github/ROCm
1
1
Fork 0
mirror of https://github.com/ROCm/ROCm.git synced 2026-01-09 14:48:06 -05:00
Code Issues Packages Projects Releases Wiki Activity

Deep learning framework doc highlight update to RN 6.4.2 (#474)

Browse Source 
* HIP 7.0 upcoming changes blog link updated

* Documentation highlight for deep learning framework added

* Note loading fixed

* Note removed

* Link fixed
This commit is contained in:
Pratik Basyal
2025-07-21 14:17:10 -04:00
committed by GitHub
parent 2bbcfc8f92
commit 977c74fe71
2 changed files with 6 additions and 83 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
RELEASE.md
View File

@@ -80,6 +80,12 @@ ROCm documentation continues to be updated to provide clearer and more comprehen
For more information about the changes, see [Changelog for the AI Developer Hub](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/changelog.html).
* ROCm provides a comprehensive ecosystem for deep learning development. For more details, see [Deep learning frameworks for ROCm](https://rocm.docs.amd.com/en/latest/how-to/deep-learning-rocm.html). As of July 2025, AMD ROCm provides support for the following additional deep learning frameworks:
* Deep Graph Library is an easy-to-use, high-performance, and scalable Python package for deep learning on graphs. DGL is framework agnostic, meaning if a deep graph model is a component in an end-to-end application, the rest of the logic is implemented using PyTorch. It is currently supported on ROCm 6.4.0. For more information, see [DGL compatibility](https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/dgl-compatibility.html).
* Stanford Megatron-LM is a large-scale language model training framework. It’s designed to train massive transformer-based language models efficiently by model and data parallelism. It is currently supported on ROCm 6.3.0. For more information, see [Stanford Megatron-LM compatibility](https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.html).
* Volcano Engine Reinforcement Learning for LLMs (verl) is a reinforcement learning framework designed for large language models (LLMs). verl offers a scalable, open-source fine-tuning solution optimized for AMD Instinct GPUs with full ROCm support. It is currently supported on ROCm 6.2.0. For more information, see [verl compatibility](https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/verl-compatibility.html).
* Documentation for the new [ROCprof Compute Viewer](https://rocm.docs.amd.com/projects/rocprof-compute-viewer/en/amd-mainline/) was added in May 2025. This tool is used to visualize and analyze GPU thread trace data collected using [rocprofv3](https://rocm.docs.amd.com/projects/rocprofiler-sdk/en/latest/index.html). Note that [ROCprof Compute Viewer](https://rocm.docs.amd.com/projects/rocprof-compute-viewer/en/amd-mainline/) is in an early access state. Running production workloads is not recommended.
* The AMDGPU installer documentation has been removed to encourage the use of the package manager for ROCm installation. While the package manager is the recommended method, you can still install ROCm using the AMDGPU installer by following the [legacy process](https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.1/install/install-methods/amdgpu-installer-index.html). Ensure to update the command with the intended ROCm version before running it. For more information, see [Installation via native package manager](https://rocm.docs.amd.com/projects/install-on-linux-internal/en/latest/install/install-methods/package-manager-index.html).