00-Environment

🛠️ ROCm Environment Setup

Unified environment baseline · ROCm 10.0.0 (TheRock + ROCm.AI) · Prerequisite for all subsequent chapters

Introduction

This chapter serves as the environment baseline for the entire hello-rocm project. It targets ROCm 10.0.0 (ROCm Core SDK, released 2026-08-26) and covers installation, verification, and uninstallation on both Windows and Ubuntu.

All subsequent chapters (01-Deploy, 02-Fine-tune, etc.) depend on this setup. To use a different ROCm version or GPU architecture, refer to the GPU Architecture Reference Table for substitutions. For 10.0.0 vs 7.14.0, plus AMD Skills / Hyperloom / ROCm CLI, see the ROCm 10.0.0 release notes.

🚀 Major release: ROCm 10.0.0 is built on TheRock and ships ROCm.AI for the first time. 7.14.0 finished the move from a monolithic bundle to a modular Core SDK. 10.0.0 folds install, validation, serving, and optimization into three new entry points:
AMD Skills: official AMD optimization knowledge inside Claude / Cursor / Codex;
Hyperloom: an open-source auto-optimizer that profiles, finds bottlenecks, rewrites kernels, and tunes parameters;
ROCm CLI: install, verify, deploy, and manage from one command surface.
The pip / uv flow still works, but the wheel index moved from repo.amd.com/rocm/whl-multi-arch/ to https://stable.repo.amd.com/rocm/whl-next/. Linux apt / dnf repos now live on stable.repo.amd.com. See the TheRock transition guide and the official latest docs.

💡 Platform recommendation: Windows supports ROCm for quick inference and experimentation, but the full ROCm toolchain (rocminfo, amd-smi, multi-GPU, containerized deployment, etc.) is best supported on Ubuntu. We recommend Ubuntu 24.04 as the primary development environment; Windows works well for lightweight inference and quick testing.

⚠️ Windows users must read: Before installation, verify that your Adrenalin Driver version and Windows version meet the requirements (see version table below), or ROCm will not function.

Version Requirements

Item	Requirement	Download
ROCm	10.0.0 (ROCm Core SDK / TheRock)	Official install page
PyTorch	2.13.0	Via uv (see below)
Python	3.11 / 3.12 / 3.13 / 3.14	Managed by uv
Windows Version	11 25H2	—
Adrenalin Driver (Windows)	26.8.1	⬇️ Download Adrenalin 26.8.1
Visual Studio 2022 (Windows)	Community, select "Desktop development with C++"	⬇️ Download VS 2022
Ubuntu	24.04.4 (GA kernel 6.8) / 26.04 (GA kernel 7.0)	Ubuntu Downloads

⚠️ Ryzen APU users note (Ubuntu 24.04): Ryzen APUs (gfx1150 / 1151 / 1152 / 1153 / 1103) require the OEM kernel 6.14 on Ubuntu 24.04: sudo apt install linux-oem-24.04c, then reboot.

AI Ecosystem Compatibility

ROCm 10.0.0 provides optimized support for popular deep learning frameworks and AI inference engines (a full upgrade over 7.14.0):

Framework / Engine	Supported Version	Notes
PyTorch	2.13.0	Also 2.12.0 / 2.11.0; Windows is validated on 2.13.0
JAX	0.11.0	Also 0.10.2 / 0.10.0
vLLM	0.27.0	Official images cover gfx1151 and other client / APU targets
SGLang	0.5.15	Instinct and selected Radeon GPUs
TensorFlow	2.21	Also 2.20 / 2.19.1

💡 These versions replace the 7.14.0-era PyTorch 2.12.0 / JAX 0.10.0 / vLLM 0.23.0 / SGLang 0.5.13. See vLLM inference. Full delta: ROCm 10.0.0 release notes.

ROCm 10.0.0 Release Notes
GPU Architecture Reference Table (separate file)
1. Windows Installation
2. Ubuntu Installation
- 2.5 Alternative: apt Install (TheRock)
- 2.6 Alternative: ROCm CLI
3. Verify Installation
4. Uninstall ROCm
5. Switching GPU Architectures

1. Windows 11 Installation

Example: Ryzen AI Max+ 395 (gfx1151)
📖 Official docs: Install ROCm on Windows | Install PyTorch

1.1 Prerequisites Check

✅ Check	Requirement
Windows Version	Must be Windows 11 25H2 (Settings → System → About)
Adrenalin Driver	Must be 26.8.1 (⬇️ Download)
Visual Studio 2022 (Optional)	Community edition, select "Desktop development with C++" (⬇️ Download). Required for AMD Quark or custom op compilation

