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docs/install_guides/configurations-for-intel-gna.md
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# Configurations for Intel® Gaussian & Neural Accelerator (GNA) with OpenVINO™ {#openvino_docs_install_guides_configurations_for_intel_gna}
@sphinxdirective
> **NOTE**: On platforms where Intel® GNA is not enabled in the BIOS, the driver cannot be installed, so the GNA plugin uses the software emulation mode only.
.. note:: On platforms where Intel® GNA is not enabled in the BIOS, the driver cannot be installed, so the GNA plugin uses the software emulation mode only.
### Drivers and Dependencies
@endsphinxdirective
Intel® GNA hardware requires a driver to be installed on the system.
## Drivers and Dependencies
@sphinxdirective
Intel® GNA hardware requires a driver to be installed on the system.
.. _gna guide:
@endsphinxdirective
## Linux
### Prerequisites
@ -21,31 +26,56 @@ Ensure that make, gcc, and Linux kernel headers are installed.
### Configuration steps
1. Download [Intel® GNA driver for Ubuntu Linux 18.04.3 LTS (with HWE Kernel version 5.4+)](https://storage.openvinotoolkit.org/drivers/gna/)
2. Run the sample_install.sh script provided in the installation package:
```sh
prompt$ ./scripts/sample_install.sh
```
@sphinxdirective
#. Download `Intel® GNA driver for Ubuntu Linux 18.04.3 LTS (with HWE Kernel version 5.4+) <https://storage.openvinotoolkit.org/drivers/gna/>`__
#. Run the sample_install.sh script provided in the installation package:
.. code-block:: sh
prompt$ ./scripts/sample_install.sh
You can also build and install the driver manually by using the following commands:
```sh
prompt$ cd src/
prompt$ make
prompt$ sudo insmod intel_gna.ko
```
.. code-block:: sh
prompt$ cd src/
prompt$ make
prompt$ sudo insmod intel_gna.ko
To unload the driver:
```sh
prompt$ sudo rmmod intel_gna
```
@sphinxdirective
.. code-block:: sh
prompt$ sudo rmmod intel_gna
.. _gna guide windows:
@endsphinxdirective
## Windows
Intel® GNA driver for Windows is available through Windows Update.
## What’s Next?
@sphinxdirective
Now you are ready to try out OpenVINO™. You can use the following tutorials to write your applications using Python and C++.
Developing in Python:
* `Start with tensorflow models with OpenVINO™ <https://docs.openvino.ai/nightly/notebooks/101-tensorflow-to-openvino-with-output.html>`_
* `Start with ONNX and PyTorch models with OpenVINO™ <https://docs.openvino.ai/nightly/notebooks/102-pytorch-onnx-to-openvino-with-output.html>`_
* `Start with PaddlePaddle models with OpenVINO™ <https://docs.openvino.ai/nightly/notebooks/103-paddle-onnx-to-openvino-classification-with-output.html>`_
Developing in C++:
* :doc:`Image Classification Async C++ Sample <openvino_inference_engine_samples_classification_sample_async_README>`
* :doc:`Hello Classification C++ Sample <openvino_inference_engine_samples_hello_classification_README>`
* :doc:`Hello Reshape SSD C++ Sample <openvino_inference_engine_samples_hello_reshape_ssd_README>`
@endsphinxdirective