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UID:submissions.pasc-conference.org_PASC24_sess132@linklings.com
SUMMARY:MS6E - Julia for HPC: Tools and Applications - Part II
DESCRIPTION:Minisymposium\n\nPerformance portability and scalability on la
 rge-scale heterogeneous hardware represent crucial aspects challenging cur
 rent scientific software development. Beyond software engineering consider
 ations, workflows making further use of large datasets to constrain physic
 al models are also emerging and are indispensable to develop, e.g., digita
 l twins. GPU computing and differentiable programming constitute leading-e
 dge tools that provide a promising way to combine physics-based simulation
 s with novel machine learning and AI based methods to address interdiscipl
 inary problems in science. The Julia language leverages both tools, as it 
 includes first-class support for various accelerator types and an advanced
  compiler interface that supports native automatic differentiation capabil
 ities. Julia makes it possible to differentiate efficiently through both C
 PU and GPU code without significant impact on performance. The goal of thi
 s minisymposium is to bring together scientists who work on or show intere
 st in large-scale Julia HPC development, with a particular focus on the ne
 cessary tool stack for automatic differentiation and machine learning in t
 he Julia GPU ecosystem, and on applications built on top of it. The select
 ion of speakers, with expertise spanning from computer to domain science, 
 offers a unique opportunity to learn about the latest development of Julia
  for HPC to drive discoveries in natural sciences.\n\nEnhancing GPU-Accele
 rated Scientific Computing in Julia with Ginkgo.jl\n\nSolving sparse linea
 r systems on GPU-accelerated systems efficiently is a highly specialized a
 nd demanding task. The implementation of efficient solvers incorporates no
 t only deep insights into the problem but also an extensive understanding 
 of the underlying hardware and the respective platform-spe...\n\n\nYou Wu 
 (ETH Zurich) and Tobias Ribizel and Hartwig Anzt (Technical University of 
 Munich)\n---------------------\nGPU4GEO: Frontier GPU Multiphysics Solvers
  Using Julia\n\nThe GPU4GEO project aims at developing new High-Performanc
 e Computing (HPC) tools for modelling geodynamics and ice sheet dynamics w
 ritten in the Julia language. This initiative is a response to the practic
 al demands of HPC, particularly the need for optimal performance in superc
 omputing environment...\n\n\nAlbert de Montserrat and Ivan Utkin (ETH Zuri
 ch), Ludovic Räss (University of Lausanne), and Boris Kaus (Johannes Guten
 berg University Mainz)\n---------------------\nAdvanced HPC Workflows for 
 Urgent and Interactive Computing Using Julia\n\nModern data-driven discove
 ry algorithms and workflows require the tight interpretation of Simulation
 , Data Analysis, and AI. This means that all too often modern workflows fa
 il to mesh well with HPC environments which are optimized for isolated app
 lications over integrated workflows; and high utiliz...\n\n\nJohannes Blas
 chke (Lawrence Berkeley National Laboratory, NERSC)\n---------------------
 \nAdaptively Coupled Multiphysics Simulations with Trixi.jl\n\nWe extended
  the capabilities of the numerical simulation framework Trixi.jl to be abl
 e to simulate adaptively coupled multiphysics systems. Coupling is perform
 ed through the boundary values of the systems where the coupling functions
  can be freely defined, depending on the physical nature of the int...\n\n
 \nSimon Candelaresi (University of Stuttgart, High-Performance Computing C
 enter Stuttgart)\n\nDomain: Climate, Weather, and Earth Sciences, Physics,
  Computational Methods and Applied Mathematics\n\nSession Chairs: Ludovic 
 Raess (University of Lausanne, ETH Zurich); Samuel Omlin (ETH Zurich / CSC
 S); and Michael Schlottke-Lakemper (University of Augsburg)
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