness nVidia's CUDA.

Realize that mobile platforms have been evolving at a much faster rate than PCs, i.e. the type of phone you could have gotten with Intel first released the Core i series (2008) vs what is available now.

Further down the pipeline there are Compute Shaders in OpenGL ES 3.1 and Vulkan. So if you are looking for baseline - you would be better off in C/C++ thread land.

Now if you really had a mobile app that you needed to push the performance then you can figure out what optimizations are required on the mobile platform of your choice.