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.github/workflows/main.yml

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name: CI
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on: [push, pull_request]
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on: push
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jobs:
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build:
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AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID}}
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AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY}}
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run: |
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python3 scripts/oneapi.py spec-venv
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. spec-venv/bin/activate
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python scripts/oneapi.py --branch $GITHUB_REF ci
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- name: Archive site
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uses: actions/upload-artifact@v1
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with:
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name: oneapi-spec-artifacts
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path: site.zip
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- name: Archive spellcheck
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uses: actions/upload-artifact@v1
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with:
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name: spell check
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path: build/spelling/output.txt
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python3 scripts/oneapi.py --branch $GITHUB_REF ci

source/conf/common_conf.py

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]
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env = {
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'oneapi_version': '0.85',
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'l0_version': '0.95',
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'oneapi_version': '0.9',
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}
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prolog_template = string.Template("""
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.. |dnn_full_name| replace:: oneAPI Deep Neural Network Library
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.. |dnn_version| replace:: $oneapi_version
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.. |l0_full_name| replace:: oneAPI Level Zero
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.. |l0_version| replace:: $l0_version
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.. |tbb_full_name| replace:: oneAPI Threading Building Blocks
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.. |tbb_version| replace:: $oneapi_version
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.. |vpl_full_name| replace:: oneAPI Video Processing Library

source/contributors.rst

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.. Alphbetical list of authors, | forces linebreak
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| Anastasiya Ageeva, Intel
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| Maksim Banin, Intel
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| Konstantin Boyarinov, Intel
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| Robert Cohn, Intel
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| Max Domeika, Intel
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| Roman Dubtsov, Intel
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| Andrey Fedorov, Intel
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| Evarist Fomenko, Intel
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| Ruslan Israfilov, Intel
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| Alexei Katranov, Intel
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| Todd Rosenquist, Intel
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| Sally Sams, Intel
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| Sanjiv Shah, Intel
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| Mikhail Shiryaev, Intel
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| Timmie Smith, Intel
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| Mikhail Smorkalov, Intel
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| Peng Tu, Intel
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| Zack Waters, Intel

source/elements/dpcpp/source/index.rst

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source/elements/oneCCL/source/definitions.rst

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.. toctree::
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spec/main_objects.rst
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spec/collective_communication.rst
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spec/operations.rst
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spec/error_handling.rst
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..
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Copyright 2020 Intel Corporation
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==============
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=============
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Introduction
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==============
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=============
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The |ccl_full_name| (oneCCL) provides primitives for the
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communication patterns that occur in deep learning applications.
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oneCCL supports both scale-up for platforms with multiple
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oneAPI devices and scale-out for clusters with multiple compute nodes.
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oneCCL supports the following communication patterns used in
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deep learning (DL) algorithms:
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oneCCL supports the following communication patterns used in deep learning (DL) algorithms:
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- Allreduce
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- Allgatherv
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- Broadcast
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- Reduce
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- Alltoall
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- allgatherv
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- allreduce
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- alltoall
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- alltoallv
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- broadcast
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- reduce
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- reduce_scatter
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oneCCL exposes controls over additional optimizations and
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capabilities such as:
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oneCCL exposes controls over additional optimizations and capabilities such as:
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* User-defined pre-/post-processing of incoming buffers and reduction
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operation
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* Prioritization for communication operations
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* Persistent communication operations (enables decoupling one-time
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initialization and repetitive execution)
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* Fusion of multiple communication operations into the single one
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* Persistent communication operations (enables decoupling one-time initialization and repetitive execution)
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* Unordered communication operations
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* :code:`Allreduce` on sparse data
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Intel has published an `open source implementation`_ with the Apache
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license. The `open source implementation`_ includes a comprehensive
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test suite. Consult the `README`_ for directions.
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.. _`open source implementation`: https://github.com/oneapi-src/oneCCL
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.. _`README`: https://github.com/oneapi-src/oneCCL/blob/master/README.md
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source/elements/oneCCL/source/programming_model.rst

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.. toctree::
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spec/generic_workflow.rst
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spec/gpu_support.rst
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spec/cpu_support.rst
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spec/host_communication.rst
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spec/device_communication.rst

source/elements/oneCCL/source/spec/ccl_datatypes.rst

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source/elements/oneCCL/source/spec/collective_call_attributes.rst

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source/elements/oneCCL/source/spec/collective_communication.rst

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