[CPU][ARM][DOC] ARM documentation - 23.1 release (#19464)

* arm docs

* Update docs/OV_Runtime_UG/supported_plugins/CPU.md

Co-authored-by: Tatiana Savina <tatiana.savina@intel.com>

* Update docs/OV_Runtime_UG/supported_plugins/CPU.md

Co-authored-by: Tatiana Savina <tatiana.savina@intel.com>

* remove f16

* add space

* update plugin link

---------

Co-authored-by: Tatiana Savina <tatiana.savina@intel.com>

README.md

@@ -73,9 +73,9 @@ The OpenVINO™ Runtime can infer models on different hardware devices. This sec
             <td>Intel Xeon with Intel® Advanced Vector Extensions 2 (Intel® AVX2), Intel® Advanced Vector Extensions 512 (Intel® AVX-512), and AVX512_BF16, Intel Core Processors with Intel AVX2, Intel Atom Processors with Intel® Streaming SIMD Extensions (Intel® SSE)</td>
         </tr>
         <tr>
-            <td> <a href="https://docs.openvino.ai/2023.1/openvino_docs_OV_UG_supported_plugins_CPU.html">ARM CPU</a></tb>
-            <td><b><i><a href="https://github.com/openvinotoolkit/openvino_contrib/tree/master/modules/arm_plugin">openvino_arm_cpu_plugin</a></i></b></td>
-            <td>Raspberry Pi™ 4 Model B, Apple® Mac mini with M1 chip, NVIDIA® Jetson Nano™, Android™ devices
+            <td> <a href="https://docs.openvino.ai/2023.1/openvino_docs_OV_UG_supported_plugins_CPU.html#doxid-openvino-docs-o-v-u-g-supported-plugins-c-p-u">ARM CPU</a></tb>
+            <td><b><i><a href="./src/plugins/intel_cpu">openvino_arm_cpu_plugin</a></i></b></td>
+            <td>Raspberry Pi™ 4 Model B, Apple® Mac with Apple silicon
         </tr>
         <tr>
             <td>GPU</td>

docs/OV_Runtime_UG/supported_plugins/CPU.md

@@ -52,7 +52,7 @@ CPU plugin supports the following data types as inference precision of internal
 - Floating-point data types:
 
   - ``f32`` (Intel® x86-64, Arm®)
-  - ``bf16``(Intel® x86-64)
+  - ``bf16`` (Intel® x86-64)
 - Integer data types:
 
   - ``i32`` (Intel® x86-64, Arm®)

docs/OV_Runtime_UG/supported_plugins/Device_Plugins.md

@@ -24,6 +24,7 @@ OpenVINO™ Runtime can infer deep learning models using the following device ty
 * :doc:`CPU <openvino_docs_OV_UG_supported_plugins_CPU>`
 * :doc:`GPU <openvino_docs_OV_UG_supported_plugins_GPU>`
 * :doc:`GNA <openvino_docs_OV_UG_supported_plugins_GNA>`
+* :doc:`Arm® CPU <openvino_docs_OV_UG_supported_plugins_CPU>`
 
 For a more detailed list of hardware, see :doc:`Supported Devices <openvino_docs_OV_UG_supported_plugins_Supported_Devices>`.
 

docs/dev/build_windows.md

@@ -27,12 +27,6 @@ Supported configurations:
     cd openvino
     git submodule update --init --recursive
     ```
-   (Extra for WoA) To build on Windows on ARM with ARM plugin:
-    ```sh
-    git clone https://github.com/openvinotoolkit/openvino_contrib.git
-    cd openvino_contrib
-    git submodule update --init --recursive
-    ```
 
 2. Create build directory:
     ```sh
@@ -40,16 +34,10 @@ Supported configurations:
     ```
 3. In the `build` directory, run `cmake` to fetch project dependencies and generate a Visual Studio solution.
 
-   On Windows x86 64-bits:
     ```sh
     cmake -G "Visual Studio 16 2019" -DCMAKE_BUILD_TYPE=Release <path/to/openvino>
     ```
 
-   On Windows on ARM for ARM64 architecture:
-    ```sh
-    cmake -G "Visual Studio 16 2019" -DOPENVINO_EXTRA_MODULES=<openvino_contrib>/modules/arm_plugin -DCMAKE_BUILD_TYPE=Release <path/to/openvino>
-    ```
-
 4. Build generated solution in Visual Studio or run `cmake --build . --config Release --verbose -j8` to build from the command line. Be aware that this process may take some time.
 
 5. Before running the samples, add paths to the Threading Building Blocks (TBB) binaries used for the build to the `%PATH%` environment variable. By default, TBB binaries are downloaded by the CMake-based script to the `<path/to/openvino>/temp/tbb/bin` folder.

docs/resources/Supported_Devices.md

@@ -30,7 +30,7 @@ Currently, processors of the 11th generation and later (up to the 13th generatio
 ||                                                                    | Intel® Core™ Processors with Intel® AVX2,                                                            |
 ||                                                                    | Intel® Atom® Processors with Intel® Streaming SIMD Extensions (Intel® SSE)                           |
 ||                                                                    |                                                                                                      |
-||   (Arm®)                                                           | Raspberry Pi™ 4 Model B, Apple® Mac mini with M1 chip, NVIDIA® Jetson Nano™, Android™ devices        |
+||   (Arm®)                                                           | Raspberry Pi™ 4 Model B, Apple® Mac with Apple silicon                                               |
 ||                                                                    |                                                                                                      |
 +---------------------------------------------------------------------+------------------------------------------------------------------------------------------------------+
 || :doc:`GPU <openvino_docs_OV_UG_supported_plugins_GPU>`             | Intel® Processor Graphics including Intel® HD Graphics and Intel® Iris® Graphics,                    |