Add build documentation for custom SYCL targets (#2026)

* Add build documentation for custom SYCL targets

* Add RPATH for build with onemkl

* Update doc/quick_start_guide.rst

Co-authored-by: vtavana <[email protected]>

---------

Co-authored-by: vtavana <[email protected]>

Author: npolina4

CMakeLists.txt

@@ -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)

doc/quick_start_guide.rst

@@ -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
 =======