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UID:pretalx-juliacon-2026-VC7Q39@pretalx.com
DTSTART;TZID=CET:20260813T143000
DTEND;TZID=CET:20260813T144500
DESCRIPTION:Multi-GPU execution is the future - as data sizes grow\, and as
  more work is pushed to the GPU\, a single GPU no longer suffices. Unfortu
 nately\, programming an algorithm for multi-GPU is more complicated than s
 ingle-GPU - you now have to deal with the complexity of multi-device data 
 movement and multi-stream synchronization\, which puts more burden on the 
 algorithm author and takes away from just writing the algorithm in the sim
 plest\, most readable manner. Thankfully\, Dagger.jl makes programming mul
 ti-GPU algorithms much easier with its Datadeps framework\, which lets you
  focus on writing the algorithm at a high level while Dagger handles the d
 etails of managing multiple GPUs.\n\nThis talk will explain the problems a
 round multi-GPU programming\, and show how Dagger handles them. We will sh
 ow how the Datadeps framework makes it much easier to write algorithms whi
 ch naturally support multi-GPU execution\, and show the tools that Dagger 
 and Datadeps provide to make algorithm design a breeze.
DTSTAMP:20260502T104509Z
LOCATION:Room 3
SUMMARY:Multi-GPU Algorithms with Dagger.jl - Julian P Samaroo\, Felipe Tom
 é
URL:https://pretalx.com/juliacon-2026/talk/VC7Q39/
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