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SUMMARY:Zarr: Community specification of large\, cloud-optimised\, N-dimen
 sional\, typed array storage - Sanket Verma\, Josh Moore\, John Kirkham
DTSTART;TZID=America/Chicago:20230713T155000
DTEND;TZID=America/Chicago:20230713T162000
DTSTAMP:20261017T024718Z
UID:pretalx-2023-T3NSL8@cfp.scipy.org
DESCRIPTION:A key feature of the Python data ecosystem is the reliance on 
 simple but efficient primitives that follow well-defined interfaces to mak
 e tools work seamlessly together (Cf. http://data-apis.org/). NumPy provid
 es an in-memory representation for tensors. Dask provides parallelisation 
 of tensor access. Xarray provides metadata linking tensor dimensions. Zarr
  provides a missing feature\, namely the scalable\, persistent storage for
  annotated hierarchies of tensors. Defined through a community process\, t
 he Zarr specification enables the storage of large out-of-memory datasets 
 locally and in the cloud. Implementations exist in C++\, C\, Java\, Javasc
 ript\, Julia\, and Python\, enabling.
LOCATION:Zlotnik Ballroom
URL:https://cfp.scipy.org/2023/talk/T3NSL8/
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SUMMARY:New CUDA Toolkit packages for Conda - Rick Ratzel\, John Kirkham\,
  Thomson Comer
DTSTART;TZID=America/Chicago:20230714T104500
DTEND;TZID=America/Chicago:20230714T111500
DTSTAMP:20261017T024718Z
UID:pretalx-2023-DQR9NU@cfp.scipy.org
DESCRIPTION:In this talk\, we will examine the new CUDA package layout for
  Conda (as included in conda-forge). Show how CUDA components have been br
 oken out. Share how this affects development and package building. Walk th
 rough changes in the conda-forge infrastructure made to incorporate these 
 new packages. Examine recipes using the new packages and what was needed t
 o update them. Additionally will provide guidance on how to use these new 
 packages in recipes or in library development.
LOCATION:Amphitheater 204
URL:https://cfp.scipy.org/2023/talk/DQR9NU/
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SUMMARY:Python Array API Standard: Toward Array Interoperability in the Sc
 ientific Python Ecosystem - Ralf Gommers\, Stephannie Jimenez Gacha\, Leo 
 Fang\, Saul Shanabrook\, Travis Oliphant\, Matthew Barber\, Aaron Meurer\,
  Thomas J. Fan\, John Kirkham\, Stephan Hoyer\, Tyler Reddy\, Andreas Muel
 ler\, Athan Reines\, Mario\, Alexandre Passos
DTSTART;TZID=America/Chicago:20230714T112500
DTEND;TZID=America/Chicago:20230714T115500
DTSTAMP:20261017T024718Z
UID:pretalx-2023-T7DTX8@cfp.scipy.org
DESCRIPTION:The array API standard (https://data-apis.org/array-api/) is a
  common specification for Python array libraries\, such as NumPy\, PyTorch
 \, CuPy\, Dask\, and JAX. \n\nThis standard will make it straightforward f
 or array-consuming libraries\, like scikit-learn and SciPy\, to write code
  that uniformly supports all of these libraries. This will allow\, for ins
 tance\, running the same code on the CPU and GPU.\n\nThis talk will cover 
 the scope of the array API standard\, supporting tooling which includes a 
 library-independent test suite and compatibility layer\, what work has bee
 n completed so far\, and the plans going forward.
LOCATION:Amphitheater 204
URL:https://cfp.scipy.org/2023/talk/T7DTX8/
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