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33 lines
1.4 KiB
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33 lines
1.4 KiB
ReStructuredText
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<a href="https://github.com/ray-project/ray"><img style="position: absolute; top: 0; right: 0; border: 0;" src="https://camo.githubusercontent.com/365986a132ccd6a44c23a9169022c0b5c890c387/68747470733a2f2f73332e616d617a6f6e6177732e636f6d2f6769746875622f726962626f6e732f666f726b6d655f72696768745f7265645f6161303030302e706e67" alt="Fork me on GitHub" data-canonical-src="https://s3.amazonaws.com/github/ribbons/forkme_right_red_aa0000.png"></a>
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.. image:: https://github.com/ray-project/ray/raw/master/doc/source/images/ray_header_logo.png
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**Ray provides a simple, universal API for building distributed applications.**
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Ray accomplishes this mission by:
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1. Providing simple primitives for building and running distributed applications.
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2. Enabling end users to parallelize single machine code, with little to zero code changes.
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3. Including a large ecosystem of applications, libraries, and tools on top of the core Ray to enable complex applications.
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**Ray Core** provides the simple primitives for application building.
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On top of **Ray Core** are several libraries for solving problems in machine learning:
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- :doc:`../tune/index`
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- :ref:`rllib-index`
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- :ref:`sgd-index`
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- :ref:`rayserve`
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Ray also has a number of other community contributed libraries:
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- :doc:`../dask-on-ray`
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- `Mars on Ray <https://github.com/mars-project/mars/pull/1508>`__
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- :doc:`../pandas_on_ray`
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- :doc:`../joblib`
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- :doc:`../multiprocessing`
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