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Project 02: Advanced Parallelization Techniques for datadriven Uncertainty Quantification

Ehret, Uwe [Hrsg.] 1; Frank, Martin [Hrsg.] 2; KIT-Zentrum MathSEE [Hrsg.]; Krumscheid, Sebastian ORCID iD icon 2; Seelinger, Linus ORCID iD icon 2
1 Institut für Wasser und Gewässerentwicklung (IWG), Karlsruher Institut für Technologie (KIT)
2 Scientific Computing Center (SCC), Karlsruher Institut für Technologie (KIT)

Abstract:

02 Advanced Parallelization Techniques for data-driven Uncertainty
Quantification
MATH PI: TT-Prof. Dr. Sebastian Krumscheid, Steinbuch Centre for Computing (SCC), Junior Research
Group Uncertainty Quantification (SCC-UQ) & Institute for Applied and Numerical Mathematics
(IANM)
SEE PI: Dr. Linus Seelinger, YIG Prep Pro Fellow
Department(s): Mathematics
Type of position: 75% FTE, E13 TV-L
In the field of natural sciences, the integration of Bayesian inference and Uncertainty Quantification
(UQ) shows great potential in improving our understanding of complex systems and enhancing the
reliability of scientific predictions. However, UQ often faces challenges as it requires a large number of
simulation runs, which necessitates advanced UQ algorithms and high-performance computing (HPC).
Unfortunately, intricate data dependencies and technical obstacles hinder parallel computing for
inverse (i.e., data-driven) UQ. To address this problem, UM-Bridge introduces a novel software
architecture to UQ, which solves these technical challenges and lays the foundation for developing
sophisticated parallelization strategies at a relatively low compute cost. ... mehr


Zugehörige Institution(en) am KIT KIT-Zentrum Mathematik in den Natur-, Ingenieur- und Wirtschaftswissenschaften (KIT-Zentrum MathSEE)
Scientific Computing Center (SCC)
Publikationstyp Audio & Video
Publikationsdatum 23.10.2023
Erstellungsdatum 19.10.2023
Sprache Englisch
Identifikator KITopen-ID: 1000163236
HGF-Programm 46.21.02 (POF IV, LK 01) Cross-Domain ATMLs and Research Groups
Lizenz KITopen-Lizenz
Serie KCDS Virtual Open House 2023 - Fall
Folge 3
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