Linux Installation Instructions#

Ryzen AI for Linux supports running AI models on the AMD Neural Processing Unit (NPU). The current release supports STX and KRK platforms.

With this release, users can now compile and run AI models using the following formats:

CNN models in INT8
CNN models in BF16
NLP models (e.g., BERT, encoder-based) in BF16
LLMs (NPU-only flow)

Prerequisites#

Dependencies	Version Requirement
Ubuntu Distribution	Ubuntu 24.04 LTS
Kernel Version	>= 6.10
RAM	64GB (Recommended)
Python	3.12.x

Use the commands below to install Python 3.12.x along with certain dependencies

sudo apt update
sudo apt install python3.12
sudo apt install python3.12-venv
sudo apt install libboost-filesystem1.74.0

After installing required Ubuntu distribution and Python version, proceed with NPU drivers installation

Install NPU Drivers#

Download the NPU driver package from Downloads section of Ryzen AI Software Drivers.
RyzenAI linux driver package contains
- XRT Package
  
  xrt_202610.2.21.75_24.04-amd64-base.deb
  
  xrt_202610.2.21.75_24.04-amd64-base-dev.deb
  
  xrt_202610.2.21.75_24.04-amd64-npu.deb
- NPU driver package
  
  xrt_plugin.2.21.260102.53.release_24.04-amd64-amdxdna.deb
Install NPU driver package on your machine

sudo apt install --fix-broken -y ./xrt_202610.2.21.75_24.04-amd64-base.deb
sudo apt install --fix-broken -y ./xrt_202610.2.21.75_24.04-amd64-base-dev.deb
sudo apt install --fix-broken -y ./xrt_202610.2.21.75_24.04-amd64-npu.deb
sudo apt install --fix-broken -y ./xrt_plugin.2.21.260102.53.release_24.04-amd64-amdxdna.deb

Set essential Environment variables

export LD_LIBRARY_PATH=/lib/x86_64-linux-gnu:$LD_LIBRARY_PATH
source /opt/xilinx/xrt/setup.sh

Verify your Driver installation

xrt-smi examine

Device(s) Present
|BDF             |Name       |
|----------------|-----------|
|[0000:c5:00.1]  |NPU Strix  |

# NPU name might differ based on your machine

Install Ryzen AI Software#

Download the RyzenAI for Linux package ryzen_ai-1.7.1.tgz from Downloads section of Ryzen AI Software Installer.
Navigate to the downloaded path and follow the below steps

mkdir ryzen_ai-1.7.1
cp ryzen_ai-1.7.1.tgz ryzen_ai-1.7.1

cd ryzen_ai-1.7.1
tar -xvzf ryzen_ai-1.7.1.tgz

Install RyzenAI package at your desired target path

./install_ryzen_ai.sh -a yes -p <TARGET-PATH>/venv
source <TARGET-PATH>/venv/bin/activate

This will successfully install RyzenAI and activate the Virtual environment at your target location

# Validate your installation path
echo $RYZEN_AI_INSTALLATION_PATH

Test the Installation#

The RyzenAI software package contains a test script that verifies your correct installation of NPU Drivers.

Navigate to your targeted Virtual Environment created in the previous step
You will observe a subfolder named “quicktest”

cd <TARGET-PATH>/venv/quicktest
python quicktest.py

The quicktest.py script picks up a simple CNN model, compiles it and runs on AMD’s Neural Processing Unit (NPU).
On successful run, you can observe output as shown below.

Setting environment for STX/KRK

Test Finished

Examples, Demos, Tutorials#

RyzenAI-SW demonstrates various demos and examples for Model compilation and deployment on NPUs
Here are a few examples from our RyzenAI Software Repository

Note#

Before running the above examples -

RyzenAI creates its own Python Virtual Environment to run the examples. You can skip conda environment instruction as they are Windows specific only
Ensure to activate Linux based Python Virtual Environment

source <TARGET-PATH>/venv/bin/activate

Get NPU Info for your Machine#

Getting started Resnet with INT8 Model

Getting started Resnet with INT8 Model contains Resnet_util.py script that has a function “get_npu_info” to detect correct “NPU type” in your machine. This NPU lookup logic is based for Windows system.

For Linux, NPU lookup logic is shown below:

import subprocess

def get_npu_info():
    # Run below command as subprocess to enumerate PCI devices
    command = r'lspci -nn'
    process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
    stdout, stderr = process.communicate()

    # Check for supported Hardware IDs
    npu_type = ''
    if '1022:17f0' in stdout.decode(): npu_type = 'STX/KRK'
    return npu_type

Running LLM#

Follow this page to run LLM models on Linux: Running LLM on Linux

Linux Installation Instructions

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