In this session, we will learn the basics of graphics processing unit (GPU) architecture, and how to exploit these powerful computational tools to accelerate mathematical manipulations of large arrays by orders of magnitude compared to what is possible on CPUs. This exercise will be conducted entirely in python, and will also introduce the audience to using the new A100 GPU nodes on Engaging available to all of MKI. The only prerequisite for the workshop for those who want to follow along with the interactive demo is the ability to ssh into the Engaging cluster, and a text editor for writing code. The level of coding will be simple, such that anyone familiar with numpy and basic matrix algebra (e.g. how to multiply a matrix) will be able to comfortably follow the lesson. By the end of the lesson, we will have implemented the Lomb-Scargle algorithm on a GPU from scratch.