A Beginner’s guide to AI Processors: CPUs, GPUs, TPUs and LPUs
As Artificial Intelligence (AI) technology continues to evolve, need for understanding the role of specialised hardware that power AI applications is important. From training machine learning models to processing big data, the choice of processor impacts the efficiency and performance of AI tasks. Whether you are a developer, data scientist, or tech enthusiast, this guide will help you to understand the most common types of AI hardware: CPUs, GPUs, TPUs, and LPUs.
CPU: All-Rounder
Central Processing Unit (CPU) is the traditional heart of a computer, capable of handling a variety of tasks from basic calculations to complex software operations.
Examples : Intel Core processors and Apple M1/M2 chips
- Best for: General-purpose computing, smaller datasets, or tasks requiring complex logic where data processing needs are sequential.
- Application: Running data preprocessing or light machine learning models like linear/logistic regression on a dataset with less number of data points
GPU: Speedster
Graphics Processing Units (GPUs) are known for their ability to handle multiple operations simultaneously in parallel, making them ideal for graphics rendering in Games and AI computations.