I have always been a huge fan of gaming and a bit of a gaming nerd.

Since childhood, the only requirement I saw for graphics cards was for the purpose of gaming.

Luckily for me, after I started getting into artificial intelligence and data science, especially deep learning, I realized the true potential of graphics cards.

This was almost like a dream come true. It was like striking two bullseyes with one arrow because I could utilize the same single graphics card for gaming as well as study and research purposes.

Note:_ GPUs and graphics cards pretty much mean the same thing and will be used interchangeably throughout this article._

GPUs are optimized for training artificial intelligence and deep learning models as they can process multiple computations simultaneously. They have a large number of cores, which allows for the better computation of multiple parallel processes.

In this article, we will understand what exactly a GPU and CUDA is, then explore the benefits of graphics processing units as well as when you should consider buying it if you are on a budget constraint. Finally, we will discuss the alternatives.

Without further ado, let us get started with understanding these concepts.

What is a GPU exactly?

Photo by Nana Dua on Unsplash

A Graphics Processing Unit is a specialized, electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device.

GPUs are a key part of modern computing. GPU computing and high-performance networking are transforming computational science and AI. The advancements in GPUs contribute a tremendous factor to the growth of deep learning today.

NVIDIA provides something called the Compute Unified Device Architecture (CUDA), which is crucial for supporting the various deep learning applications.

CUDA is a parallel computing platform and application programming interface model created by Nvidia. It allows software developers and software engineers to use a CUDA-enabled graphics processing unit (GPU) for general-purpose processing — an approach termed GPGPU.

These CUDA cores are highly beneficial and evolutionary in the field of artificial intelligence. We will discuss this topic further in the next section.

#deep-learning #machine-learning #artificial-intelligence #data-science #gpu