Towards the Age of Computation and AI for High Performance Climate
Автор: Ai2
Загружено: 2025-05-01
Просмотров: 329
Abstract: In this talk, we will explore the role of computation and
artificial intelligence (AI) in advancing high-performance climate
modeling. We will delve into how computation can simulate and predict
climate change, addressing the limitations of current climate
simulations. With this problem in mind, we will discuss the onset of a
new computational era, highlighted by the rapid growth of AI
infrastructure investments. We realize how this development can help us
to drive finer-grained climate models and discuss the challenges and
computational demands required to achieve higher resolutions. We then
dive into ML-based models with the example of diffusion-based models for
data assimilation, showcasing opportunities and improvements over
traditional methods. Additionally, we will show pitfalls with existing
AI-based weather forecasting networks, using case studies such as Storm
Ciaran and Typhoon Doksuri to underscore their limitations in predicting
extreme events and capturing underlying physics. We will conclude with
an overview of the Swiss AI climate initiative, a project aimed at
developing a foundational model for climate and weather prediction by
integrating more data, advanced models, and higher resolutions. Efforts
to democratize access to climate data through compression techniques
will also be highlighted.
Bio/Photos: Torsten Hoefler is a Professor of Computer Science at ETH Zurich, a member of Academia Europaea, and a Fellow of the ACM, IEEE, and ELLIS. He received the 2024 ACM Prize in Computing, one of the highest honors in the field. His research interests revolve around the central topic of "Performance-centric System Design" and include scalable networks, parallel programming techniques, and performance modeling. Torsten won best paper awards at the ACM/IEEE Supercomputing Conference SC10, SC13, SC14, SC19, SC22, SC23, SC24, HPDC'15, HPDC'16, IPDPS'15, and other conferences. He published hundreds of peer-reviewed scientific conference and journal articles and authored chapters of the MPI-2.2 and MPI-3.0 standards. He received the IEEE CS Sidney Fernbach Award, the ACM Gordon Bell Prize, the ISC Jack Dongarra award, the Latsis prize of ETH Zurich, as well as the German Max Planck-Humboldt Medal. Additional information about Torsten can be found on his homepage at htor.ethz.ch. https://htor.inf.ethz.ch/bio/

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