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Updated Overview page
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| Original file line number | Diff line number | Diff line change |
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| .. | ||
| ********************************************************** | ||
| THESE ARE EXTERNAL PROJECT LINKS USED IN THE DOCUMENTATION | ||
| ********************************************************** | ||
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| .. _NumPy*: https://numpy.org/ | ||
| .. _Python* Array API Standard: https://data-apis.org/array-api/ | ||
| .. _OpenCl*: https://www.khronos.org/opencl/ | ||
| .. _oneAPI Level Zero: https://spec.oneapi.io/level-zero/latest/index.html | ||
| .. _DPC++: https://www.apress.com/gp/book/9781484255735 | ||
| .. _SYCL*: https://www.khronos.org/sycl/ | ||
| .. _dpctl: https://intelpython.github.io/dpctl/latest/index.html | ||
| .. _Data Parallel Control Library: https://intelpython.github.io/dpctl/latest/index.html | ||
| .. _Intel oneAPI Base Toolkit: https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html | ||
| .. _Intel Distribution for Python*: https://www.intel.com/content/www/us/en/developer/tools/oneapi/distribution-for-python.html | ||
| .. _Intel AI Analytics Toolkit: https://www.intel.com/content/www/us/en/developer/tools/oneapi/ai-analytics-toolkit.html |
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| @@ -1,37 +1,21 @@ | ||
| ========================================================= | ||
| DPNP -- A NumPy-compatible library for SYCL-based devices | ||
| ========================================================= | ||
| .. _index: | ||
| .. include:: ./ext_links.txt | ||
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| .. module:: dpnp | ||
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| `DPNP <https://github.com/IntelPython/dpnp>`_ is a NumPy-like library accelerated with SYCL on Intel devices. | ||
| It provides Python interfaces for many NumPy functions, and includes a subset of methods of :class:`dpnp.ndarray`. | ||
| Under the hood it is based on native C++ and oneMKL based kernels. | ||
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| Being drop-in replacement for Numpy its usage is very similar to Numpy: | ||
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| >>> import dpnp as np | ||
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| The :class:`dpnp.ndarray` class is a compatible alternative of :class:`numpy.ndarray`. | ||
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| >>> x = np.array([1, 2, 3]) | ||
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| ``x`` in the above example is an instance of :class:`dpnp.ndarray` that is created identically to ``NumPy``'s one. | ||
| The key difference of :class:`dpnp.ndarray` from :class:`numpy.ndarray` is | ||
| that the memory is allocated on Intel GPU when setting up ``DPNP_QUEUE_GPU=1`` in the environment. | ||
| Data Parallel Extension for NumPy* | ||
| ================================== | ||
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| Most of the array manipulations are also done in the way similar to NumPy such as: | ||
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| >>> s = np.sum(x) | ||
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| Please see the :ref:`API Reference <dpnp_reference>` for the complete list of supported NumPy APIs | ||
| along with their limitations. | ||
| .. module:: dpnp | ||
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| .. toctree:: | ||
| :maxdepth: 2 | ||
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| install | ||
| overview | ||
| quick_start_guide | ||
| reference/index | ||
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| .. toctree:: | ||
| :maxdepth: 1 | ||
| :caption: Development information | ||
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| dpnp_backend_api | ||
| dpctl |
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| .. _overview: | ||
| .. include:: ./ext_links.txt | ||
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| Overview | ||
| ======== | ||
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| .. module:: dpnp | ||
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| The Data Parallel Extension for NumPy* (dpnp package) - 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. | ||
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| The Data Parallel Extension for NumPy* is being developed as part of | ||
| `Intel AI Analytics Toolkit`_ and is distributed with the | ||
| `Intel Distribution for Python*`_. The dpnp package is also available | ||
| on Anaconda cloud. Please refer the :doc:`getting_started` page to learn more. | ||
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| Being drop-in replacement for `NumPy*`_ means that the usage is very similar: | ||
|
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| >>> import dpnp as np | ||
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| The :class:`dpnp.ndarray` class is a compatible alternative of | ||
| :class:`numpy.ndarray`. | ||
|
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||
| >>> x = np.array([1, 2, 3]) | ||
|
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| ``x`` in the above example is an instance of :class:`dpnp.ndarray` that | ||
| is created identically to ``NumPy*``'s one. The key difference of | ||
| :class:`dpnp.ndarray` from :class:`numpy.ndarray` is that the memory | ||
| is allocated on the default `SYCL*`_ device, which is a ``"gpu"`` on systems | ||
| with integrated or discrete GPU (otherwise it is the ``"host"`` device | ||
| on systems that do not have GPU). | ||
|
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| Most of the array manipulations are also done in the way similar to `NumPy*`_ such as: | ||
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| >>> s = np.sum(x) | ||
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| Please see the :ref:`API Reference <dpnp_reference>` for the complete list of supported `NumPy*`_ APIs | ||
| along with their limitations. | ||
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