deploy: d1b2a2b

Author: github-actions[bot]

pull/1116/.buildinfo

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+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 6d807dd66b561429f1b82b39b187f96e
+tags: 645f666f9bcd5a90fca523b33c5a78b7

pull/1116/.nojekyll

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+.. _index:
+.. include:: ./../ext_links.txt
+
+
+API Reference
+=============
+
+Coming soon

pull/1116/_images/kernel-queue-device.png

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+.. _contributions:
+.. include:: ./ext_links.txt
+
+Contribution Guide
+==================
+
+Classification of Contributions
+-------------------------------
+
+Development Cycle
+-----------------
+
+Issues and Pull Requests
+------------------------
+
+Coding Guidelines
+-----------------
+
+Unit Testing
+-------------
+
+Documentation
+-------------
+
+Tips for Developers
+-------------------

pull/1116/_images/kernel_prog_model.png

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+.. _examples:
+.. include:: ./ext_links.txt
+
+List of examples
+================
+
+.. todo::
+   Provide list of examples for numba-dpex
+
+Benchmarks
+**********
+
+.. todo::
+   Provide instructions for dpbench
+
+Jupyter* Notebooks
+******************
+
+.. todo::
+   Provide instructions for Jupyter Notebook samples

pull/1116/_sources/api_reference/index.rst.txt

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+.. _getting_started:
+.. include:: ./ext_links.txt
+
+.. |copy| unicode:: U+000A9
+
+.. |trade| unicode:: U+2122
+
+Getting Started
+===============
+
+
+Installing pre-built conda packages
+-----------------------------------
+
+``numba-dpex`` along with its dependencies can be installed using ``conda``.
+It is recommended to use conda packages from the ``anaconda.org/intel`` channel
+to get the latest production releases.
+
+.. code-block:: bash
+
+    conda create -n numba-dpex-env                                             \
+        numba-dpex dpnp dpctl dpcpp-llvm-spirv                     \
+        -c intel -c conda-forge
+
+To try out the bleeding edge, the latest packages built from tip of the main
+source trunk can be installed from the ``dppy/label/dev`` conda channel.
+
+.. code-block:: bash
+
+    conda create -n numba-dpex-env                                             \
+        numba-dpex dpnp dpctl dpcpp-llvm-spirv                     \
+        -c dppy/label/dev -c intel -c conda-forge
+
+
+
+Building from source
+--------------------
+
+``numba-dpex`` can be built from source using either ``conda-build`` or
+``setuptools`` (with ``scikit-build`` backend).
+
+Steps to build using ``conda-build``:
+
+1. Ensure ``conda-build`` is installed in the ``base`` conda environment or
+   create a new conda environment with ``conda-build`` installed.
+
+.. code-block:: bash
+
+    conda create -n build-env conda-build
+    conda activate build-env
+
+2. Build using the vendored conda recipe
+
+.. code-block:: bash
+
+    conda build conda-recipe -c intel -c conda-forge
+
+3. Install the conda package
+
+.. code-block:: bash
+
+    conda install -c local numba-dpex
+
+Steps to build using ``setup.py``:
+
+As before, a conda environment with all necessary dependencies is the suggested
+first step.
+
+.. code-block:: bash
+
+    # Create a conda environment that hass needed dependencies installed
+    conda create -n numba-dpex-env                                             \
+        scikit-build cmake dpctl dpnp numba dpcpp-llvm-spirv llvmdev pytest    \
+        -c intel -c conda-forge
+    # Activate the environment
+    conda activate numba-dpex-env
+    # Clone the numba-dpex repository
+    git clone https://github.com/IntelPython/numba-dpex.git
+    cd numba-dpex
+    python setup.py develop
+
+Building inside Docker
+----------------------
+
+A Dockerfile is provided on the GitHub repository to build ``numba-dpex``
+as well as its direct dependencies: ``dpctl`` and ``dpnp``. Users can either use
+one of the pre-built images on the ``numba-dpex`` GitHub page or use the
+bundled Dockerfile to build ``numba-dpex`` from source. Using the Dockerfile
+also ensures that all device drivers and runtime libraries are pre-installed.
+
+Building
+~~~~~~~~
+
+Numba dpex ships with multistage Dockerfile, which means there are
+different `targets <https://docs.docker.com/build/building/multi-stage/#stop-at-a-specific-build-stage>`_
+available for build. The most useful ones:
+
+- ``runtime``
+- ``runtime-gpu``
+- ``numba-dpex-builder-runtime``
+- ``numba-dpex-builder-runtime-gpu``
+
+To build docker image
+
+.. code-block:: bash
+
+    docker build --target runtime -t numba-dpex:runtime ./
+
+
+To run docker image
+
+.. code-block:: bash
+
+    docker run -it --rm numba-dpex:runtime
+
+.. note::
+
+    When trying to build a docker image with Intel GPU support, the Dockerfile
+    will attempt to use the GitHub API to get the latest Intel GPU drivers.
+    Users may run into an issue related to  Github API call limits. The issue
+    can be bypassed by providing valid GitHub credentials using the
+    ``GITHUB_USER`` and ``GITHUB_PASSWORD``
+    `build args <https://docs.docker.com/engine/reference/commandline/build/#build-arg>`_
+    to increase the call limit. A GitHub
+    `access token <https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/creating-a-personal-access-token>`_
+    can also be used instead of the password.
+
+.. note::
+
+    When building the docker image behind a firewall the proxy server settings
+    should be provided using the ``http_proxy`` and ``https_proxy`` build args.
+    These build args must be specified in lowercase.
+
+The bundled Dockerfile supports different python versions that can be specified
+via the ``PYTHON_VERSION`` build arg. By default, the docker image is based on
+the official python image based on slim debian. The requested python version
+must be from the available python docker images.
+
+The ``BASE_IMAGE`` build arg can be used to build the docker image from a
+custom image. Note that as the Dockerfile is based on debian any custom base
+image should be debian-based, like debian or ubuntu.
+
+The list of other build args are as follows. Please refer the Dockerfile to
+see currently all available build args.
+
+- ``PYTHON_VERSION``
+- ``CR_TAG``
+- ``IGC_TAG``
+- ``CM_TAG``
+- ``L0_TAG``
+- ``ONEAPI_VERSION``
+- ``DPCTL_GIT_BRANCH``
+- ``DPCTL_GIT_URL``
+- ``DPNP_GIT_BRANCH``
+- ``DPNP_GIT_URL``
+- ``NUMBA_DPEX_GIT_BRANCH``
+- ``NUMBA_DPEX_GIT_URL``
+- ``CMAKE_VERSION``
+- ``CMAKE_VERSION_BUILD``
+- ``INTEL_NUMPY_VERSION``
+- ``INTEL_NUMBA_VERSION``
+- ``CYTHON_VERSION``
+- ``SCIKIT_BUILD_VERSION``
+- ``http_proxy``
+- ``https_proxy``
+- ``GITHUB_USER``
+- ``GITHUB_PASSWORD``
+- ``BASE_IMAGE``
+
+
+Using the pre-built images
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+There are several pre-built docker images available:
+
+- ``runtime`` package that provides a pre-built environment with ``numba-dpex``
+              already installed. It is ideal to quickly setup and try
+              ``numba-dpex``.
+
+.. code-block:: text
+
+    ghcr.io/intelpython/numba-dpex/runtime:<numba_dpex_version>-py<python_version>[-gpu]
+
+- ``builder`` package that has all required dependencies pre-installed and is
+              ideal for building ``numba-dpex`` from source.
+
+.. code-block:: text
+
+    ghcr.io/intelpython/numba-dpex/builder:<numba_dpex_version>-py<python_version>[-gpu]
+
+- ``stages`` package primarily meant for creating a new docker image that is
+             built on top of one of the pre-built images.
+
+After setting up the docker image, to run ``numba-dpex`` the following snippet
+can be used.
+
+.. code-block:: bash
+
+    docker run --rm -it ghcr.io/intelpython/numba-dpex/runtime:0.20.0-py3.10 bash
+
+It is advisable to verify the SYCL runtime and driver installation within the
+container by either running,
+
+.. code-block:: bash
+
+    sycl-ls
+
+or,
+
+.. code-block:: bash
+
+    python -m dpctl -f
+
+.. note::
+
+    To enable GPU device, the ``device`` argument should be used and one of the
+    ``*-gpu`` images should be used.
+
+    For passing GPU into container on linux use arguments ``--device=/dev/dri``.
+    However if you are using WSL you need to pass
+    ``--device=/dev/dxg -v /usr/lib/wsl:/usr/lib/wsl`` instead.
+
+For example, to run ``numba-dpex`` with GPU support on WSL:
+
+.. code-block:: bash
+
+    docker run --rm -it \
+    --device=/dev/dxg -v /usr/lib/wsl:/usr/lib/wsl \
+    ghcr.io/intelpython/numba-dpex/runtime:0.20.0-py3.10-gpu
+
+
+
+Testing
+-------
+
+``numba-dpex`` uses pytest for unit testing and the following example
+shows a way to run the unit tests.
+
+.. code-block:: bash
+
+    python -m pytest --pyargs numba_dpex.tests
+
+Examples
+--------
+
+A set of examples on how to use ``numba-dpex`` can be found in
+``numba_dpex/examples``.

