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UID:pretalx-juliacon-2022-YPGNCS@pretalx.com
DTSTART:20220727T130000Z
DTEND:20220727T133000Z
DESCRIPTION:In the Fall Semester 2021 at ETH Zurich\, we designed and taugh
 t a new course: **Solving PDEs in parallel on GPUs with Julia**. We presen
 t technical and teaching experiences we gained: we look at our tech-stack 
 `CUDA.jl`\, `ParallelStencils.jl` and `ImplictGlobalGrid.jl` for GPU-compu
 ting\; and `Franklin.jl`\, `Literate.jl`\, `IJulia.jl`/Jupyter for web\, s
 lides\, and exercises. We look into the crash-course in Julia\, teaching s
 oftware-engineering (git\, CI) and project-based student evaluations.
DTSTAMP:20260316T235921Z
LOCATION:Blue
SUMMARY:Teaching GPU computing\, experiences from our Master-level course -
  Ludovic Räss\, Samuel Omlin\, Mauro Werder
URL:https://pretalx.com/juliacon-2022/talk/YPGNCS/
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