ROCm isn't so much a tool you directly use as it is an enablement code set library required by tools you might use so they can run on AMD hardware. There's really a wide range of potential tools that can use ROCm as one of the things it does is provided an alternative code path for the CUDA API domain. So basically anything that can run CUDA can be ported to use ROCm instead. Or with runtime wrappers like Zluda, you can even run code that was only written to be CUDA. You need to start by reading a lot. Watch some YouTube stuff and do whatever you need to get a foot hold in to establishing a execution environment. ROCm is still not really a windows friendly thing (but that's should be coming soon) except via WSL2, so you need to have some experience with Linux and Python. But really you can follow walk throughs and just start learning and reading about whatever you find you don't understand. Mindyou, it doesn't ever really end. You might start here for ROCm specific documentation. https://rocm.docs.amd.com/en/latest/what-is-rocm.html But decided what sort of AI projects you want to learn and figure out what the projects are to run will give you a better starting point. For example, I've been playing with different versions of Stable Diffusion using set ups of automatic1111 with Zluda directly in Win11 one set up and WSL Ubuntu with SD.Next on another and those work nicely. I had to find forks that people had made specifically to use ROCm instead of CUDA, but know more projects can be configured for either easily. And now I want to start playing with ComfyAI and get more involved with understanding pipelines and multi step workflows with HuggingFace models. https://huggingface.co/learn Good Luck Answer from GanacheNegative1988 on reddit.com
GitHub
github.com › ROCm › rocm-examples
GitHub - ROCm/rocm-examples: A collection of examples for the ROCm software stack · GitHub
rocprof-systems: Demonstrates how to use the ROCm Systems Profiler. rocprofv3: Illustrates how to use the rocprofv3 profiler. Tutorials: Showcases HIP Documentation Tutorials.
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GitHub
github.com › ROCm › rocm
GitHub - ROCm/ROCm: AMD ROCm™ Software - GitHub Home
If you’re using AMD Radeon GPUs or Ryzen APUs in a workstation setting with a display connected, see the ROCm on Radeon and Ryzen documentation for operating system/framework support and step-by-step installation instructions.
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Getting started with rocM
I use fedora 38 with rocm. I target the rhel 9.2 repo that amd hosts for rocm bits. Make sure to exclude dkms during install if your using a gui Linux, as you'll already have the driver loaded. Unfortunately it is extremely niche, amd users that also use Linux, that also want to play ai/ml, tiny subset of people that are capable of even reaching the starting line. Good news is it works great. I've run native stable diffusion with all kinds of models and model add ons via rocm on my 6800 xt. Just recently got mlc-llm fully working with the new llama2 llm models too. I'm getting 70+ tokens per second, amazing performance. Really cool stuff going on, the people that say amd can't do ml/ai are just lazy. And with all the vram, even a 6800 can run huge 13b models with crazy performance. Here's the article that got me going with the llama2 stuff. I had to compile some stuff to get the 6800xt working, but if you have 7000 series it's all precompiled. https://blog.mlc.ai/2023/08/09/Making-AMD-GPUs-competitive-for-LLM-inference More on reddit.com
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August 28, 2023ROCm 7.2 official installation instructions
Holy shit AMD crew. Either I am doing something wrong or there is a RADICAL performance boost for inferring diffusion models. I just ran a 5 second wan, 3 samplers (6 steps total). It normally takes me 10 minutes. It just ran in 190 seconds. FP16! I am on an r9700. Did we just more than double our speed? lol holy smokes 2nd generation of 5s is down to 172s. fp16 6 steps 3 samplers this nutty. [edit] Testing some other models and workflows for image gen in comfy. 7.2 on linux is a MASSIVE perf boost. Insane. I was coming off 6.4.1 More on reddit.com
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January 22, 2026Videos
AMD HIP Tutorial, 9-1, ROCm Libraries
06:01
AMD HIP Tutorial, 1-4, What is ROCm - YouTube
15:54
How To Install AMD ROCm, PyTorch, Stable Diffusion & YOLO - 2024 ...
08:01
How to Install AMD ROCm on Linux - Updated Guide 10/2023 - YouTube
16:04
AMD GPU Linux ROCm installation - step by step guide - YouTube
How To Install AMD ROCm, PyTorch, Stable Diffusion & YOLO ...
AMD ROCm
rocm.docs.amd.com
AMD ROCm documentation — ROCm Documentation
Use ROCm for AI · AI tutorials · Use ROCm for HPC · System optimization · AMD Instinct MI300X performance validation and tuning · System debugging · Use advanced compiler features · Set the number of CUs · Troubleshoot BAR access limitation · ROCm examples ·
DEV Community
dev.to › digitalocean › gpu-programming-for-beginners-rocm-amd-setup-to-edge-detection-29bm
GPU Programming for Beginners: ROCm + AMD Setup to Edge Detection - DEV Community
March 10, 2026 - Understanding GPU programming is ... We'll use ROCm and HIP (AMD's version of CUDA) to take you from zero to running real GPU code, culminating in a computer vision edge detector that processes images in parallel...