Visual Studio installer — select Desktop development with C++

1.2 Remove Conflicting Software

Control Panel → Programs → Uninstall a program → Remove all HIP SDK entries (HIP SDK is retired in 10.0.0; Windows and Linux now share the ROCm Core SDK)

1.3 Disable Windows Security Features

The following features interfere with ROCm and must be disabled:

WDAG: Control Panel → Programs and Features → Turn Windows features on or off → Uncheck "Microsoft Defender Application Guard"
SAC: Settings → Privacy & Security → Windows Security → App & browser control → Smart App Control settings → Off

1.4 Install uv (Python Package Manager)

This project uses uv to manage Python environments and dependencies, replacing the traditional pip + venv workflow. uv is written in Rust and is 10-100x faster.

powershell

# Windows install (PowerShell)
irm https://astral.sh/uv/install.ps1 | iex

# Or via winget
# winget install astral-sh.uv

# Verify
uv --version

📖 More install methods: uv documentation

1.5 Install ROCm + PyTorch

powershell

# Install Python 3.12 (uv has built-in version management)
uv python install 3.12

# Create virtual environment
uv venv --python 3.12
.venv\Scripts\activate

# Install PyTorch (the wheel already includes the ROCm runtime; gfx1151 = Ryzen AI Max+ 395/390/385)
uv pip install --index-url https://stable.repo.amd.com/rocm/whl-next/ "torch[device-gfx1151]==2.13.0+rocm10.0.0" "torchvision[device-gfx1151]==0.28.0+rocm10.0.0" "torchaudio==2.11.0.2+rocm10.0.0"

# Install other project dependencies (if requirements.txt exists)
uv pip install -r requirements.txt

⚠️ Do NOT copy ROCm DLLs to System32 — this causes conflicts.
💡 10.0.0 index: wheels come from https://stable.repo.amd.com/rocm/whl-next/, and you still select the GPU via the [device-gfxXXXX] extra. The gfx1151 above is the Ryzen AI Max series (395/390/385). For other GPUs, swap the architecture tag:
Your GPU device extras tag
Ryzen AI 9 HX (PRO) 475 / 375 etc. device-gfx1150
Ryzen AI 7 (PRO) 450 / 350 etc. device-gfx1152
Ryzen AI 7 445 / AI 5 435 device-gfx1153
Radeon RX 9070 XT / 9070 GRE / AI PRO R9700S device-gfx1201
Radeon RX 9060 XT / 9060 XT LP / 9060 / RX 9050 (new in 10.0.0) device-gfx1200
Radeon RX 7900 XTX / PRO W7900 device-gfx1100
Instinct MI300X / MI325X device-gfx942
All architectures (larger, broadest compatibility) device-all
For example, gfx1150: "torch[device-gfx1150]==2.13.0+rocm10.0.0".
Full reference: GPU Architecture Table or Official Compatibility Matrix.

Your GPU	device extras tag
Ryzen AI 9 HX (PRO) 475 / 375 etc.	`device-gfx1150`
Ryzen AI 7 (PRO) 450 / 350 etc.	`device-gfx1152`
Ryzen AI 7 445 / AI 5 435	`device-gfx1153`
Radeon RX 9070 XT / 9070 GRE / AI PRO R9700S	`device-gfx1201`
Radeon RX 9060 XT / 9060 XT LP / 9060 / RX 9050 (new in 10.0.0)	`device-gfx1200`
Radeon RX 7900 XTX / PRO W7900	`device-gfx1100`
Instinct MI300X / MI325X	`device-gfx942`
All architectures (larger, broadest compatibility)	`device-all`

2. Ubuntu 24.04 Installation

Example: Ryzen AI Max+ PRO 395 (gfx1151)
📖 Official docs: Install ROCm on Ubuntu | Install PyTorch

2.1 Install uv and Dependencies

bash

sudo apt install -y libatomic1 libquadmath0

# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh

# Verify
uv --version

2.2 Install ROCm + PyTorch (uv, recommended)

bash

# Install Python 3.12
uv python install 3.12

# Create virtual environment
uv venv --python 3.12
source .venv/bin/activate

# Install PyTorch (the wheel already includes the ROCm runtime; gfx1151 = Ryzen AI Max+ 395/390/385)
uv pip install --index-url https://stable.repo.amd.com/rocm/whl-next/ "torch[device-gfx1151]==2.13.0+rocm10.0.0" "torchvision[device-gfx1151]==0.28.0+rocm10.0.0" "torchaudio==2.11.0.2+rocm10.0.0"

# Install other project dependencies (if requirements.txt exists)
uv pip install -r requirements.txt

💡 For other GPUs, just swap the architecture tag in the extra (e.g. device-gfx1150, device-gfx942, device-all) — see Section 1.5 or the GPU Architecture Table.

