ROCm
HIP
Our great sponsors
ROCm | HIP | |
---|---|---|
198 | 29 | |
3,637 | 3,453 | |
- | 3.2% | |
0.0 | 8.9 | |
5 months ago | 3 days ago | |
Python | C++ | |
MIT License | 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
-
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...
- ROCm 5.7.0 Release
-
ROCm Is AMD's #1 Priority, Executive Says
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
-
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...
-
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 ?
[1] https://github.com/RadeonOpenCompute/ROCm/issues/1587
-
Nvidia's CUDA Monopoly
Last I heard he's abandoned working with AMD products.
https://github.com/RadeonOpenCompute/ROCm/issues/2198#issuec...
-
Nvidia H100 GPUs: Supply and Demand
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...
-
Open or closed source Nvidia driver?
As for rocm support on consumer devices, AMD wont even clarify what devices are supported. https://github.com/RadeonOpenCompute/ROCm/pull/1738
-
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.
-
Disable "SetTensor/CopyTensor" console logging.
I tried to train another model using InceptionResNetV2 and the same issues happens. Also, this happens even using the model.predict() method if using the GPU. Probably this is an issue related to the AMD Radeon RX 6700 XT or some mine misconfiguration. System Inormation: ArchLinux 6.1.32-1-lts - AMD Radeon RX 6700 XT - gfx1031 Opened issues: - https://github.com/RadeonOpenCompute/ROCm/issues/2250 - https://github.com/ROCmSoftwarePlatform/tensorflow-upstream/issues/2125
HIP
- Hip: Runtime API and Kernel Language for Portable Apps for AMD and Nvidia GPUs
-
Open-source project ZLUDA lets CUDA apps run on AMD GPUs
Is it perhaps because they want people to use HIP?
> HIP is very thin and has little or no performance impact over coding directly in CUDA mode.
> The HIPIFY tools automatically convert source from CUDA to HIP.
1. https://github.com/ROCm/HIP
-
AMD's Next GPU Is a 3D-Integrated Superchip
AMD has released HIP and a tool called HIPIFY which kind of behaves like this but at the source level¹. Rather than try and just translate CUDA to work on AMD compute they are more focused on higher level tooling.
Currently they seem to have a particular focus on AI frameworks and tools like PyTorch/Tensorflow/ONNX. They have sponsored and helped with a lot of PyTorch development for example, so PyTorch support for AMD is much better than it was this time last year².
¹(https://github.com/ROCm/HIP)
²(https://pytorch.org/blog/experience-power-pytorch-2.0/)
-
Intel CEO: 'The entire industry is motivated to eliminate the CUDA market'
> what would be the point for someone to add ROCm support to various pieces of software which currently require CUDA
It isn't just old cards though, CUDA is a point of centralization on a single provider during a time when access to that providers higher end cards isn't even available and that is causing people to look elsewhere.
ROCm supports CUDA through the included HIP projects...
https://github.com/ROCm/HIP
https://github.com/ROCm/HIPCC
https://github.com/ROCm/HIPIFY
The later will regex replace your CUDA methods with HIP methods. If it is as easy as running hipify on your codebase (or just coding to HIP apis), it certainly makes sense to do so.
-
Nvidia on the Mountaintop
AMD's equivalent is HIP [1], for sufficiently flexible definitions of "equivalent". I can't speak to how complete/correct/performant it is (I'm just a guy running tutorial/toy-level ML stuff on an RDNA1 card), but part of AMD's problem is that it might not practically matter how well they do this because the broader ecosystem support specifically for the CUDA stack is so entrenched.
[1] https://github.com/ROCm-Developer-Tools/HIP
- Stable Diffusion in pure C/C++
- Would love to hear your information and knowledge to simplify my understanding on AMD's positioning in the AI market
-
Ask HN: C++ still dominates on GPUs, why not Rust?
From what I know, modern GPUs are still programmed with C++ exclusively. See CUDA [0] for Nvidia and ROCm [1] for AMD.
Why is this? Why Rust is not loved there?
[0] https://docs.nvidia.com/cuda/
[1] https://github.com/ROCm-Developer-Tools/HIP
-
[P] RWKV C++ Cuda library with no dependencies, no torch, and no python
Go ahead and try to ship ROCm code that works on multiple consumer graphics cards on Linux, MacOS, and Windows. As an example of how much AMD cares about it, the installation notes linked to in the readme returns a 404.
-
Someone found a ROCm 5.5 RC Docker Container that works on 7000 series GPUs
The big whoop for ROCm is that AMD invested a considerable amount of engineering time and talent into a tool they call hip. Basically, it's an analysis tool that does its best to port proprietary Nvidia CUDA-style code - which due to various smelly reasons rules the roost - to code that can happily run on AMD graphics cards, and presumably others. Intel has a similar thing going with OneAPI. They've done this whilst working on porting a lot of their code base to the linux AMGPU open source kernel driver, as well.
What are some alternatives?
tensorflow-directml - Fork of TensorFlow accelerated by DirectML
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!
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
ZLUDA - CUDA on AMD GPUs
rocm-arch - A collection of Arch Linux PKGBUILDS for the ROCm platform
futhark - :boom::computer::boom: A data-parallel functional programming language
oneAPI.jl - Julia support for the oneAPI programming toolkit.
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.
SHARK - SHARK - High Performance Machine Learning Distribution
ginkgo - Numerical linear algebra software package
llama.cpp - LLM inference in C/C++