This is clearly an amazing resource on advanced GPU programming regardless of programming language.

To the best of my knowledge, CUDA is Nvidia only. You would need to look at OpenCL or something similar. I guess the techniques presented in the article could be ported to OpenCL.

I think that's the point... The title conveys a more general article.

Right, CUDA is Nvidia only (8-series and above, so basically anything after 2006). The stuff in the article can totally be replicated in OpenCL. Especially since OpenCL 1.1 where buffers can be shared between GL and CL contexts, which IIRC was the only real technical capability CUDA had that OpenCL did not.

This is one way to run CUDA on your Radeon card: https://code.google.com/p/gpuocelot/

Although there's a note on that page saying that they're actively seeking developers for the AMD back-end, so I don't know how solid the support is.

What do you suggest, he writes a new title it will get flagged because it does not have the original title (or it gets reverted).

Suggest you undo your flag or write a better article with a better title.

OK undone my flag.

However, it was flagged originally because it promotes bad way forward for the community who want to learn GPU computing. It is pushes material for one company NVIDIA and its products and SDK, while there is an alternative open standard.

Instead of embracing it they continue splitting the community and do it an deceiving way "Modern GPU"? I gave an example of a modern GPU that this doesn't apply.

> a better article with a better title.

That is a bit dis-ingenious. Every time someone is wrong on the internet I will not go and spend hours re-writing their stuff but better. I thought a vote of flag was supposed to achieve some of that. Yes, it is a lot better to contribute and improve but I pick my battles, and filtering out bad stuff is another way of contributing.