What is a GPU?

A Graphics Processing Unit (GPU) is a processor that uses parallel processing capability and high memory bandwidth to perform specialized tasks such as accelerating graphics rendering and simultaneous computation. GPUs have become essential for applications such as gaming, 3D image processing, video editing, cryptocurrency mining, and machine learning. GPUs are significantly faster and more efficient than CPUs when processing large volumes of numerical calculations.

The need for GPUs in Kubernetes

With the advancement of technology, especially deep learning models, the demand for GPU usage has grown rapidly as technology companies invest heavily in AI. With the emergence of ChatGPT and other language/image/video processing tools that primarily rely on AI processing capability, GPUs have demonstrated their strength. This is why major technology companies want to use GPUs to meet their growing AI requirements.

GPUs are much faster than CPUs in deep learning because the training phase is highly resource-intensive. The GPU architecture, with its many cores and high memory bandwidth, makes the deep learning process significantly more efficient than with CPUs.

Combined with GPUs, Kubernetes is a suitable solution for AI. An increasing number of data scientists are choosing Kubernetes to optimize the training and deployment of AI models for the following reasons: automated deployment, easy scaling, a large and active community, and support for many features.