Toward exascale climate modelling: a python DSL approach to ICON's (icosahedral non-hydrostatic) dynamical core (icon-exclaim v0.2.0)

  • Anurag Dipankar
  • , Mauro Bianco
  • , Mona Bukenberger
  • , Till Ehrengruber
  • , Nicoletta Farabullini
  • , Oliver Fuhrer
  • , Abishek Gopal
  • , Daniel Hupp
  • , Andreas Jocksch
  • , Samuel Kellerhals
  • , Clarissa A. Kroll
  • , Xavier Lapillonne
  • , Matthieu Leclair
  • , Magdalena Luz
  • , Christoph Muller
  • , Chia Rui Ong
  • , Carlos Osuna
  • , Praveen Pothapakula
  • , Andreas Prein
  • , Matthias Rothlin
  • William Sawyer, Christoph Schar, Sebastian Schemm, Giacomo Serafini, Hannes Vogt, Ben Weber, Robert C. Jnglin Wills, Nicolas Gruber, Thomas C. Schulthess

Research output: Contribution to journalArticlepeer-review

Abstract

A refactored atmospheric dynamical core of the ICON model implemented in GT4Py, a Python-based domain-specific language designed for performance portability across heterogeneous CPU-GPU architectures, is presented. Integrated within the existing Fortran infrastructure, the new GT4Py dynamical core is shown to exceed ICON OpenACC performance. A multi-tiered testing strategy has been implemented to ensure numerical correctness and scientific reliability of the model code. Validation has been performed through global aquaplanet and prescribed sea-surface temperature simulations to demonstrate model's capability to simulate mesoscale and its interaction with the larger-scale at km-scale grid spacing. This work establishes a foundation for architecture-agnostic ICON global climate and weather model, and highlights poor strong scaling as a potential bottleneck in scaling toward exascale performance.
Original languageEnglish
Pages (from-to)713-729
Number of pages17
JournalGeoscientific Model Development
Volume19
Issue number2
DOIs
StatePublished - Jan 22 2026

Keywords

  • Earth system
  • Programming-model
  • Performance
  • Kilometer

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