pull/1116/_sources/contribution_guide.rst.txt

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+.. _glossary:
+.. include:: ./ext_links.txt
+
+Glossary
+========

pull/1116/_sources/examples.rst.txt

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+.. _index:
+.. include:: ./ext_links.txt
+
+.. Feedbacks:
+.. 	Use proper names (as provided by marketing)
+.. 	Do not use "we/I"
+.. 	Use correct acronym, expand acronym at the first instance
+
+
+.. Follow cupy docs.
+
+.. Overview:
+.. 	Main Features
+.. 	Project Goal
+
+.. Getting Started:
+.. 	Yevheni
+.. 	Docker page
+
+.. User Guide:
+.. 	https://intelpython.github.io/oneAPI-for-SciPy/details/programming_model/
+.. 	Kernel Programming API --> Kernel Programming Basics
+.. 	Compiling and Offloading DPNP
+.. 		- Introduce @dpjit
+.. 		- Array constructor in dpjit
+.. 		- ufunc (refer to numba)
+.. 		- prange
+.. 		-
+.. 	Debugging using GDB
+.. 	# Performance Tips
+.. 	# Troubleshooting
+.. 	Useful Links
+.. 	# To-Do
+
+.. API Reference:
+
+
+Data Parallel Extension for Numba*
+==================================
+
+.. module:: numba_dpex
+
+.. toctree::
+   :maxdepth: 2
+
+   overview
+   getting_started
+   user_guide/index
+   api_reference/index
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Development
+
+   contribution_guide
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Misc Notes
+
+   examples
+   glossary
+   license
+   release-notes

pull/1116/_sources/getting_started.rst.txt

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+.. _license:
+.. include:: ./ext_links.txt
+
+License
+=======
+
+Numba-dpex is Licensed under Apache License 2.0 that can be found in `LICENSE
+<https://github.com/IntelPython/numba-dpex/blob/main/LICENSE>`_. All usage and
+contributions to the project are subject to the terms and conditions of this
+license.