Reddit
reddit.com › r/rocm › what’s the best way to learn how to use and tools/features for rocm?
r/ROCm on Reddit: What’s the best way to learn how to use and tools/features for ROCm?
November 5, 2024 -
Nooby at AI but wanting to learn the ROCm tool set.. any advice?
Top answer 1 of 3
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ROCm isn't so much a tool you directly use as it is an enablement code set library required by tools you might use so they can run on AMD hardware. There's really a wide range of potential tools that can use ROCm as one of the things it does is provided an alternative code path for the CUDA API domain. So basically anything that can run CUDA can be ported to use ROCm instead. Or with runtime wrappers like Zluda, you can even run code that was only written to be CUDA. You need to start by reading a lot. Watch some YouTube stuff and do whatever you need to get a foot hold in to establishing a execution environment. ROCm is still not really a windows friendly thing (but that's should be coming soon) except via WSL2, so you need to have some experience with Linux and Python. But really you can follow walk throughs and just start learning and reading about whatever you find you don't understand. Mindyou, it doesn't ever really end. You might start here for ROCm specific documentation. https://rocm.docs.amd.com/en/latest/what-is-rocm.html But decided what sort of AI projects you want to learn and figure out what the projects are to run will give you a better starting point. For example, I've been playing with different versions of Stable Diffusion using set ups of automatic1111 with Zluda directly in Win11 one set up and WSL Ubuntu with SD.Next on another and those work nicely. I had to find forks that people had made specifically to use ROCm instead of CUDA, but know more projects can be configured for either easily. And now I want to start playing with ComfyAI and get more involved with understanding pipelines and multi step workflows with HuggingFace models. https://huggingface.co/learn Good Luck
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There's a lot of good books on using CUDA, learn CUDA, then use the rocm documentation to port your cuda code to ROCM.
Amd
rocm-handbook.amd.com
AMD ROCm Programming Guide — AMD ROCm Programming Guide 7.2.4
Multi-kernel programming: breadth-first search tutorial · HIP compilers · Performance optimization techniques · Understanding GPU performance · Performance guidelines · Optimizing performance · Highly parallel workload: image gamma correction · Fixed-size kernels: image gamma correction · Reduction · Tiling and reuse: matrix multiplication · Tiling and coalescing: matrix transpose · Multi-GPU programming · ROCm platform ·
AMD
amd.com › https://www.amd.com/en.html › developer central › rocm™ hub › training videos
AMD ROCm™ Platform Training Videos
June 24, 2024 - This presentation goes over the AMD Instinct™ architecture and the basics of developing applications within the AMD ROCm ecosystem.
AMD ROCm
rocm.docs.amd.com › projects › ai-developer-hub › en › latest
Tutorials for AI developers - ROCm Documentation
The AI Developer Hub contains AMD ROCm tutorials in Jupyter Notebook format for training, fine-tuning, and inference.
AMD ROCm
rocm.docs.amd.com › en › docs-5.0.2 › examples › all.html
All Tutorial Material — ROCm 5.0.2 Documentation Home
Detailed walkthroughs of specific use-cases driven by frameworks using ROCm acceleration.
AMD GPUOpen
gpuopen.com › learn › amd-lab-notes › amd-lab-notes-rocm-installation-readme
AMD ROCm™ installation - AMD GPUOpen
Installation of the AMD ROCm™ software package can be challenging. This introductory material shows how to install ROCm on a workstation with an AMD GPU card that supports the AMD GFX9 architecture.
Reddit
reddit.com › r/amd › getting started with rocm
r/Amd on Reddit: Getting started with rocM
August 28, 2023 -
Hello,
I recently acquired a new PC including the 7900 xtx and 7800x3d and wanted to try to run rocm. I already found the documentation:
https://rocm.docs.amd.com/en/latest/index.html
However i wanted to ask if there is a community that is active and discusses current progression/bugs etc. I honestly cant find much information online however it is probably a relativley niche topic since most people use nvidia.
I will also probably have to install a supported OS and the respective kernel accourding to : https://rocm.docs.amd.com/en/latest/release/gpu_os_support.html
How accurate is this? I currently have Ubuntu 22.04.3 with kernel 6.2.0-26-generic, its neither in the supported nor unsupported tab.
Also what about the disadvantages of dockerization? It sounds pretty good and useful but will the perfomance suffer? Im familiar with docker to some degree but im kinda sceptical how it works to pass the actual physcial gpu to the Container.
Also i would be grateful for every information/source you can give me. Also grateful for every advice.
