GPU: Definition

A GPU (Graphics Processing Unit) is a specialized processor designed to execute a vast number of calculations in parallel. Originally developed to accelerate image rendering and video games, GPUs have become essential for artificial intelligence workloads, scientific computing, and big data analysis within data centers.

GPU vs. CPU: What Are the Differences?

The comparison between GPUs and CPUs relies primarily on their operating modes and architectures. A CPU executes a variety of instructions sequentially, making it suitable for general-purpose computing and tasks requiring low latency. A GPU adopts a different approach: it simultaneously processes a large volume of identical operations, making it particularly efficient for machine learning, model training, and LLM inference.

The leading GPU manufacturers today are NVIDIA, AMD, and Intel. NVIDIA currently dominates the artificial intelligence market thanks to CUDA (Compute Unified Device Architecture), a software platform enabling users to leverage the parallel computing capabilities of GPUs.

APUs (Accelerated Processing Units) combine a CPU and a graphics processor on a single chip. Alongside these architectures, GPGPU (General-Purpose computing on Graphics Processing Units) refers to using a graphics processor for general computing well beyond graphics rendering.

What Role Do GPUs Play in Data Centers?

In data centers, multiple GPUs can be installed within a single server to accelerate AI model training and inference, as well as simulations and scientific computing.

However, these systems introduce new technical constraints. Increased computing power comes with ever-higher power density, exceeding 100 kW per rack in certain dedicated AI infrastructures. Cooling requirements become a major challenge, as do power supply and the infrastructure's ability to maintain high availability.

Through its network of over 250 Edge data centers in France, including 7 hyperconnected IX data centers, UltraEdge supports businesses in deploying infrastructures capable of hosting latest-generation GPUs while guaranteeing performance, scalability, and availability.