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UID:pretalx-foss4g-2025-TSVGYJ@talks.staging.osgeo.org
DTSTART;TZID=NZST:20251119T154500
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DESCRIPTION:Zarr is a cloud-native format\, and now it can be GPU-native to
 o! We address one of the main bottlenecks of geospatial machine learning\,
  which is on the data loading stage. Let's see how we can read and decompr
 ess data from Zarr directly into GPU memory!
DTSTAMP:20260505T041138Z
LOCATION:WG403
SUMMARY:GPU-native Zarr: Optimizing data throughput for large-scale geospat
 ial machine learning workflows - Wei Ji Leong
URL:https://talks.staging.osgeo.org/foss4g-2025/talk/TSVGYJ/
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