In this session we will cover the basics of the NVIDIA GPU (graphics processing unit) and how it can be used in the context of education and research. We will start with an overview of how the GPU functions compared to traditional CPU computing and will follow that with an outline of the existing hardware portfolio. Then we will transition to talk about how you can program for the GPU, and what workloads are well suited to take advantage of the parallel nature of the GPU. Finally, we will have a hands-on demonstration of cutting edge LLMs (large language models) and generative AI workloads that rely on the compute power of the GPU.
Zoe Ryan is a solutions architect at NVIDIA. She's worked in embedded systems/simulations and GPU-accelerated high-performance computing, specifically targeting higher education institutions and researchers to adopt and fully utilize GPU technology.