rocm-arch
ROCm
DISCONTINUED
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rocm-arch | ROCm | |
---|---|---|
19 | 198 | |
326 | 3,637 | |
1.8% | - | |
6.5 | 0.0 | |
about 1 month ago | 4 months ago | |
Shell | Python | |
- | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
rocm-arch
- I need assistance interpreting a specific error and understanding the purpose of the code that is referenced by the error, please.
- Finally, ROCm packages in [community]!
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Limit AUR build cores; paru
rocm-arch README
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Looking for co-maintainers (AUR)
. I use this for my personal PKGBUILDS: https://github.com/acxz/pkgbuilds and for smaller projects with less than 30ish packages like https://github.com/acxz/gazebo-arch/ and https://github.com/rocm-arch/rocm-arch/. and of course for projects that have larger amount of PKGBUILDS just mirroring them int their own github organization like ros-noetic is the way to go.
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First time in 2 years I was able to get Blender running with an AMD GPU on Linux!
I had to install rocm from the AUR. https://github.com/rocm-arch/rocm-arch
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Build for unofficial supported GPU (6700XT - gfx1031)
Obviously i followed that instruction with the parameter gfx1031, also tried to recompile all rocm packages in rocm-arch/rocm-arch repository with gfx1031 but none works.
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"error making: rocfft" when installing rocm-tensorflow
However, there is an unofficial Arch Linux ROCm project at https://github.com/rocm-arch/rocm-arch (not supported by AMD).
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Tensorflow with Radeon GPU
As others said, rocm is the solution. However compiling all the rocm stuff is very painful and last I tried, I was not able to compile not all rocm packages on AUR. There is a binary repository called arch4edu, which has rocm and a tensorflow-rocm package. I haven't tried it myself, but if you don't mind the security implications of using a binary repository (of course containers are always an option), then this will probably be the easiest way for tensorflow on amd.
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The State Of ROCm For HPC In Early 2021 With CUDA Porting Via HIP, Rewriting With OpenMP - Phoronix
The Arch community created a repository just with PKGBUILDs to install ROCM on Arch, here: https://github.com/rocm-arch/rocm-arch - but given that ROCM itself depends a lot on LLVM upstream it's quite hard to add it to the community repository (and also the whole installation procedure is VERY slow), like they talked in this issue: https://github.com/rocm-arch/rocm-arch/issues/262
ROCm
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AMD May Get Across the CUDA Moat
Yep, did exactly that. IMO he threw a fit, even though AMD was working with him squashing bugs. https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...
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ROCm Is AMD's #1 Priority, Executive Says
I don't know if they'll ultimately succeed or not, but they at least seem to be putting genuine effort into this. ROCm releases are coming out at a relatively nice clip[1], including a new release just a week or two ago[2].
Ok, I wonder what's wrong. maybe it's this? https://stackoverflow.com/questions/4959621/error-1001-in-cl...
Nope. Anything about this on the arch wiki? Nope
This bug report[2] from 2021? Maybe I need to update my groups.
[2]: https://github.com/RadeonOpenCompute/ROCm/issues/1411
$ ls -la /dev/kfd
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Simplifying GPU Application Development with HMM
HMM is, I believe, a Linux feature.
AMD added HMM support in ROCm 5.0 according to this: https://github.com/RadeonOpenCompute/ROCm/blob/develop/CHANG...
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AMD Ryzen APU turned into a 16GB VRAM GPU and it can run Stable Diffusion
Woot AMD now supports APU? I sold my notebook as i hit a wall when trying rocm [1] Is there a list oft Wirkung apu's ?
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Nvidia's CUDA Monopoly
I think geohot is working on that with tinygrad. Activity on the ROCm repo seems to have increased a lot recently:
https://github.com/RadeonOpenCompute/ROCm/graphs/code-freque...
Last I heard he's abandoned working with AMD products.
https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...
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Nvidia H100 GPUs: Supply and Demand
[1] links to https://github.com/RadeonOpenCompute/ROCm/issues/2198 which has all the context (driver bugs, vowing to stop using AMD, Lisa Su's response that they're committed to fixing this stuff, a comment that it's fixed)
They're talking about the meltdown he had on stream [1] (in front of the mentioned pirate flag), that ended with him saying he'd stop using AMD hardware [2]. He recanted this two weeks after talking with AMD [3].
Maybe he'll succeed, but this definitely doesn't scream stability to me. I'd be wary of investing money into his ventures (but then I'm not a VC, so what do I know).
[1] https://www.youtube.com/watch?v=Mr0rWJhv9jU
[2] https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...
[3] https://twitter.com/realGeorgeHotz/status/166980346408248934...
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Why Nvidia Keeps Winning: The Rise of an AI Giant
He flamed out, then is back after Lisa Su called him (lmao)
https://geohot.github.io/blog/jekyll/update/2023/05/24/the-t...
https://www.youtube.com/watch?v=Mr0rWJhv9jU
https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...
https://geohot.github.io/blog/jekyll/update/2023/06/07/a-div...
On a personal level that youtube doesn't make him come off looking that good... like people are trying to get patches to him and generally soothe him/damage control and he's just being a bit of a manchild. And it sounds like that's the general course of events around a lot of his "efforts".
On the other hand he's not wrong either, having this private build inside AMD and not even validating official, supported configurations for the officially supported non-private builds they show to the world isn't a good look, and that's just the very start of the problems around ROCm. AMD's OpenCL runtime was never stable or good either and every experience I've heard with it was "we spent so much time fighting AMD-specific runtime bugs and specs jank that what we ended up with was essentially vendor-proprietary anyway".
On the other other hand, it sounds like AMD know this is a mess and has some big stability/maturity improvements in the pipeline. It seems clear from some of the smoke coming out of the building that they're cooking on more general ROCm support for RDNA cards, and generally working to patch the maturity and stability issues he's talking about. I hate the "wait for drivers/new software release bro it's gonna fix everything" that surrounds AMD products but in this case I'm at least hopeful they seem to understand the problem, even if it's completely absurdly late.
Some of what he was viewing as "the process happening in secret" was likely people doing rush patches on the latest build to accommodate him, and he comes off as berating them over it. Again, like, that stream just comes off as "mercurial manchild" not coding genius. And everyone knew the driver situation is bad, that's why there's notionally alpha for him to realize here in the first place. He's bumping into moneymakers, and getting mad about it.
What are some alternatives?
tensorflow-directml - Fork of TensorFlow accelerated by DirectML
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
oneAPI.jl - Julia support for the oneAPI programming toolkit.
SHARK - SHARK - High Performance Machine Learning Distribution
plaidml - PlaidML is a framework for making deep learning work everywhere.
llama.cpp - LLM inference in C/C++
exllama - A more memory-efficient rewrite of the HF transformers implementation of Llama for use with quantized weights.
tensorflow-upstream - TensorFlow ROCm port
AdaptiveCpp - Implementation of SYCL and C++ standard parallelism for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!
ROCm-OpenCL-Runtime - ROCm OpenOpenCL Runtime
kompute - General purpose GPU compute framework built on Vulkan to support 1000s of cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.
server - The Triton Inference Server provides an optimized cloud and edge inferencing solution.