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DTSTAMP:20260421T090513Z
LOCATION:Bldg. 6 - Room 104
DTSTART;TZID=Europe/Stockholm:20260701T140000
DTEND;TZID=Europe/Stockholm:20260701T143000
UID:submissions.pasc-conference.org_PASC26_sess163_msa146@linklings.com
SUMMARY:Reducing and Validating Precision in the ICON model
DESCRIPTION:Dylan Kierans (DKRZ)\n\nReducing model precision can significa
 ntly reduce the memory footprint of a model, and increase utilization on f
 uture AI-based hardware. However, identifying and validating single precis
 ion model components without compromising on the model accuracy of scienti
 fic experiments remains a key challenge. We demonstrate the development wo
 rkflow for verifying single-precision in the weather and climate model ICO
 N, with the use of floating point emulation tool Verrou and test cases wit
 h analytic solutions for isolated model components. Since ICON uses the sa
 me dynamical core and tracer advection for both numerical weather predicti
 on and climate modelling, we first focus on validating these components us
 ing recognized test cases from the Dynamical Core Model Intercomparison Pr
 oject (DCMIP). Using Verrou, we identify precision sensitive code regions 
 which cause the test case to fail to for some given tolerance. The code re
 gions are then subject to further investigation, requiring solutions such 
 as algorithm or precision adjustments. Metrics comparing time-to-solution,
  memory consumption and energy consumption in double-precision versus sing
 le-precision are presented. Performance metrics are presented on a range o
 f model resolutions and target architectures.\n\nDomain: Climate, Weather,
  and Earth Sciences\n\nSession Chairs: Balthasar Reuter (ECMWF) and Claudi
 a Frauen (DKRZ)\n\n
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