Prerequisites to use ROCm on Radeon desktop GPUs for machine learning development#
Before starting with the installation, ensure that your system meets the necessary requirements such as supported hardware, a compatible operating system, and the recommended system configuration to ensure optimal performance and functionality.
See Compatibility matrices for more information.
Supported graphics processing units#
To successfully install ROCm™ for machine learning development, ensure that your system is operating on a Radeon™ Desktop GPU listed in the Compatibility matrices section.
The recommended memory to use ROCm on Radeon. These specifications are required for complex AI/ML workloads:
64GB Main Memory
24GB GPU Video Memory
Minimum memory requirements to use ROCm on Radeon. Note that low system memory may cause issues running inference models on CPU.
16GB Main Memory
8GB GPU Video Memory
Supported operating systems#
Ensure that your operating system is up-to-date to successfully install ROCm for machine learning development.
Refer to Compatibility matrices for up-to-date operating system compatibility.
Update Ubuntu® operating system#
Use the following commands to bring your OS up-to-date:
sudo apt-get update
sudo apt-get dist-upgrade
Recommended system configuration#
This section guides users on how to optimize system configuration for ROCm™ usage, ensuring smooth and performant ROCm operation.
The iGPU is non-essential for AI and ML workloads and not officially supported. Disable iGPU in SBIOS before proceeding to avoid unknown issues.
Alternatively, use environment variables to select the target GPU.
Here are examples to disable iGPU on some AMD motherboards:
Gigabyte™ X670 AORUS ELITE AX#
Path: Advanced → AMD CBS → NBIO Common Options → GFX Configuration → iGPU Configuration
Set iGPU to
ASUS Prime X670-P WIFI#
Path: Advanced → NB Configuration → Integrated Graphics
NOTE: This step only applies to AMD motherboards, no action is required for non-AMD motherboards.
There are no minimum motherboard hardware requirements.
Alternative option: Use environment variables to select target GPU#
An alternative option to disabling the iGPU is to use environment variable to select the GPU.
See GPU Isolation Techniques to specify the device indices you would like to expose to your application.