Getting a bit difficult to understand your point of view here. The simple fact is NVDA executed well, had the strategic vision from 2006-7 onwards to invest in R&D, build complex libraries encompassing various complicated algorithms as well as allocated precious chip area to support these when no one was using the GPUs for those purposes. They took a risk.
I don't use Apple, but I don't complain abt them. You are free to use AMD if you so desire. Why the hate?
> The simple fact is NVDA executed well, had the strategic vision from 2006-7 onwards to invest in R&D...
The issue here isn't as much as nVidia as it is nVidia fanboism and intellectually dishonest argument.
What determines the speed of an algorithm, all things being similar, is the raw power of hardware underneath. For that, you use the device drivers, use their equivalent level (e.g. low level on both) APIs and let them rip. You want to have as equal as comparison as you want.
What I don't expect is to take nVidia drivers, load them onto the AMD graphics card and then when the thing glitches out or underperforms say - see, it's bad.
The fact is that Hipify on AMD isn't the fastest way to run CUDA code on AMD anymore. Not since ZLUDA was created. Which raises unfortunate implications. Why wasn't Hipify able to reach the same performance? Maybe because it's a shitty translation layer. Who knows?
> I don't use Apple, but I don't complain abt them.
Just because you don't use them, doesn't mean they don't negatively impact the world in a huge way. Looks at the app store, Apple's penchant for proprietary charges, and the constant phone upgrade treadmill.
Nothing you said prevents API makers of biasing their API to favor one hardware platform over the other.
EDIT: Which CUDA to AMD GPU translation project are you referring to? AMD's original efforts or ZLUDA?