index.md

CuPy-Xarray: Xarray on GPUs!

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 conda or pip:

From Conda Forge:

conda install -c conda-forge cupy-xarray

From PyPI:

pip install cupy-xarray

The latest version from Github:

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

Extras

To enable the cog3pio backend for reading TIFFs (only available for linux-x86_64 and linux-aarch64), do:

From Conda Forge:

conda install -c conda-forge cupy-xarray cog3pio

From PyPI:

pip install cupy-xarray[tiff]

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

   examples/01_cupy-basics
   examples/02_introduction
   examples/03_basic-computations
   examples/04_high-level-api
   examples/05_apply-ufunc
   examples/06_real-example


**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