GPU for DL: Benefits and Drawbacks of On-Premises vs. Cloud

As technology advances and more organizations are implementing machine learning operations (MLOps), people are looking for ways to speed up processes. This is especially true for organizations working with deep learning (DL) processes which can be incredibly long to run. You can speed up this process by using graphical processing units (GPUs) on-premises or in the cloud.

GPUs are microprocessors that are specially designed to perform specific tasks. These units enable parallel processing of tasks and can be optimized to increase performance in artificial intelligence and deep learning processes.