GPU

A Graphics Processing Unit (GPU) is a specialized electronic circuit initially designed to accelerate the rendering of images and videos for computer displays. Unlike a Central Processing Unit (CPU), which typically has a few powerful cores optimized for sequential processing (handling tasks one after another), a GPU is built with thousands of smaller, more specialized cores. This architectural difference allows GPUs to perform a massive number of calculations simultaneously, a concept known as parallel processing.

This inherent ability to handle many operations at once makes GPUs exceptionally well-suited for Artificial Intelligence (AI) workloads, particularly in areas like machine learning and deep learning. AI models, especially deep neural networks, involve vast amounts of matrix multiplications and other linear algebra operations that can be broken down into numerous independent, simple calculations. A GPU can distribute these calculations across its thousands of cores, executing them concurrently. This dramatically speeds up the training of complex AI models, often reducing training times from days to hours, and enables real-time inference (applying a trained model to new data) in applications like image recognition, natural language processing, and autonomous driving.

Elastx offers a number of different GPU models in our Openstack IaaS and Kubernetes CaaS to match the required performance and capacity.

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