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Add build documentation for custom SYCL targets #2026

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Merged
merged 3 commits into from
Sep 10, 2024
Merged

Add build documentation for custom SYCL targets #2026

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b8db9ef
Add build documentation for custom SYCL targets
npolina4 Sep 10, 2024
c86abe8
Add RPATH for build with onemkl
npolina4 Sep 10, 2024
3c6dab5
Update doc/quick_start_guide.rst
npolina4 Sep 10, 2024
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1 change: 1 addition & 0 deletions CMakeLists.txt
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Expand Up @@ -121,6 +121,7 @@ if(_use_onemkl_interfaces)
GIT_TAG f2d2dcb4213a435bb60fbb88320c5f24892423ce
)
FetchContent_MakeAvailable(onemkl_interfaces_library)
set(CMAKE_INSTALL_RPATH "${CMAKE_BINARY_DIR}/lib")
endif()

if(WIN32)
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21 changes: 21 additions & 0 deletions doc/quick_start_guide.rst
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Expand Up @@ -116,6 +116,27 @@ Alternatively, to develop on Linux OS, you can use the driver script:

python scripts/build_locally.py

Building for custom SYCL targets
--------------------------------
Project ``dpnp`` is written using generic SYCL and supports building for multiple SYCL targets,
subject to limitations of `CodePlay <https://codeplay.com/>`_ plugins implementing SYCL
programming model for classes of devices.

Building ``dpnp`` for these targets requires that these CodePlay plugins be installed into DPC++
installation layout of compatible version. The following plugins from CodePlay are supported:

- `oneAPI for NVIDIA(R) GPUs <codeplay_nv_plugin_>`_

.. _codeplay_nv_plugin: https://developer.codeplay.com/products/oneapi/nvidia/

Building ``dpnp`` also requires `building Data Parallel Control Library for custom SYCL targets.
<https://intelpython.github.io/dpctl/latest/beginners_guides/installation.html#building-for-custom-sycl-targets>`_

Build ``dpnp`` as follows:

.. code-block:: bash

python scripts/build_locally.py --target=cuda

Testing
=======
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