JuliaCon 2024 is being held in Eindhoven (9-13 july 2024)

The Julia programming language is being used more and more for high-performance computing and data processing (including on Snellius), due to being a combination of a high-level language with optimized native code generation. It also offers interesting interactive workflows that are not very common when working on high-performance code.

The JuliaCon conference is the annual multi-day conference on everything Julia. JuliaCon 2023 featured over 200 presentation sessions and many workshops. This year Julia conference is held in Eindhoven, 9-13 july 2024. This might be a nice opportunity for current users of Julia for HPC, or those interested in Julia, to get a feel for the Julia language and  ecosystem, plus to get in touch with the Julia community. Early bird tickets are now available.



Apart from lots of presentations (schedule not published yet) there are also HPC-focused workshops that might be interesting:

There is also a mini-symposium Julia for High-Performance Computing. The minisymposium will include presentations of the following confirmed speakers and topics (exact titles and schedule will be finalized later):

  • Giacomo Aloisi (ETH Zurich, Switzerland) “SeismicWaves.jl: a Julia package for Full-Waveform Inversion on multi-xPUs”

  • Tim Besard (JuliaHub) “Update on CUDA.jl and oneAPI.jl changes”

  • Sriharsha Kandala (California Institute of Technology, USA) “Juggling GPUs: handling multiple devices for distributed computing”

  • Bernat Font and Gabriel Weymouth (TU Delft) “WaterLily.jl: A fast and flexible CFD solver with heterogeneous execution”

  • Benedict Geihe (University of Cologne, Germany) “libtrixi: serving legacy codes in earth system modeling with fresh Julia CFD”

  • Boris Kaus (JGU Mainz, Germany) & Ludovic Räss (University Lausanne, Switzerland) "Developing Supercomputing Geoscience Applications using Composable Julia Tools"

  • Samuel Omlin (CSCS, Switzerland) "Seamless transition from single-core Python to Julia Multi-GPU"

  • Julian Samaroo (MIT, USA) "Applications of Distributed Task Parallelism"

  • You Wu (ETH Zurich, Switzerland) "Ginkgo.jl: Harnessing GPU Power for Solving Sparse Linear Systems"





Dit artikel heeft 0 reacties