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"the possibilities are relatively open for varied application."

They are actually very limited, because a GPU does not work, like many cpus in parallel (how I initially assumed).

So you will be limited and restricted in everything you do, making every step painful.

The trick is to find the parts that can be offloaded to the GPU - and come calculated back at the right time.

Games are usually performance critical - and communicating between the GPU and CPU can induce lots of lags as the coordination is tricky and not really under your control.



>They are actually very limited, because a GPU does not work, like many cpus in parallel (how I initially assumed).

This is how I understood GPUs. What's a better way to understand them?


Well, I am not an expert but something that can perform the same simple operations massivly parallel. Meaning, you want to avoid branching for example and there are lots of footguns, otherwise everything will be slow, or not working. And debugging is a pain.


I guess it would be more accurate to say that GPUs are an array of massively parallel SIMD processors, which are their own kind of parallelism. It's parallelism all the way down


Oh so why do you ask, if you know it (better)? ;)

What is optimised for parallelism, is not optimised for single thread performance, which is what one expects out of a CPU ..




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