ROCm
ZLUDA
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ROCm
- ROCm 6.1.0
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
ROCm is not spelled out anywhere in their documentation and the best answers in search come from Github and not AMD official documents
"Radeon Open Compute Platform"
https://github.com/ROCm/ROCm/issues/1628
And they wonder why they are losing. Branding absolutely matters.
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AMD Instinct MI300X Accelerators
https://github.com/ROCm/ROCm/issues/1353
Bought in 2020. Stopped working in 2020. Not the latest, but in-production, advertised ROCm-capable, and what I could find during the Great GPU Shortage of 2020.
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AMD leaps after launching AI chip that could challenge Nvidia dominance
Maybe so. But it isn't confidence inspiring when I go to see which cards are supported and I see this issue:
https://github.com/ROCm/ROCm/issues/1714
With Nvidia cards, I know that if I buy any Nvidia card made in the last 10 years, CUDA code will run on it. Period. (Yes, different language levels require newer hardware, but Nvidia docs are quite clear about which CUDA versions require which silicon.)
The will-they-won't-they and the rapidly dropped support is hurting the otherwise excellent ROCm and HIP projects. There is a huge API surface to implement and it looks like they're making rapid gains.
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GCN2, GCN3: What is the Technical, Non-Business Reason for Limited Supported in Linux (OpenSYCL/HIP/ROCM)? [Exasperated client]
Like, there is: https://github.com/ROCm/ROCm.github.io/blob/master/hardware.md but I'm pretty sure that's very very outdated, maybe from 4.x?
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AMD’s Best GPU has some problems — Radeon RX 7900XTX VR Performance Review
Fair enough I'll give you that. Although it is listed as officially supported here, other documentation says it works but is not officially supported.
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Finally, ROCm packages in [community]!
Do you have a source? The 580 and several older cards are listed as officially supported here, and even some 2xx/3xx cards are listed as unofficially supported.
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[D] What’s the word on AMD gpus these days?
Some of the GPUs listed in your link are for consumers. For a more extensive list, see https://github.com/ROCm/ROCm.github.io/blob/master/hardware.md
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Told an AI to generate Linux. Looks about right
Very conveniently, your linked page (the therein linked pages) do not talk about which GPUs actually do support ROCm. This is probably because AMDs newest cards do not support ROCm in any way, and would guess they don't want the sales pact this lack of feature could cause. Please do evaluate yourself, here: https://github.com/ROCm/ROCm.github.io/blob/master/hardware.md
ZLUDA
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Open-source project ZLUDA lets CUDA apps run on AMD GPUs
It now supports AMD GPUs since 3 weeks ago, check the latest commit at the repo:
https://github.com/vosen/ZLUDA
The article also mentions exactly this fact.
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Nvidia bans using translation layers for CUDA software
Looks like nvidia is trying to keep the lynchpin of their entire business model from crumbling underneath them. ZLUDA lets you run unmodified CUDA applications with near-native performance on AMD GPUs.
https://github.com/vosen/ZLUDA
With Triton looking to eclipse CUDA entirely, im not sure this prohibition does anything more than placate casual shareholders.
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Nvidia bans using translation layers for CUDA software to run on other chips
>Dark API functions are reverse-engineered and implemented by ZLUDA on a case-by-case basis once we observe an application making use of it.
https://github.com/vosen/ZLUDA/blob/master/ARCHITECTURE.md
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Nvidia hits $2T valuation as AI frenzy grips Wall Street
> I know AMD have their competition, but their GPU software division keeps tripping over itself.
They are actively stepping on every rake there is. Eg they just stopped supporting the drop-in-cuda project everyone is waiting for, due to there being "no business-case for CUDA on AMD GPUs" [0].
[0] https://github.com/vosen/ZLUDA?tab=readme-ov-file#faq
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Nvidia Is Now More Valuable Than Amazon and Google
https://github.com/vosen/ZLUDA
They still funded it and it was created.
- Debian on Apple hardware (M1 and later)
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
From the same repo, I found this excellent, well-written architecture document: https://github.com/vosen/ZLUDA/blob/master/ARCHITECTURE.md
I love the direct, "no bullshit" style of writing.
Some gems:
> Anyone familiar with C++ will instantly understand that compiling it is a complicated affair.
> Additionally CUDA allows, to a large degree, mixing CPU code and GPU code. What does all this complexity mean for ZLUDA? Absolutely nothing
> Since an application can dynamically link to either Driver API or Runtime API, it would seem that ZLUDA needs to provide both. In reality very few applications dynamically link to Runtime API. For the vast majority of applications it's sufficient to provide Driver API for dynamic (runtime) linking.
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Intel CEO: 'The entire industry is motivated to eliminate the CUDA market'
CUDA is huge and nvidia spent a ton in a lot of "dead end" use cases optimizing it. There have been experiments with CUDA translation layers with decent performance[1]. There are two things that most projects hit:
1. The CUDA API is huge; I'm sure Intel/AMD will focus on what they need to implement pytorch and ignore every other use case ensuring that CUDA always has the leg up in any new frontier
2. Nvidia actually cares about developer experience. The most prominent example is Geohotz with tinygrad - where AMD examples didn't even work or had glaring compiler bugs. You will find nvidia engineer in github issues for CUDA projects. Intel/AMD hasn't made that level of investment and thats important because GPUs tend to be more fickle than CPUs.
[1] https://github.com/vosen/ZLUDA
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Why Nvidia Keeps Winning: The Rise of an AI Giant
> I don't think you understand just how insanely difficult it is to break into that market.
You're right, I have no clue nor have I ever tried myself.
> Even with apple money or something like that, it's a losing prospect because in the time it'll take you to get up and off the ground (which is FOREVER) your competition will crush you.
This I find hard to believe, do you have a source or reference for that claim? Companies with that amount of cash are hardly going to be crushed by competition be it direct or indirect. Anyway, I'm talking more about the Intels and AMDs of this world.
We have very lacklustre efforts from players I won't name with their Zluda library (https://github.com/vosen/ZLUDA) which I got REALLY excited about, until I read the README.txt. Four contributors, last commit early 2021.
Why, oh why, is it this bad?
- Intel Arc Graphics Driver Change Leads To A Big Speed-Up Under Linux
What are some alternatives?
rocm-arch - A collection of Arch Linux PKGBUILDS for the ROCm platform
InvokeAI - InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.
ROCR-Runtime - ROCm Platform Runtime: ROCr a HPC market enhanced HSA based runtime
HIPIFY - HIPIFY: Convert CUDA to Portable C++ Code [Moved to: https://github.com/ROCm/HIPIFY]
deep-daze - Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). Technique was originally created by https://twitter.com/advadnoun
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
HIPIFY - HIPIFY: Convert CUDA to Portable C++ Code
stable-diffusion-webui - Stable Diffusion web UI
HIP - HIP: C++ Heterogeneous-Compute Interface for Portability
arrow - 🏹 Better dates & times for Python