at Google ScholarTitle data
Faghih-Naini, Sara ; Aizinger, Vadym ; Kuckuk, Sebastian ; Angersbach, Richard ; Zint, Daniel ; Kemmler, Samuel ; Köstler, Harald ; Grosso, Roberto:
HPC code generation framework for the discontinuous Galerkin method as a technology demonstrator for digital twins.
2023
Event: Platform for Advanced Scientific Computing (PASC) Conference 2023
, 26.-28. June 2023
, Davos, Switzerland.
(Conference item: Conference
,
Speech
)
Project information
| Project title: |
Project's official title Project's id Performance optimized software strategies for unstructured-mesh applications in ocean modeling No information |
|---|---|
| Project financing: |
Deutsche Forschungsgemeinschaft |
Abstract in another language
Nowadays, automatic code generation and domain-specific languages are among the most promising methodologies for the future development of numerical weather prediction models and digital twins. As a technology demonstrator for new weather and climate models, we present the automatic code generation framework ExaStencils with its Python frontend GHODDESS, which is specialized towards discontinuous Galerkin discretizations for a shallow water model. Our implementation serves as a test platform for a range of new numerical, algorithmic, and computational technologies with the potential to be incorporated into digital twins after successful evaluation. First, we re-formulate the conservative shallow water equations in a way that avoids fraction-type nonlinearities and is suited for quadrature-free integration. Furthermore, we show an algorithm re-design that achieves improved hardware usage on a heterogeneous CPU-GPU system and significantly speeds up the computations. Lastly, we present masked block-structured grids for realistic ocean domains, which on the one hand, are capable of accurately meshing fine-scale geometric features and, on the other, offer performance benefits associated with structured grid models.