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UID:pretalx-juliacon-2026-NJBNMC@pretalx.com
DTSTART;TZID=CET:20260812T163000
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DESCRIPTION:In this talk\, we present the current state of our static DAG o
 ptimization and scheduling package [ComputableDAGs.jl](https://github.com/
 ComputableDAGs/ComputableDAGs.jl). The package allows to represent computa
 tions as static computational graphs. These graphs can be procedurally gen
 erated\, automatically analyzed and optimized\, and finally scheduled\, an
 d executed with no runtime overhead. The optimization can exploit domain s
 pecific knowledge about the computational problem\, provided through meta 
 information on the graph\, without requiring an actual domain-specific lan
 guage. Depending on available hardware\, parts of the graph are automatica
 lly scheduled to accelerator devices if possible.\nWe present the current 
 capabilities and design of the package\, using a high-energy physics appli
 cation as a case study. Furthermore\, we report about ongoing challenges\,
  and invite discussions about usability and improvements.
DTSTAMP:20260502T104016Z
LOCATION:Room 2
SUMMARY:ComputableDAGs.jl - Anton Reinhard
URL:https://pretalx.com/juliacon-2026/talk/NJBNMC/
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