ML for High-Performance Climate: Data Post Processing, Compression, and Earth Virtualization Engines
Scalable Parallel Computing Lab, SPCL @ ETH Zurich via YouTube
Overview
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Explore cutting-edge applications of machine learning in high-performance climate science, focusing on data post-processing, compression techniques, and Earth virtualization engines. Delve into advanced topics presented by experts from the Scalable Parallel Computing Lab at ETH Zurich in this comprehensive 68-minute conference talk. Gain insights into how ML is revolutionizing climate data handling, enhancing computational efficiency, and enabling more accurate Earth system simulations. Learn about innovative approaches to tackle the challenges of processing and storing massive climate datasets, and discover how Earth virtualization engines are transforming our ability to model and understand complex climate systems.
Syllabus
ML for High-Performance Climate: Data Post Processing, Compression, and Earth Virtualization Engines
Taught by
Scalable Parallel Computing Lab, SPCL @ ETH Zurich