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Aleksandr Voron 2023-10-05 11:51:12 +02:00 committed by GitHub
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6
README.md
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@ -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 mini with Apple silicon
</tr>
<tr>
<td>GPU</td>

2
docs/articles_en/about_openvino/compatibility_and_support/Supported_Devices.md
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@ -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 mini with Apple silicon |
|| | |
+---------------------------------------------------------------------+------------------------------------------------------------------------------------------------------+
|| :doc:`GPU <openvino_docs_OV_UG_supported_plugins_GPU>` | Intel® Processor Graphics including Intel® HD Graphics and Intel® Iris® Graphics, |

1
docs/articles_en/openvino_workflow/openvino_intro/Device_Plugins.md
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@ -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>`.

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docs/articles_en/openvino_workflow/openvino_intro/Device_Plugins/CPU.md
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@ -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®)