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CuPy-Xarray: Xarray on GPUs!

GitHub Workflow CI Status pre-commit.ci status Documentation Status license

PyPI Conda-forge

NASA-80NSSC22K0345

Overview

CuPy-Xarray is a Python library that leverages CuPy, a GPU array library, and Xarray, a library for multi-dimensional labeled array computations, to enable fast and efficient data processing on GPUs. By combining the capabilities of CuPy and Xarray, CuPy-Xarray provides a convenient interface for performing accelerated computations and analysis on large multidimensional datasets.

Installation

cupy-xarray will use an existing cupy installation, hence cupy needs to be installed manually! Please follow cupy's install instructions at https://docs.cupy.dev/en/stable/install.html.

CuPy-Xarray can be installed using pip or conda:

From Conda Forge:

conda install cupy-xarray -c conda-forge

From PyPI:

pip install cupy-xarray

The latest version from Github:

pip install git+https://github.com/xarray-contrib/cupy-xarray.git

Acknowledgements

Large parts of this documentations comes from SciPy 2023 Xarray on GPUs tutorial and this NCAR tutorial to GPUs.

Contents


**User Guide**:

.. toctree::
   :maxdepth: 1
   :caption: User Guide

   source/cupy-basics
   source/introduction
   source/basic-computations
   source/high-level-api
   source/apply-ufunc
   source/real-example-1
   source/kvikio


**Tutorials & Presentations**:

.. toctree::
   :maxdepth: 1
   :caption: Tutorials & Presentations

   source/tutorials-and-presentations

**Contributing**:

.. toctree::
   :maxdepth: 1
   :caption: Contributing

   source/contributing


**Reference**:

.. toctree::
   :maxdepth: 1
   :caption: Reference

   api
   changelog