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BEGIN:VEVENT
UID:pretalx-scipy-2026-SPXK7T@pretalx.com
DTSTART;TZID=CST:20260713T080000
DTEND;TZID=CST:20260713T120000
DESCRIPTION:GPU-powered math libraries are the core of accelerated scientif
 ic computing.  The nvmath-python package aims to provide intuitive pythoni
 c APIs giving users full access to all features offered by NVIDIA's librar
 ies in a variety of execution spaces.  It is your one-stop shop for Python
 ic math libraries on the GPU.\n\nInstallation Instructions: We will provid
 e Nvidia Brev cloud instances.  Attendees will only need their laptops and
  an Internet connection.
DTSTAMP:20260715T021115Z
LOCATION:Accelerated Computing
SUMMARY:Accelerated Python Math Libraries (Room HSEC 2-110) - Katrina Riehl
URL:https://pretalx.com/scipy-2026/talk/SPXK7T/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-scipy-2026-9FQMMN@pretalx.com
DTSTART;TZID=CST:20260713T133000
DTEND;TZID=CST:20260713T173000
DESCRIPTION:Scientific researchers need reproducible software environments 
 for complex applications that can run across heterogeneous computing platf
 orms. Modern open source tools\, like [Pixi](https://pixi.sh/)\, provide a
 utomatic reproducibility solutions for all dependencies while providing a 
 high level interface well suited for researchers.\n\nThis tutorial will pr
 ovide a practical introduction to using Pixi to easily create scientific a
 nd AI/ML environments that benefit from hardware acceleration\, across mul
 tiple machines and platforms. The focus will be on CUDA applications\, suc
 h as machine learning frameworks and use of CUDA Tile\, as well as using p
 ixi-build to construct bespoke CUDA enabled conda packages.\n\nInstallatio
 n Instructions: https://matthewfeickert-talks.github.io/reproducible-cuda-
 workflows-with-pixi-scipy-2026/setup/
DTSTAMP:20260715T021115Z
LOCATION:Accelerated Computing
SUMMARY:Reproducible CUDA Accelerated Workflows for Scientists with Pixi (R
 oom HSEC 2-138) - Matthew Feickert\, Ruben Arts\, Katrina Riehl
URL:https://pretalx.com/scipy-2026/talk/9FQMMN/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-scipy-2026-ZNPYX9@pretalx.com
DTSTART;TZID=CST:20260716T164000
DTEND;TZID=CST:20260716T173500
DESCRIPTION:This Birds of a Feather session will bring together developers\
 , users\, researchers\, and educators interested in GPU-accelerated Python
 .  The discussion will explore the current state of the ecosystem\, new li
 brary developments\, and strategies for making GPU acceleration more acces
 sible to a broader scientific audience.  Topics may include performance op
 timization\, debugging and profiling\, education and training\, and opport
 unities for collaboration across projects and communities.
DTSTAMP:20260715T021115Z
LOCATION:Johnson Great Room
SUMMARY:GPU-Accelerated Python - Katrina Riehl
URL:https://pretalx.com/scipy-2026/talk/ZNPYX9/
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