Description:

The use of artificial intelligence and machine learning algorithms has grown considerably in the past several years, and with that growth has come an increase in demand for faster and larger compute platforms that tailor themselves to quickly and efficiently performing the specialized calculations and data manipulations required. GPUs currently are the true workhorse devices for this task for many reasons, however new processor architectures that are designed with AI in mind from the start are now emerging in the form of IPUs, wafer-scale computers, and other designs touting further performance gains and ease of use. Additionally, new storage systems and memory designs and configurations better tuned to the read and write patterns of AI methods are also coming to market.

This session seeks to explore any of these new AI-centric hardware technologies being put to use in the development of new AI models for weather, water, and climate applications. Submissions are encouraged to not only introduce the innovative AI-centric hardware being used, but also the scientific problem(s) they are being used for, the challenges of using these cutting-edge and oftentimes proprietary technologies in their AI training and evaluation workflows versus more traditional HPC and GPU architectures, and any other useful information that provides insights into the benefits and limitations of these devices.