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UID:pretalx-scipy2025-KA7ZYR@cfp.scipy.org
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DESCRIPTION:As general purpose GPU programming has risen in popularity\, ma
 ny Python programmers have expressed a need to use this technology in thei
 r libraries and applications.  They soon realize that the GPU landscape is
  vast and sometimes difficult to traverse for Python users.  \n\nIn this t
 alk\, I will demystify the CUDA-enabled Accelerated Python landscape\, foc
 using on the advantages and disadvantages of popular libraries\, the commo
 n performance issues encountered\, and the best practices to getting the m
 ost out of your GPU.  Topics include CuPy\, numba\, nvmath-python\, cuDF\,
  and cuML.\n\nThis talk is beginner-friendly\, but even the most seasoned 
 programmer will gain insight into the Python GPU computing landscape.
DTSTAMP:20260711T171525Z
LOCATION:Room 316
SUMMARY:The Accelerated Python Developer's Toolbox - Katrina Riehl
URL:https://cfp.scipy.org/scipy2025/talk/KA7ZYR/
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