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BEGIN:VEVENT
DTSTAMP:20230831T095745Z
LOCATION:Davos
DTSTART;TZID=Europe/Stockholm:20230626T112000
DTEND;TZID=Europe/Stockholm:20230626T115000
UID:submissions.pasc-conference.org_PASC23_sess104_pos124@linklings.com
SUMMARY:P27 - GPU-Accelerated Modelling of Greenhouse Gases and Air Pollut
 ants in ICON with OpenACC
DESCRIPTION:Poster\n\nArash Hamzehloo and Dominik Brunner (Empa)\n\nReleas
 ing excess greenhouse gases into the atmosphere is the major cause of its 
 natural composition alternation and climate change. Computational modellin
 g of the atmospheric chemistry and transport processes has played a vital 
 role in enhancing our understanding of such complex phenomena and helped d
 evelop major policy guidelines. Advanced high performance computing system
 s with heterogeneous architectures, that utilise "accelerators" such as Gr
 aphical Processing Units (GPUs), have provided the opportunity to develop 
 scale-resolving high-resolution numerical weather prediction frameworks wi
 th complex atmospheric chemistry, physics and transport models. Compiler d
 irectives of OpenACC provide a relatively fast and high-level coding appro
 ach for such heterogeneous computing. In the present work, OpenACC is used
  to accelerate the "Online Emission Module (OEM)" of the FORTRAN-based atm
 ospheric chemistry and transport model ICON-ART. The module reads in a sma
 ll number of emission fields and handles essential processing steps during
  the simulation. The GPU-accelerated OEM code is tested based on cases of 
 methane distribution over Europe. The newly developed code exhibits a noti
 ceable speed-up, comparable with that of the baseline ICON GPU code. The G
 PU-accelerated OEM will be used to perform ICON-ART simulations coupled wi
 th the Carbon Tracker Data Assimilation Shell (CTDAS) at a higher spatial 
 resolution than is currently possible.\n\nSession Chair: Elaine M. Raybour
 n (Sandia National Laboratories)
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