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DOE OSTI · 3028571

Scalable foundation models for numerical simulations on HPC platforms

Wang, Dali [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000168065108)·Gong, Qian [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000235704142)·Liu, Zirui [University of Minnesota, Minneapolis, MN (United States)]·Wang, Xiao [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000165451943)·Cao, Qinglei [Saint Louis University, St. Louis, MO (United States)] (ORCID:000000026690194X)·Klasky, Scott [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000335595772)
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Abstract

In recent years, foundation models (FMs) have begun to reshape numerical simulations on high-performance computing (HPC) platforms. These large, pre-trained AI models enable rapid predictions across a broad range of physical domains, including Earth system modeling, fluid dynamics, materials science, as well as complex multi-modal simulations in aerospace engineering and fusion research. By training on diverse datasets, FMs learn intricate relationships and underlying physical behavior while also enabling the quantification of uncertainty in their predictions. This capability allows simulations that once required days of numerical calculation to be completed in minutes (FM inference), supporting real-time design optimization, uncertainty-aware decision making, and more comprehensive exploration of complex scenarios.

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Wang, Dali [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000168065108), Gong, Qian [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000235704142), Liu, Zirui [University of Minnesota, Minneapolis, MN (United States)], Wang, Xiao [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000165451943), Cao, Qinglei [Saint Louis University, St. Louis, MO (United States)] (ORCID:000000026690194X), Klasky, Scott [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000335595772). 2026-03-26. Scalable foundation models for numerical simulations on HPC platforms. https://doi.org/10.3389/fhpcp.2026.1778471

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