AMD Quietly Funded A Drop-In CUDA Implementation Built On ROCm: It's Now Open-Source
AMD Quietly Funded A Drop-In CUDA Implementation Built On ROCm: It's Now Open-Source
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Can someone please explain like I’m five what the meaning and impact of this will be? Past posts and comments don’t seem to be very clear. As someone who uses both Linux and macOS professionally for design, this could be a massive game changer for me.
If you already have a cuda workflow and want to use an AMD card, you can do that with this library.
That includes stuff like Stable Diffusion that recommended nvidia cards because it uses CUDA to accelerate image generation?
So does it work with off the shelf software or is it something the developer has the patch in?
So does it work with off the shelf software or is it something the developer has the patch in?
The point of a drop-in replacement is that no patching is required but in reality the software was released in incomplete form.
ok, I get that much. what I’d like to know, if you’re willing to explain: what’s it going to be like deploying that on, say, a Mac workstation? a pop_os workstation? (edit: such as: how, can I on macOS, will I work with after effects, etc.)
thanks for your time
Your question is legitimate, but chances are that you will need to find the answers yourself by reading the docs.
CUDA is when a program can use the NVIDIA GPU in addition to the CPU for some complicated calculations. AMD now made it possible to use their cards for it too.
I know what CUDA does (as someone who likes rendering stuff, but with AMD cards, I’ve missed it). I’m trying to figure out, realistically, how I can easily deploy and make use of it on my linux and Mac workstations.
the details o’ve come across lately have been a bit… vague.
edit: back when I was in design school, I heard, “when Adobe loves a video card very much, it will hardware accelerate. We call this ‘CUDA’."
You can't use it with programs that aren't specifically coded to use it. Outside of hash cracking, AI training and crypto mining, few programs are.
If you mean from a developer perspective, you need to download the CUDA libraries and read through the documentation.
CUDA is the kernel diver API for Nvidia. Stuff like AI runs directly on it.
ROCm is the AMD kernel driver API for their hardware, think like Windows calls it a folder while Linux has directories kinds of naming, but in code.
API is an abstraction layer like how Linux makes open, close, print like command and translates then into the actual byte code that runs on your specific hardware.
HIPS is a translation layer that automatically converts CUDA API calls to the ROCm API equivalent.
One problem with ROCm/HIPS is that it only targets the latest 7000 series cards onwards. AMD directly took over the API with the 7k stuff. Older AMD cards are almost like a whole different unrelated thing. At least this is the best I understand it from researching this before making a purchase to run AI offline 7 months ago.
ZLUDA is new and looks to be like a HIPS translation layer between the older 6000 series cards and CUDA indicating likely support for these in the near future.
If you are on modern hardware with secure boot and you have not gone through the hassle of setting up your own TPM secure boot keys so that you can sign your own kernel modules, you want to pay attention to the DKMS info like:
There are some known limitations though like currently only targeting the ROCm 5.x API and not the newly-released ROCm 6.x releases.. In turn having to stick to ROCm 5.7 series as the latest means that using the ROCm DKMS modules don't build against the Linux 6.5 kernel now shipped by Ubuntu 22.04 LTS HWE stacks, for example. Hopefully there will be enough community support to see ZLUDA ported to ROCM 6 so at least it can be maintained with current software releases.
The DKMS module is how the secureboot key shim can automatically build the GPU kernel driver module from source when changes are made. Your use case and what you run may vary here but I think the article is hinting that support is sketchy in the Kernel across distros. You'll probably still have some update headaches at times when stuff might break, but that us pure speculation on my part.
To me it means likely support for AI with older Radeon hardware is in the cards in the near future.