2.3 Alternative: One-Click Install Script

For a fully automated installation (kernel, driver, ROCm), use the project's install script:

bash

git clone -b unified-installer https://github.com/amdjiahangpan/rocm-install-script.git
cd rocm-install-script
chmod +x install.sh
sudo ./install.sh

📖 Script details and options: rocm-install-script (unified-installer branch)

2.4 Configure GPU Access Permissions (Linux)

💡 This step can be done anytime after installation; takes effect after reboot.

bash

sudo usermod -a -G render,video "$LOGNAME"
# Log out and back in, or reboot

2.5 Alternative: apt Install (TheRock)

💡 If you don't use pip / uv and prefer a system-wide install via the system package manager (apt), TheRock packaging continues from 7.14.0 into 10.0.0: package names stay amdrocm-*, and the repo moves to stable.repo.amd.com.

Change	ROCm Core SDK 10.0.0	ROCm Legacy (7.2 and earlier)
Install directory	`/opt/rocm/core`	`/opt/rocm/`
Package prefix	`amdrocm-*` (e.g. `amdrocm-blas`)	`rocm-` / `roc` / `hip*`
Repository	`https://stable.repo.amd.com/rocm/core/packages/`	Older `repo.amd.com` layout
Library lookup	Installed packages embed RPATH (before `LD_LIBRARY_PATH`)	RUNPATH / manual `LD_LIBRARY_PATH`

bash

sudo apt update
sudo apt install sudo wget gpg
# Add the 10.0.0 stable repo (Ubuntu 24.04 example):
sudo mkdir --parents --mode=0755 /etc/apt/keyrings
wget https://stable.repo.amd.com/rocm/gpg/packages.gpg -O - | \
  gpg --dearmor | sudo tee /etc/apt/keyrings/amdrocm.gpg > /dev/null

sudo tee /etc/apt/sources.list.d/amdrocm-stable.sources <<'EOF'
X-Repo-Id: amdrocm-stable
Types: deb
URIs: https://stable.repo.amd.com/rocm/core/packages/ubuntu2404/
Suites: stable
Components: main
Architectures: amd64
Signed-By: /etc/apt/keyrings/amdrocm.gpg
Enabled: yes
EOF

sudo apt update
# Use the meta-package name shown on the official install page

✅ Compatibility: the Core SDK keeps an ABI/API compatibility path with ROCm 7.2 legacy. With apt, the amdrocm meta package still configures update-alternatives for /opt/rocm/bin and /opt/rocm/lib. For tarball installs, point PATH / LD_LIBRARY_PATH / ROCM_PATH at /opt/rocm/core.
⚠️ Note: keep using amd-smi (rocm-smi was removed in 7.14.0). ASAN packages ship with 10.0.0. Installed DEB / RPM / runfile packages now use RPATH, so a multi-version machine is less likely to pick up the wrong libraries from LD_LIBRARY_PATH.
📖 Official selector: Install ROCm.

2.6 Alternative: ROCm CLI

If you do not want to copy pip extras by hand, use the ROCm.AI ROCm CLI (Technology Preview):

bash

curl -fsSL https://raw.githubusercontent.com/ROCm/rocm-cli/main/install.sh | sh
rocm examine          # GPU / driver / runtime
rocm install sdk      # TheRock wheels into a CLI-managed environment
rocm serve qwen       # local OpenAI-compatible server

Windows:

powershell

irm https://raw.githubusercontent.com/ROCm/rocm-cli/main/install.ps1 | iex

Minimum Linux is Ubuntu 24.04. If a 7.14.0 hand-built .venv is already present, rocm examine reports it as unmanaged and rocm install sdk creates a managed runtime beside it. Details: ROCm 10.0.0 release notes.

3. Verify Installation

3.1 PyTorch Check (Windows / Linux)

bash

python -c "import torch; print('PyTorch:', torch.__version__); print('ROCm available:', torch.cuda.is_available()); print('Device:', torch.cuda.get_device_name(0) if torch.cuda.is_available() else 'N/A')"

Expected output:

PyTorch: 2.13.0+rocm10.0.0
ROCm available: True
Device: AMD Radeon Graphics

💡 ROCm uses HIP to provide CUDA API compatibility, so torch.cuda.is_available() returning True is expected behavior.

