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DTSTAMP:20260624T171340Z
LOCATION:Bldg. 8 - Entrance Hall
DTSTART;TZID=Europe/Stockholm:20260630T173000
DTEND;TZID=Europe/Stockholm:20260630T194500
UID:submissions.pasc-conference.org_PASC26_sess135_pos101@linklings.com
SUMMARY:P28 - Performance-Portable and Highly Scalable Spectral Transforms
  with ecTrans
DESCRIPTION:Sam Hatfield (ECMWF)\n\nThe continued increase in the skill of
  weather forecasts observed over the past decades depends crucially on the
  efficient exploitation of the next generation of high-performance compute
 rs by Earth-system models. The European Centre for Medium-Range Weather Fo
 recast (ECMWF)'s model, the IFS, is one such model. The IFS atmospheric co
 mponent relies on a spectral transform method, a very old technique that i
 s still competitive today. This is one of the most important parts of the 
 entire system, and has been tested even up to 750 m resolution. Developmen
 t of the spectral transform method has accelerated since it was released a
 s an open-source package in 2022, managed by ECMWF. Recently, support for 
 both Nvidia and AMD GPUs has been added, and the spectral transform has pr
 oven to be a natural fit for accelerators. In this poster I will summarise
  the recent developments to ecTrans and present an overview in particular 
 on its performance portability characteristics. I will also present a comp
 arison against a new, simpler spectral transform recently implemented in p
 ure PyTorch, developed in order to train data-driven weather forecasting m
 odels with spectral loss functions.\n\n
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