Democratizing uncertainty quantification
Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In this paper, we introduce UM-Bridge (the UQ and Modeling Bridge), a high-level abstraction and software protocol that facilitates universal interoperability of UQ software with simulation codes. It breaks down the technical complexity of advanced UQ applications and enables separation of concerns between experts. UM-Bridge democratizes UQ by allowing effective interdisciplinary collaboration, accelerating the development of advanced UQ methods, and making it easy to perform UQ analyses from prototype to High Performance Computing (HPC) scale. In addition, we present a library of ready-to-run UQ benchmark problems, all easily accessible through UM-Bridge. These benchmarks support UQ methodology research, enabling reproducible performance comparisons. We demonstrate UM-Bridge with several scientific applications, harnessing HPC resources even using UQ codes not designed with HPC support.
Authors
- Wolfgang Bangerth (ORCID: https://orcid.org/0000-0003-2311-9402)
- Mikkel B. Lykkegaard (ORCID: https://orcid.org/0000-0002-0932-9668)
- Anne Reinarz (ORCID: https://orcid.org/0000-0003-1787-7637)
- Jakob Sauer Jørgensen (ORCID: https://orcid.org/0000-0001-9114-754X)
- Benjamin M. Kent (ORCID: https://orcid.org/0000-0003-4968-7993)
- Katherine Rosenfeld (ORCID: https://orcid.org/0000-0001-8902-9990)
- Matthew Parno (ORCID: https://orcid.org/0000-0002-9419-2693)
- Matteo Diez (ORCID: https://orcid.org/0000-0001-6113-7893)
- Massimiliano Martinelli (ORCID: https://orcid.org/0000-0003-1481-1069)
- Linus Seelinger (ORCID: https://orcid.org/0000-0001-8632-8493)
- Tim Dodwell
- Amal Alghamdi (ORCID: https://orcid.org/0000-0003-0145-5296)
- Robert Scheichl (ORCID: https://orcid.org/0000-0001-8493-4393)
- Jean Bénézech (ORCID: https://orcid.org/0000-0002-2989-3856)
- Noémi Petra (ORCID: https://orcid.org/0000-0002-9491-0034)
- Riccardo Pellegrini (ORCID: https://orcid.org/0000-0003-4953-3038)
- R. Akers
- Andrea Serani (ORCID: https://orcid.org/0000-0002-8814-1793)
- Nicolai A. B. Riis (ORCID: https://orcid.org/0000-0002-6883-9078)
- David Aristoff (ORCID: https://orcid.org/0000-0002-0347-0812)
- Umberto Villa (ORCID: https://orcid.org/0000-0002-5142-2559)
- Lorenzo Tamellini (ORCID: https://orcid.org/0000-0002-8008-0359)
- John Jakeman (ORCID: https://orcid.org/0000-0002-3517-337X)
- Kurt Frey
- Ki-Tae Kim (ORCID: https://orcid.org/0000-0002-5772-2317)
Institutions
- Technical University of Denmark (DK)
Publication Details
- Journal
- Journal of Computational Physics
- Published
- 2024-10-31
- DOI
- https://doi.org/10.1016/j.jcp.2024.113542
- Citations
- 4
- Primary Topic
- Probabilistic and Robust Engineering Design
- Type
- article
- Field-Weighted Citation Impact
- 1.85
Funders
- National Science Foundation
- U.S. Department of Energy
- Villum Fonden
- Istituto Nazionale di Alta Matematica "Francesco Severi"
- European Commission
- Durham University
- Deutsche Forschungsgemeinschaft
- National Nuclear Security Administration
- Gruppo Nazionale per il Calcolo Scientifico
- Engineering and Physical Sciences Research Council
- Advanced Scientific Computing Research
- Sandia National Laboratories