3.2 Simple Computation Test

python

import torch
x = torch.randn(3, 3, device='cuda')
y = torch.randn(3, 3, device='cuda')
print(x @ y)

3.3 Linux-only Tools

bash

rocminfo | grep -E "Name:|Marketing Name:"
amd-smi monitor   # ROCm SMI was removed in 7.14.0 — use amd-smi
hipinfo           # available with pip installation

3.4 Troubleshooting

Symptom	Cause	Solution
`torch.cuda.is_available()` = `False`	Driver version mismatch	Windows: confirm Adrenalin 26.8.1; Linux: confirm inbox / OEM kernel (Ryzen APUs need `linux-oem-24.04c`)
`No GPU detected` (Linux)	Not in render/video group	`sudo usermod -a -G render,video $LOGNAME` + reboot
DLL load error (Windows)	SAC/WDAG not disabled	See Section 1.3

4. Uninstall ROCm

Windows

Simply delete the .venv folder (via File Explorer, or in CMD):

cmd

rmdir /s /q .venv

To uninstall Adrenalin driver: Control Panel → Programs → Uninstall a program → AMD Software

Ubuntu

bash

rm -rf .venv

5. Switching GPU Architectures

Since 10.0.0, wheels are served from https://stable.repo.amd.com/rocm/whl-next/, and you still select the architecture via the [device-gfxXXXX] extra. Replace the architecture tag in the install command:

GPU Example	LLVM Target	device extras tag
MI355X / MI350X / MI350P	gfx950	`device-gfx950`
MI300X / MI325X	gfx942	`device-gfx942`
RX 9070 XT / 9070 GRE / AI PRO R9700S	gfx1201	`device-gfx1201`
RX 9060 XT / 9060 XT LP / 9060 / RX 9050 (new in 10.0.0)	gfx1200	`device-gfx1200`
RX 7900 XTX / PRO W7900	gfx1100	`device-gfx1100`
Radeon PRO W6800 / V620	gfx1030	`device-gfx1030`
Ryzen AI Max 395	gfx1151	`device-gfx1151`
Ryzen AI PRO 400 / AI 9 HX 475	gfx1150	`device-gfx1150`
Ryzen AI 200 PRO / AI 7 350	gfx1152	`device-gfx1152`
Ryzen AI 7 445 / AI 5 435	gfx1153	`device-gfx1153`
All architectures	—	`device-all`

For example, to switch to gfx942 (MI300X):

bash

uv pip install --index-url https://stable.repo.amd.com/rocm/whl-next/ "torch[device-gfx942]==2.13.0+rocm10.0.0" "torchvision[device-gfx942]==0.28.0+rocm10.0.0" "torchaudio==2.11.0.2+rocm10.0.0"

💡 For the apt path, add the stable.repo.amd.com repo from Section 2.5, then use the meta-package name shown on the official install page.

Full reference: GPU Architecture Table

📖 Official documentation:
ROCm 10.0.0 docs home
ROCm 10.0.0 release notes (this project)
ROCm 10.0.0 Release Notes
TheRock Transition Guide
Compatibility Matrix
Install ROCm
Install PyTorch
vLLM Inference
AMD Skills
ROCm CLI
Hyperloom

00-Environment

Introduction ​

Version Requirements ​

AI Ecosystem Compatibility ​

Table of Contents ​

1. Windows 11 Installation ​

1.1 Prerequisites Check ​

1.2 Remove Conflicting Software ​

1.3 Disable Windows Security Features ​

1.4 Install uv (Python Package Manager) ​

1.5 Install ROCm + PyTorch ​

2. Ubuntu 24.04 Installation ​

2.1 Install uv and Dependencies ​

2.2 Install ROCm + PyTorch (uv, recommended) ​

2.3 Alternative: One-Click Install Script ​

2.4 Configure GPU Access Permissions (Linux) ​

2.5 Alternative: apt Install (TheRock) ​

2.6 Alternative: ROCm CLI ​

3. Verify Installation ​

3.1 PyTorch Check (Windows / Linux) ​

3.2 Simple Computation Test ​

3.3 Linux-only Tools ​

3.4 Troubleshooting ​

4. Uninstall ROCm ​

Windows ​

Ubuntu ​

5. Switching GPU Architectures ​

Introduction

Version Requirements

AI Ecosystem Compatibility

Table of Contents

1. Windows 11 Installation

1.1 Prerequisites Check

1.2 Remove Conflicting Software

1.3 Disable Windows Security Features

1.4 Install uv (Python Package Manager)

1.5 Install ROCm + PyTorch

2. Ubuntu 24.04 Installation

2.1 Install uv and Dependencies

2.2 Install ROCm + PyTorch (uv, recommended)

2.3 Alternative: One-Click Install Script

2.4 Configure GPU Access Permissions (Linux)

2.5 Alternative: apt Install (TheRock)

2.6 Alternative: ROCm CLI

3. Verify Installation

3.1 PyTorch Check (Windows / Linux)

3.2 Simple Computation Test

3.3 Linux-only Tools

3.4 Troubleshooting

4. Uninstall ROCm

Windows

Ubuntu

5. Switching GPU Architectures