Move MediaTek docs to new page

Author: GregoryComer

docs/source/build-run-mediatek-backend.md

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 # MediaTek Backend
 
-Placeholder
+MediaTek backend empowers ExecuTorch to speed up PyTorch models on edge devices that equips with MediaTek Neuron Processing Unit (NPU). This document offers a step-by-step guide to set up the build environment for the MediaTek ExecuTorch libraries.
+
+::::{grid} 2
+:::{grid-item-card}  What you will learn in this tutorial:
+:class-card: card-prerequisites
+* How to export and lower a PyTorch model ahead of time with ExecuTorch for MediaTek devices.
+* How to build MediaTek backend and examples.
+* How to deploy the exported models on device with ExecuTorch runtime.
+:::
+:::{grid-item-card}  Tutorials we recommend you complete before this:
+:class-card: card-prerequisites
+* [Introduction to ExecuTorch](intro-how-it-works.md)
+* [Setting up ExecuTorch](getting-started-setup.md)
+* [Building ExecuTorch with CMake](runtime-build-and-cross-compilation.md)
+:::
+::::
+
+
+## Prerequisites (Hardware and Software)
+
+### Host OS
+- Linux operating system
+
+### Supported Chips:
+- MediaTek Dimensity 9300 (D9300)
+
+### Software:
+
+- [NeuroPilot Express SDK](https://neuropilot.mediatek.com/resources/public/npexpress/en/docs/npexpress) is a lightweight SDK for deploying AI applications on MediaTek SOC devices.
+
+## Setting up your developer environment
+
+Follow the steps below to setup your build environment:
+
+1. **Setup ExecuTorch Environment**: Refer to the [Setting up ExecuTorch](https://pytorch.org/executorch/stable/getting-started-setup) guide for detailed instructions on setting up the ExecuTorch environment.
+
+2. **Setup MediaTek Backend Environment**
+- Install the dependent libs. Ensure that you are inside `backends/mediatek/` directory
+   ```bash
+   pip3 install -r requirements.txt
+   ```
+- Install the two .whl downloaded from NeuroPilot Portal
+   ```bash
+   pip3 install mtk_neuron-8.2.13-py3-none-linux_x86_64.whl
+   pip3 install mtk_converter-8.9.1+public-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
+   ```
+- Set evironment variables for building backend
+   ```bash
+   export NEURON_BUFFER_ALLOCATOR_LIB=<path_to_buffer_allocator.so>
+   ```
+
+## Build
+
+### Ahead of time:
+
+**Exporting a PyTorch Model for MediaTek Backend**:
+1. Lower and export the `.pte` file for on-device execution. The export script samples are povided under `example/mediatek/`. For example, the following commnad exports the `.pte` using the scripts provided.
+```bash
+cd executorch
+
+./examples/mediatek/shell_scripts/export_oss.sh mobilenetv3
+```
+
+2. Find the `.pte` files under the directory named as same as the model.
+
+### Runtime:
+
+**Build MediaTek Backend for ExecuTorch Runtime**
+1. Navigate to `backends/mediatek/scripts/` directory.
+
+2. **Build MediaTek Backend**: Once the prerequisites are in place, run the `mtk_build.sh` script to start the build process:
+   ```bash
+   ./mtk_build.sh
+   ```
+
+3. MediaTek backend will be built under `cmake-android-out/backends/` as `libneuron_backend.so`.
+
+**Build a runner to execute the model on the device**:
+1. Build the runners and the backend by exedcuting the script:
+```bash
+./mtk_build_examples.sh
+```
+
+2. The runners will be built under `cmake-android-out/examples/`
+
+## Deploying and running on a device
+
+1. **Push MediaTek universal SDK and MediaTek backend to the device**: push `libneuronusdk_adapter.mtk.so` and `libneuron_backend.so` to the phone and export it to the `$LD_LIBRARY_PATH` environment variable before executing ExecuTorch with MediaTek backend.
+
+   ```bash
+   export LD_LIBRARY_PATH=<path_to_usdk>:<path_to_neuron_backend>:$LD_LIBRARY_PATH
+   ```