Authors: 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

Published on: February 05, 2024

Impact Score: 8.15

Arxiv code: Arxiv:2402.03480

Summary

• What is new: Entering the era of Trillion Parameter Models (TPM) in AI, focusing on the ecosystem for scientific research.
• Why this is important: Scaling and serving TPMs for scientific research poses significant system design challenges.
• What the research proposes: A comprehensive software stack and flexible interfaces tailored for the scientific community’s needs.
• Results: Outlines the vision and initial steps towards enabling TPMs for scientific discoveries.

Technical Details

Technological frameworks used: Not specified in the abstract

Models used: Trillion Parameter Models, example: Huawei’s PanGu-$\\Sigma$

Data used: Not specified in the abstract

Potential Impact

AI research firms, cloud service providers, scientific research communities

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