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UID:submissions.pasc-conference.org_PASC24_sess115@linklings.com
SUMMARY:MS6A - Architectures for Hybrid Next-Generation Weather and Climat
 e Models
DESCRIPTION:Minisymposium\n\nClimate and weather models, traditionally bui
 lt using low-level languages like Fortran for performance, face sustainabi
 lity challenges due to evolving hardware architectures and advances in mac
 hine learning (ML). ML models are rapidly approaching the effectiveness of
  physics-based models, suggesting a future shift towards hybrid systems th
 at blend classic numerical methods with ML. This evolution necessitates ex
 ploring new tools and methodologies to address performance portability iss
 ues and the integration of physics-based models with high-performance GPU 
 and ML frameworks in Python. Significant progress has been made with domai
 n specific languages or general-purpose software libraries, but integratin
 g these with traditional model components remains a challenge. The next-ge
 neration weather and climate models must accommodate a range of tools, inc
 luding numerical methods, performance-portable frameworks, auto differenti
 ation toolkits, and ML libraries. However, the architectural complexities 
 of integrating these diverse tools are often overlooked in scientific soft
 ware development. The minisymposium will focus on architectural design for
  scalable weather and climate models, addressing key topics like automatic
  differentiation, optimization, integration of various model components, a
 nd efficient data handling for ML-enabled simulations.\n\nDesign and Inter
 faces for CliMA’s Next-Generation Performance-Portable Earth System Model\
 n\nThe Climate Modeling Alliance (CliMA) is developing a new Earth System 
 Model (ESM) entirely written in Julia. The CliMA model achieves performanc
 e portability by targeting both CPU and GPU architectures with a common co
 debase. In this talk, we will illustrate some of the different package arc
 hitectu...\n\n\nValeria Barra (San Diego State University); Simon Byrne (N
 VIDIA Inc.); and Akshay Sridhar, Shriharsha Kandala, Lenka Novak, Julia Sl
 oan, Dennis Yatunin, Charles Kawczynski, Gabriele Bozzola, and Tapio Schne
 ider (California Institute of Technology)\n---------------------\nCan we B
 uild Composable Atmospheric Models Without Sacrificing Performance?\n\nAtm
 ospheric models consist of a dynamical core – integrating the equations of
  motion on a computational mesh – and physical parameterizations – taking 
 into account the bulk effect of subgrid-scale phenomena (e.g. radiative he
 at transfer, microphysics, turbulence). For ease of softw...\n\n\nStefano 
 Ubbiali (ETH Zurich), Christian Kühnlein (ECMWF), Christoph Schär (ETH Zur
 ich), Linda Schlemmer (DWD), Thomas C. Schulthess (ETH Zurich / CSCS), and
  Heini Wernli (ETH Zurich)\n---------------------\nNVIDIA and Earth-2's Co
 ntributions to Tools, Libraries, Data and Workflow Infrastructure in the E
 ra of ML-Driven Weather and Climate Modeling\n\nIn this talk I will discus
 s contributions from NVIDIA and the Earth-2 Initiative towards scalable, p
 erformance-portable, user-friendly tools, libraries, data and workflow inf
 rastructure in the era of ML-driven weather and climate modeling. I'll del
 ve into what approaches might move the needle on dig...\n\n\nKarthik Kashi
 nath (NVIDIA Inc.)\n---------------------\nKeeping Pace: Using DSLs to Cre
 ate a Modeling Platform for Next Generation Models\n\nAs hardware architec
 tures and algorithmic approaches diversify, flexibility becomes a greater 
 and greater virtue for weather and climate model developers. The approach 
 of porting models to a domain-specific language can provide this flexibili
 ty; a Python frontend allows natural integration of ML com...\n\n\nOliver 
 Elbert (Geophysical Fluid Dynamics Laboratory); Florian Deconinck (NASA); 
 and Frank Malatino, Rusty Benson, and Lucas Harris (Geophysical Fluid Dyna
 mics Laboratory)\n\nDomain: Climate, Weather, and Earth Sciences, Engineer
 ing\n\nSession Chairs: Mauro Bianco (ETH Zurich / CSCS, ETH Zurich); Enriq
 ue González Paredes (ETH Zurich / CSCS); and Hannes Vogt (ETH Zurich / CSC
 S)
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