Hi, I have a triangulated model with (let’s say) 15 million faces. I want to assign a distinct ID (or maybe color) to each triangle (i.e. 15 million IDs) and after that, I want to generate a few million cubemap textures from regular points within this model. Then, for each cubemap texture I want to scan which distinct colors exist and keep a global (shared) accumulating counter, among all cubemap textures. Or in other words, I want to count how many times each distinct id (i.e. triangle) is found to exist within all cubemaps. For example, the triangle with ID 412345 (or color RGB 240,102,248) is located in half of the cubemaps textures.
With that process I will be able to see which triangle is the most/least visible. I do not care about visuallizing anything. I only want the counts and for that I am searching for the fastest possible approach.
Can I achieve this, fast, by using only CUDA C++ parallelism? Or I’m I going to need other specific tools/frameworks/libraries/etc… for that (e.g. OpenGL)? What would the fastest approach be? By the way I have no experience with either CUDA C++ or OpenGL. I can only speak Java, Python, R and Julia.
Thank you for your time.