GPU Programming for Beginners: ROCm + AMD Setup to Edge Detection

In this hands-on tutorial, we demystify GPU computation and show you how to write your own GPU programs from scratch. Understanding GPU programming is essential for anyone looking to grasp why AI models depend on this specialized hardware. We'll use ROCm and HIP (AMD's version of CUDA) to take you from zero to running real GPU code, culminating in a computer vision edge detector that processes images in parallel. You can find the code in the project repository : https://github.com/oconnoob/intro_to_rocm_hip/blob/main/README.md 👇 WHAT YOU'LL LEARN IN THIS VIDEO 👇 🔧 Getting Set Up with ROCm Two ways to get started : spin up a GPU Droplet on DigitalOcean with ROCm pre-installed, or install ROCm yourself on an Ubuntu system with an AMD GPU. We cover both methods step-by-step. ➕ Example 1 : Vector Addition (The Basics) Learn the fundamental structure of GPU programs—kernels, threads, blocks, and memory management. We'll add one million elements in parallel and verify our results. ⚡ Example