BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//pretalx.com//juliacon2024//speaker//ZTATFJ
BEGIN:VTIMEZONE
TZID:Europe/Amsterdam
BEGIN:DAYLIGHT
DTSTART:20230710T000000
TZNAME:CEST
TZOFFSETFROM:+0200
TZOFFSETTO:+0200
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20231029T030000
RDATE:20241027T030000
TZNAME:CET
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20240331T030000
RDATE:20250330T030000
TZNAME:CEST
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
SUMMARY:Hands-on with Julia for HPC on GPUs and CPUs - Carsten Bauer\, Lud
 ovic Räss\, Johannes Blaschke\, Ivan Utkin
DTSTART;TZID=Europe/Amsterdam:20240709T133000
DTEND;TZID=Europe/Amsterdam:20240709T163000
DTSTAMP:20260819T150557Z
UID:pretalx-juliacon2024-NTQZJJ@pretalx.com
DESCRIPTION:Julia offers the flexibility of a high-productivity language w
 hile providing control\, performance\, and compatibility with high-perform
 ance computing (HPC) hardware. This workshop demonstrates how Julia makes 
 modern HPC accessible. It covers resource configuration\, distributed comp
 uting\, code optimization for CPUs and GPUs\, and versatile workflows. Par
 ticipants will have the opportunity to experience it firsthand with a hand
 s-on session on a GPU-powered supercomputer.
LOCATION:TU-Eindhoven -1.350
URL:https://pretalx.com/juliacon2024/talk/NTQZJJ/
END:VEVENT
BEGIN:VEVENT
SUMMARY:FastIce.jl: a massively parallel ice flow model running on GPUs - 
 Ludovic Räss\, Samuel Omlin\, Mauro Werder\, Ivan Utkin
DTSTART;TZID=Europe/Amsterdam:20240710T170000
DTEND;TZID=Europe/Amsterdam:20240710T173000
DTSTAMP:20260819T150557Z
UID:pretalx-juliacon2024-VHFAQ8@pretalx.com
DESCRIPTION:We introduce [FastIce.jl](https://github.com/PTsolvers/FastIce
 .jl)\, a novel ice flow model for massively parallel architectures\, writt
 en in Julia. Leveraging GPUs (Nvidia\, AMD) and supporting distributed com
 puting through MPI.jl\, FastIce.jl includes a thermo-mechanically coupled 
 Full-Stokes ice flow model. We present the performance testing of FastIce.
 jl in single-node and distributed scaling benchmarks on LUMI\, the largest
  European supercomputer.
LOCATION:For Loop (3.2)
URL:https://pretalx.com/juliacon2024/talk/VHFAQ8/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Developing Supercomputing Geoscience Applications using Julia - Lu
 dovic Räss\, Boris Kaus
DTSTART;TZID=Europe/Amsterdam:20240712T140000
DTEND;TZID=Europe/Amsterdam:20240712T142200
DTSTAMP:20260819T150557Z
UID:pretalx-juliacon2024-GTGCH7@pretalx.com
DESCRIPTION:The rapidly increasing amount of data in the geosciences requi
 res new tools and workflows to processing them\, along with software to mo
 delling the physics of the governing processes. Julia offers a great basis
  for this by combining the benefits of a high-level language\, such as eas
 e of use and interactivity\, with the features of a low-level language\, i
 ncluding speed\, efficiency\, scalability\, and native GPU support.
LOCATION:Function (4.1)
URL:https://pretalx.com/juliacon2024/talk/GTGCH7/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Subglacial water flow simulations on GPUs - Ludovic Räss\, Mauro 
 Werder\, Ivan Utkin\, Annegret Pohle
DTSTART;TZID=Europe/Amsterdam:20240712T151000
DTEND;TZID=Europe/Amsterdam:20240712T152000
DTSTAMP:20260819T150557Z
UID:pretalx-juliacon2024-VKCYEK@pretalx.com
DESCRIPTION:Modeling subglacial water flow and its link to ice dynamics is
  necessary for accurate predictions of ice sheet response to a warming cli
 mate.  Here we present a re-implementation of the widely used GlaDS model 
 to run on GPUs.  We show-case the matrix free implementation which leverag
 es the full capabilities of the GPU\, present model runs of test cases\, s
 how the model's scalability and provide an outlook towards inversion schem
 es and high-resolution continental-scale applications.
LOCATION:While Loop (4.2)
URL:https://pretalx.com/juliacon2024/talk/VKCYEK/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Sustainable Development of Stencil-based HPC Applications - Ludovi
 c Räss\, Samuel Omlin\, Ivan Utkin
DTSTART;TZID=Europe/Amsterdam:20240712T155000
DTEND;TZID=Europe/Amsterdam:20240712T160000
DTSTAMP:20260819T150557Z
UID:pretalx-juliacon2024-QLVPSN@pretalx.com
DESCRIPTION:We present a successful approach for a sustainable development
  of stencil-based HPC applications in Julia. The approach includes automat
 ic performance optimization for hardware-agnostic high-level kernels\, dat
 a layout abstractions enabling memory layouts optimized per backend\, and 
 GPU-aware inter-process communication that is automatically hideable behin
 d computation. We demonstrate on multiple examples near optimal performanc
 e and scaling on thousands of GPUs.
LOCATION:Else (1.3)
URL:https://pretalx.com/juliacon2024/talk/QLVPSN/
END:VEVENT
END:VCALENDAR