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7 changes: 7 additions & 0 deletions docs/sources/ext_links.txt
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..
**********************************************************
THESE ARE EXTERNAL PROJECT LINKS USED IN THE DOCUMENTATION
**********************************************************
.. _NumPy*: https://numpy.org/
.. _Numba*: https://numba.pydata.org/
.. _Python Array API Standard: https://data-apis.org/array-api/
5 changes: 5 additions & 0 deletions docs/sources/heterogeneous_computing.rst
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.. _heterogeneous_computing:
.. include:: ./ext_links.txt

Heterogeneous computing
=======================
66 changes: 32 additions & 34 deletions docs/sources/index.rst
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.. documentation master file, created by
sphinx-quickstart.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.

Welcome to DPPY documentation!
======================================

...

About
=====

...

License
=======

...

Indices and tables
==================

.. only:: builder_html

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`

.. only:: not builder_html

* :ref:`modindex`

.. |reg| unicode:: U+000AE .. REGISTERED SIGN
.. _index:
.. include:: ./ext_links.txt

.. image:: ./_images/dpep-large.png
:width: 400px
:align: center
:alt: Data Parallel Extensions for Python

Data Parallel Extensions for Python
===================================

Data Parallel Extensions for Python* extend numerical Python capabilities beyond CPU and allow even higher performance
gains on data parallel devices such as GPUs. It consists of three foundational packages:

* **dpnp** - Data Parallel Extensions for `Numpy*`_ - a library that implements a subset of
Numpy that can be executed on any data parallel device. The subset is a drop-in replacement
of core Numpy functions and numerical data types.
* **numba_dpex** - Data Parallel Extensions for `Numba*`_ - extension for Numba compiler
that enables programming data parallel devices the same way you program CPU with Numba.
* **dpctl - Data Parallel Control library** that provides utilities for device selection,
allocation of data on devices, tensor data structure along with `Python Array API Standard`_ implementation, and support for creation of user-defined data-parallel extensions.

Table of Contents
*****************
.. toctree::
:maxdepth: 2

prerequisites_and_installation
parallelism
heterogeneous_computing
programming_dpep
useful_links
5 changes: 5 additions & 0 deletions docs/sources/parallelism.rst
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.. _parallelism:
.. include:: ./ext_links.txt

Parallelism in modern data parallel architectures
=================================================
5 changes: 5 additions & 0 deletions docs/sources/prerequisites_and_installation.rst
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.. _prerequisites_and_installation:
.. include:: ./ext_links.txt

Prerequisites and installation
==============================
5 changes: 5 additions & 0 deletions docs/sources/programming_dpep.rst
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.. _programming_dpep:
.. include:: ./ext_links.txt

Programming with Data Parallel Extensions for Python
====================================================
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/* Intel logo png */
/*
div.topbar a.brand {
width: 50px;
float: left;
display: block;
height: 60px;
padding: 8px 12px 0px 45px;
margin-left: -10px;
background: transparent url("intel_logo.png") no-repeat 10px 4px;
background-size: 86px 60px;
}
*/

/* Scalable Dataframe Compiler png */
div.topbar a.brand_sdc {
width: 200px;
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.. _useful_links:
.. include:: ./ext_links.txt

Useful links
============