How to Set Up TensorFlow with AMD ROCm GPU Acceleration on Ubuntu 24.04

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TensorFlow, a popular open-source machine learning framework, can be configured to run with AMD GPU acceleration using ROCm, AMD's platform for high-performance GPU computing. A step-by-step guide outlines two approaches: running a pre-configured ROCm-enabled TensorFlow Docker container and installing TensorFlow natively on the host via pip. The containerized method requires pulling the official rocm/tensorflow image and running it with appropriate GPU device flags, while the native install involves matching the TensorFlow version to the installed ROCm release using AMD's support matrix. Both methods allow users to verify GPU availability through TensorFlow's device listing utility. The setup requires an Ubuntu 24.04 server equipped with a ROCm-capable AMD GPU and a pre-configured Docker environment with ROCm support.

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