Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision

no code implementations • 5 Feb 2024 • Nathaniel Hudson, J. Gregory Pauloski, Matt Baughman, Alok Kamatar, Mansi Sakarvadia, Logan Ward, Ryan Chard, André Bauer, Maksim Levental, Wenyi Wang, Will Engler, Owen Price Skelly, Ben Blaiszik, Rick Stevens, Kyle Chard, Ian Foster

Deep learning methods are transforming research, enabling new techniques, and ultimately leading to new discoveries.

Hierarchical and Decentralised Federated Learning

no code implementations • 28 Apr 2023 • Omer Rana, Theodoros Spyridopoulos, Nathaniel Hudson, Matt Baughman, Kyle Chard, Ian Foster, Aftab Khan

Hierarchical Federated Learning is likely to be a key enabler for a wide range of applications, such as smart farming and smart energy management, as it can improve performance and reduce costs, whilst also enabling FL workflows to be deployed in environments that are not well-suited to traditional FL.

energy management Federated Learning