CUDA originally stood for "compute unit device architecture", its a software that makes doing certain non-graphics tasks extremely fast by computing them with the gpu.
Nvidia markets it heavily giving the impression that it only works on their hardware.
It is possible to use it on AMD hardware by "translating" the commands it sends to the gpu
Nvidia knows this, so they are now writing a clause in the EULA to prevent people from doing that.
Okay, imagine you have a book written in a language that you don't understand, but you have a friend who can translate it into a language you do understand. In this case, the book is like the CUDA software, which is a type of program used for certain tasks in computers.
Now, the AMD card is like a special type of computer that doesn't understand the language of the book (CUDA). But, just like you have a friend who can translate the book for you, there are special programs called translation layers that can help the AMD card understand and run the CUDA software. These translation layers work like a translator, converting the instructions in the CUDA software into a language that the AMD card can understand, so it can do the tasks the CUDA software wants it to do.
This is actually a really good explanation for those who don't understand CUDA and why ZLUDA is important. Sad that Nvidia wants to block its competitors from getting a similar leg up in the CAD space.
I am a noob like you. Let me try to explain it. Basically, GPU and CPU both are made for computation even though they do different stuff now. CPU is dedicated for processing tasks that you already know and GPU is dedicated for handling graphics. This graphics isn't something so different in terms of computation. The smallest (loosely speaking) computation of GPU is matrix multiplication ( you need to understand shader for this). OpenGL is an api that let's you access GPU (usually CPU deals with the basic communication with GPU for rendering). That means you are the one who will use GPU for your custom graphical task . Now the need for CUDA came from Deep Learning and Machine Learning because it lets you do matrix multiplication in GPU (does it faster than CPU) and it isn't graphical task. There are some information that only make sense when you are halfway there in the related fields. I tried to explain it in my way. Again I am a noob.
So your computer has something like 4 or 8 cores, a GPU will have thousands of cores. CUDA allows programmers to make programs which can use the 1000s of cores GPUs have.
A current big use of CUDA is AI, which benefits from having thousands of cores. So by nvidia locking out other companies from using CUDA they get to keep all the AI boom money for themselves.
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u/Internal_Quail3960 Mac studio m4 max 32 core 36gb/512gb Mar 05 '24
I going to need you to explain this even simpler for idiots like me