How to Use Multiple GPUs with TensorFlow (No Code Changes Required)

This article is a hands-on technical guide to configuring TensorFlow for GPU acceleration. It covers everything from detecting and using GPUs with tf.config, controlling memory growth, manually setting device placement, and logging tensor execution across GPUs. It also explores how to scale models across multiple physical or virtual GPUs using both manual strategies and tf.distribute.Strategy. Whether you're running deep learning models locally or preparing for production, this walkthrough helps you unlock and fine-tune TensorFlow's GPU capabilities.