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Review of User Guides section (#1663)
* Review of User Guides section * Update docs/doc_sources/user_guides/environment_variables.rst Co-authored-by: ndgrigorian <[email protected]> * Update docs/doc_sources/user_guides/basic_concepts.rst Co-authored-by: Oleksandr Pavlyk <[email protected]> * Update execution_model.rst * Update docs/doc_sources/user_guides/execution_model.rst Co-authored-by: Oleksandr Pavlyk <[email protected]> --------- Co-authored-by: ndgrigorian <[email protected]> Co-authored-by: Oleksandr Pavlyk <[email protected]>
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docs/doc_sources/user_guides/basic_concepts.rst

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@@ -168,7 +168,7 @@ they do not compare equal, since they correspond to two independent scheduling e
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Event
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-----
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SYCL event is an entity created when a task is submitted to SYCL queue for execution. The event are be used to
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A SYCL event is an entity created when a task is submitted to SYCL queue for execution. The events are used to
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order execution of computational tasks by the DPC++ runtime. They may also contain profiling information associated
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with the submitted task, provided the queue was created with "enable_profiling" property.
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tasks to when performing copying of elements from or to this allocation or when filling
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the allocation with values.
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Classes that represent host-accessible USM allocations, i.e. types USM-shared and USM-host,
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Classes that represent host-accessible USM allocations, i.e., types USM-shared and USM-host,
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expose Python buffer interface.
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.. code-block:: python
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Intel(R) oneAPI Data Parallel C++ compiler ships with two backends:
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#. OpenCL backend
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#. OpenCL* backend
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#. Level-Zero backend
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Additional backends can be added to the compiler by installing CodePlay's plugins:

docs/doc_sources/user_guides/environment_variables.rst

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@@ -18,13 +18,13 @@ description and :ref:`uses <beginners_guide_oneapi_device_selector_usecase>`.
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Variable ``SYCL_CACHE_PERSISTENT``
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----------------------------------
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The binaries implementing :py:mod:`dpctl.tensor` created using DPC++ compiler contain sections
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with standardized intermediate forms (e.g. `SPIR-V <https://www.khronos.org/spir/>`_) that must be
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The binaries implementing :py:mod:`dpctl.tensor` created using the DPC++ compiler contain sections
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with standardized intermediate forms (e.g., `SPIR-V <https://www.khronos.org/spir/>`_) that must be
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further built using SYCL device drivers for execution on the specific target hardware.
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This step is known as just-in-time compiling (JIT-ing).
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By default, the result of JIT-ing persists for the duration of SYCL application, i.e. for the
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duration of the Python session where :py:mod:`dpctl.tensor` is used. Setting environment variable
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By default, the result of JIT-ing persists for the duration of SYCL application, i.e., for the
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duration of the Python session where :py:mod:`dpctl.tensor` is used. Setting the environment variable
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``SYCL_CACHE_PERSISTENT`` to value of ``1`` instructs DPC++ runtime to save the result of JIT-ing to
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disk and reuse it in subsequent Python sessions (assuming the variable remains to be set when sessions
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are started).
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--------------------------
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Setting this debugging variable enables specific levels of tracing for SYCL Programming Interfaces (PI).
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The value of the variable is a bit-mask, with the following supported values
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The value of the variable is a bit-mask, with the following supported values:
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.. list-table::
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:header-rows: 1

docs/doc_sources/user_guides/execution_model.rst

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=======================================
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Using oneAPI libraries, a user calls functions that take ``sycl::queue`` and a collection of
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``sycl::event`` objects among other arguments, e.g.
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``sycl::event`` objects among other arguments. For example:
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.. code-block:: cpp
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:caption: Prototypical call signature of oneMKL function
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ready. The function returns a ``sycl::event`` object representing completion of the set of
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computational tasks submitted by the ``compute`` function.
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Hence, in oneAPI programming model, the execution **queue** is used to specify which device the
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Hence, in the oneAPI programming model, the execution **queue** is used to specify which device the
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function will execute on. To create a queue, one must specify a device to target.
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In :mod:`dpctl`, the ``sycl::queue`` is represented by :class:`dpctl.SyclQueue` Python type,
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) -> dpctl.SyclEvent:
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...
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Even if Python API to an offloading Python function looks different from this, it must
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translate to a similar call under the hood.
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When building Python API for a SYCL offloading function, and you choose to
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map the SYCL API to a different API on the Python side, it must still translate to a
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similar call under the hood.
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The arguments to the function must be suitable for use in the offloading functions.
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Typically these are Python scalars, or objects representing USM allocations, such as
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Python type representing the USM allocation.
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This design choice allows :mod:`dpctl` to have a preferred queue to use when operating on any single
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USM allocation, i.e.
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USM allocation. For example:
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.. code-block:: python
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>>> # rules are not met
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>>> tensor.concat((y1, y2))
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Please refer to :ref:`array migration <dpctl_tensor_array_migration>` section of the introduction to
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Please refer to the :ref:`array migration <dpctl_tensor_array_migration>` section of the introduction to
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:mod:`dpctl.tensor` to examples on how to resolve ``ExecutionPlacementError`` exceptions.
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