Top answer 1 of 5
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I use fedora 38 with rocm. I target the rhel 9.2 repo that amd hosts for rocm bits. Make sure to exclude dkms during install if your using a gui Linux, as you'll already have the driver loaded. Unfortunately it is extremely niche, amd users that also use Linux, that also want to play ai/ml, tiny subset of people that are capable of even reaching the starting line. Good news is it works great. I've run native stable diffusion with all kinds of models and model add ons via rocm on my 6800 xt. Just recently got mlc-llm fully working with the new llama2 llm models too. I'm getting 70+ tokens per second, amazing performance. Really cool stuff going on, the people that say amd can't do ml/ai are just lazy. And with all the vram, even a 6800 can run huge 13b models with crazy performance. Here's the article that got me going with the llama2 stuff. I had to compile some stuff to get the 6800xt working, but if you have 7000 series it's all precompiled. https://blog.mlc.ai/2023/08/09/Making-AMD-GPUs-competitive-for-LLM-inference
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r/ROCm ?
YouTube
youtube.com › playlist
AMD ROCm™ Software Tutorials - YouTube
Learn how to build, optimize, and deploy AI and HPC applications with AMD ROCm™ software. These step-by-step tutorials and educational how-to videos cover in...
GitHub
github.com › pkucnc › awesome-rocm
GitHub - pkucnc/awesome-rocm: Collections and tutorials for ROCm · GitHub
A collection of userful information and tutorials for using ROCm.
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AMD ROCm
rocmdocs.amd.com › en › latest › Installation_Guide › Installation-Guide.html
Quick start installation guide — ROCm installation (Linux)
Then select your operating system and version, and run the provided commands to install the AMD GPU and ROCm.
Readthedocs
doc-aug-21.readthedocs.io › en › latest › Programming_Guides › Programming-Guides.html
Programming Guide — ROCm Documentation 1.0.0 documentation
Follow the instruction here to setup the ROCm apt repository and install the rocm or the rocm-dev meta-package for RHEL/CentOS. Currently, HCC support for RHEL 7.4 and CentOS 7 is experimental and the compiler has to be built from source.
Reddit
reddit.com › r/rocm › rocm 7.2 official installation instructions
r/ROCm on Reddit: ROCm 7.2 official installation instructions
January 22, 2026 -
Windows (requires 26.1.1 driver): PyTorch via PIP installation — Use ROCm on Radeon and Ryzen
Linux: Install Radeon software for Linux with ROCm — Use ROCm on Radeon and Ryzen
Release notes: https://rocm.docs.amd.com/en/latest/about/release-notes.html
Top answer 1 of 5
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Holy shit AMD crew. Either I am doing something wrong or there is a RADICAL performance boost for inferring diffusion models. I just ran a 5 second wan, 3 samplers (6 steps total). It normally takes me 10 minutes. It just ran in 190 seconds. FP16! I am on an r9700. Did we just more than double our speed? lol holy smokes 2nd generation of 5s is down to 172s. fp16 6 steps 3 samplers this nutty. [edit] Testing some other models and workflows for image gen in comfy. 7.2 on linux is a MASSIVE perf boost. Insane. I was coming off 6.4.1
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Hi everyone, I wanted to share my recent experience with the latest ROCm setup for ComfyUI and why I decided to revert to Zluda. Outdated Default Version: The ComfyUI version bundled with the driver is the older 0.3.x. As expected, it lacks the latest features and doesn't provide optimal performance. Lack of Memory Optimization: I tried setting up a fresh ComfyUI environment using Python 3.12 and the latest PyTorch. However, when running VRAM-intensive models like Qwen, I immediately hit OOM (Out of Memory) errors. Compared to NVIDIA, there seems to be almost no efficient memory management or reduction for these models on ROCm. Severe Performance Drop during OOM: Once it hits the memory limit, the slowdown is unbearable. It becomes 3 to 5 times slower than generating images via Zluda. In my case, it took over 100 seconds just to complete a single iteration (1it). Because of these issues, I’ve decided to give up on using ComfyUI with the latest native PyTorch for now and am switching back to the Zluda-based setup. My Specs: GPU: AMD Radeon RX 7900 XTX (24GB) CPU: AMD Ryzen 9 7950X3D RAM: 64GB DDR5-5600
ENCCS
enccs.github.io › amd-rocm-development
Developing Applications with the AMD ROCm Ecosystem — Developing Applications with the AMD ROCm Ecosystem documentation
It covers how to develop and port applications to run on AMD GPU and CPU hardware on top AMD-powered supercomputers. You will learn about the ROCm software development languages, libraries, and tools, as well as getting a developer’s view of the hardware that powers the system.
ENCCS
enccs.github.io › amd-rocm-development › exercises-1
Exercises — Developing Applications with the AMD ROCm Ecosystem documentation
For an interactive session, we’ll use “salloc -N 1 -p MI250 –gpus=1 -t 10” or “salloc -N 1 -p MI210 –gpus=1 -t 10” for these exercises so that the nodes can be shared. Check what is available with “sinfo” and look for a partition with nodes in the “idle” state.
Readthedocs
cgmb-rocm-docs.readthedocs.io › en › latest › index.html
Welcome to AMD ROCm™ Platform — ROCm 4.5.0 documentation
Tools, guidance and insights are shared freely across the ROCm GitHub community and forums.